2021 Title, Contents, and Minutes (88th Annual Western Snow Conference, 2021)

Mapping Snow Grain Size Using LiDAR Intensity (Extended Abstract) - Chelsea Ackroyd; S. McKenzie Skiles (88th Annual Western Snow Conference, 2021)
Net solar radiation is the primary driver of snowmelt, which is mainly determined by snow albedo. Controls on snow albedo vary spectrally: in the visible wavelengths it is controlled by light-absorbing particles, including dust and black carbon. For clean snow, snow albedo is dependent upon ice absorption in the near infrared wavelengths, typically characterized using the effective grain size (Warren, 1982). Grain size is currently estimated using radiative transfer inversion methods that leverage reflectance data from passive optical remote sensing imagery. Theoretically, it may also be possible to relate lidar intensity to grain size when the wavelength of the lidar is in the near-infrared wavelengths: smaller grains would reflect more light back to the sensor, larger grains would reflect less. This indicates that lidar could be used to retrieve surface optical properties. Here, we evaluate how well aerial lidar intensity at 1064 nm can be related to the grain size of snow at the basin-scale.
Keywords: intensity; LiDAR; radiometric correction; remote sensing; snow grain size

“Our Winter Snows Are of the Utmost Importance”: The Development of Snow Surveys in British Columbia, 1920s-1950s - Blake Butler (88th Annual Western Snow Conference, 2021)
In the early twentieth century, British Columbian engineers realized that snow was one of the province’s most important resources. It was nature’s principal reservoir of “white coal,” or snow-melt run-off, an important energy source that powered industries and sustained communities. Private industries and large communities conducted some of British Columbia’s first snow surveys in the 1920s and early 1930s. The provincial government began its own snow survey program – in partnership with these earlier initiatives – in the mid-1930s in response to the economic challenges of the Depression and in collaboration with American snow science research along the Columbia River. Snow surveys expanded to much of southern British Columbia over the next fifteen years. The program’s growth reflected the government’s belief that snow and snow-melt run-off could best be understood and forecasted through scientific methods. But, during this period, engineers with the province’s Water Rights Branch (WRB) struggled to generate accurate run-off forecasts. In the immediate postwar era, the program’s growth was driven by immediate concerns, government policies that promoted economic development, and the continued desire to improve forecast accuracy. Knowing the early history of B.C.’s snow survey program helps explain its importance in the province today.
Keywords: British Columbia; snow; Snow survey; snow-melt run-off

Deep-Learning-Based Snowpack Mapping and Forecasting with Ground Observations: A Case Study Using A Wireless-Sensor Network in the American Basin (Extended Abstract) - Guotao Cui; Roger Bales (88th Annual Western Snow Conference, 2021)
Mountain snowpack in the Sierra Nevada is a major source of California’s water supply. Basin-scale snowpack is crucial hydrologic information for water-resources decision making (Bales et al., 2006), e.g. reservoir operation and flood control. In particular, during precipitation events associated with atmospheric rivers, rain-on-snow-melted snow can significantly augment basin runoff (Henn et al., 2020), highlighting the importance of near-real-time estimates and forecasts of snowpack for decision-making support. This study presents an approach based on a deep-learning Long Short-Term Memory (LSTM) model and a bias-correction method using ground snow measurements for snow mapping and forecasting. The approach is evaluated in the upper American River basin (elevation ≥1500 m, Figure 1).
Keywords: bias correction; deep learning; Snow mapping; Snow Water Equivalent (SWE); wireless-sensor network

Snowmelt Detection from Sentinel-1 Synthetic Aperture Radar in the Lajoie Basin, British Columbia - Sara Darychuk; Joseph Shea; Anna Chesnokova; Brian Menounos; Frank Weber; Georg Jost (88th Annual Western Snow Conference, 2021)
Snowmelt runoff supplements streamflow and soil moisture during warm summer months in Western North America. As direct snowpack measurements are sparse, many models exist to predict the release of runoff in alpine regions. An increase in spatially distributed observational data of seasonal snow may help to refine and improve these efforts going forward. Synthetic Aperture Radar (SAR) is sensitive to the liquid water content of snow and has been successfully used to map wet snow in alpine regions. We employ SAR and multispectral data to estimate the onset and duration of snowmelt in 2018 in the Lajoie Basin, British Columbia. We collate and process Sentinel-1, Sentinel-2 and Landsat-8 images in Google Earth Engine. A backscatter threshold is used to define the inferred period at which the snowpack is saturated and begins to generate runoff. Multispectral imagery is used to estimate snow-free dates across the basin to define the end of the snowmelt period. These methods are most effective on moderate to low slopes (< 30°) in open areas. This approach has high potential for adaptability to other alpine basins or regions and can be used for future model calibration.
Keywords: Google Earth Engine; remote sensing; snowmelt; snowpack dynamics; Synthetic Aperture Radar

Improving Streamflow Forecasts in the NOAA National Water Model Using Observational Constraints on Snowpack Albedo and Snow-Covered Area from STC-MODSCAG (Extended Abstract) - Thomas L. Enzminger; Aubrey L. Dugger; Karl Rittger; Edward H. Bair; James L. McCreight; Mark S. Raleigh; Mary J. Brodzik (88th Annual Western Snow Conference, 2021)
The NOAA National Water Model (NWM) is a physically-based modeling system which simulates major hydrologic processes across the conterminous United States (US). Difficulties in accurately simulating snowpack states hinder the NWM’s ability to provide high-quality streamflow forecasts, particularly in snow-dominated western US mountains. Errors in snowpack simulations propagate into streamflow time series as errors in both magnitude and timing of peak streamflow in snow-dominated basins. We imposed observation-based constraints on simulated fractional snow-covered area (fSCA) and snowpack albedo in the NWM using remotely sensed data and investigated the impacts on simulated snow states and streamflow over the Upper Colorado River Basin. We identified a set of parameters that influence the relationship between snow depth and fSCA (the snow depletion curve) and seasonal snowpack evolution. For each parameter, we derived spatially-distributed values using 15 years of data from STC-MODSCAG (Spatially and Temporally Complete MODIS Snow-Covered Area and Grain Size), which provides daily estimates of fSCA, snowpack albedo, and other variables at ~500 m spatial resolution. When implemented into the NWM’s snow model, the derived values tended to shift simulated streamflow peaks lower and earlier, often improving agreement with observed streamflow. Results from these experiments will help to improve streamflow forecasting for water management and inform NWM data assimilation strategies with model parameter uncertainties.
Keywords: MODSCAG; National Water Model; snow-covered area; snowpack albedo; streamflow

Evaluating the Snow-Wildfire Relationship Using an Ensemble of Snowpack Observations - Alex Gottlieb; Justin Mankin (88th Annual Western Snow Conference, 2021)
Wildfire activity in the United States has increased in recent decades, with documented rises in the number of large fires, burned areas, and the length of the fire season (Westerling, 2016). Fires contribute to carbon emissions, widespread forest mortality, and human morbidity and mortality by posing a direct hazard and from degrading air quality. Wildfire increases are thought to be a product of several interacting factors, including human settlement in fire-prone areas, a legacy of fire suppression, as well as favorable fire weather partly attributable to anthropogenic climate change (Abatzoglou and Williams, 2016). As such, a deeper understanding of the geophysical drivers of wildfire activity can both improve its seasonal predictability and inform expectations about future wildfire under continued warming.
Keywords: climate change; ensembles; Snow water equivalent; wildfire

Review of the Past 20 Years of Hydroclimate Data in Yosemite National Park (Poster) - Rachel Hallnan; Chad Anderson; Catherine Fong (88th Annual Western Snow Conference, 2021)
The impacts of climate change are projected to be profound in mountainous, snowpack dominated regions of the Sierra Nevada Mountains. Anticipated impacts include a shift in precipitation from snow to rain, increasing snow lines, higher air and stream temperatures, and shifting snowmelt and peak runoff timing earlier in the year. Such changes have implications on natural resources such as vegetation distribution, stream ecosystems and water quality, natural fire regime, wildlife abundance and diversity, and the quantity and distribution of water resources valued and stewarded by the National Park Service. Yosemite National Park, spanning elevations from 640 – 4000 m in the central Sierra Nevada Mountains is equipped with a robust network of snowpack, meteorological, and stream monitoring instrumentation, and provides a unique opportunity to examine water regime shifts over time. Data collection within the park is often a collaborative effort between park resource managers, researchers, and state agencies to satisfy multiple objectives. For park resource managers, these long-term datasets provide an opportunity to examine local weather and climate trends to better understand local climate change impacts and use this knowledge to inform resource management decisions. Presented here are long term trends in temperature and precipitation for the high elevations of the park, and trends in snowpack and streamflow timing over the past twenty years of hydroclimate monitoring within Yosemite.
Keywords: climate change; runoff; Sierra Nevada; snowmelt; Yosemite

Potential Improvements to Colorado River Basin Forecast Center Water Supply Forecasts Using External Snow Products - Patrick Kormos; Craig Peterson; Michelle Stokes; John Lhotak; William P. Miller (88th Annual Western Snow Conference, 2021)
The amount of water stored as mountain snow is the primary driver of seasonal (April through July) streamflow volumes in the Upper Colorado River and Eastern Great Basins. The Colorado Basin River Forecast Center (CBRFC) publishes seasonal, volumetric water supply forecasts starting in January for spring runoff volumes. CBRFC streamflow forecasts are used to provide impact-based decision support services throughout the region. The CBRFC continually seeks to improve their forecasts by incorporating new information into their hydrologic forecast system. To this end, the CBRFC is investigating the usability of external snow products in the current forecasting system. The CBRFC conducted an error attribution analysis to compare the uncertainties in April 1st water supply forecasts related to CBRFC hydrologic model errors and unknown future spring weather. Errors in model snow states are some portion of the larger model errors, along with errors from model soil moisture states, calibration parameters, model structure, etc. Results indicate that on average, roughly half of the forecast error in an April 1st water supply forecast is attributed to the unknown spring weather. It follows that improvements in model April 1st snow states can be expected to improve some portion of the other half of the April 1st forecast error.
Keywords: forecast error; operational forecasting; remote sensing of snow; river forecast center; streamflow forecasts

History of the SR50 Snow Depth Sensor, from Research to Operational Use: the Challenge of Producing Useful Data for Snow Operations Group, Snowfall as a Focus (Poster) - Claude Labine (88th Annual Western Snow Conference, 2021)
The SR50 snow depth sensor is used worldwide in automatic snow depth measurements (CIMO Survey for Solid Precipitation, 2009). The history of its development is a good example of the conference theme, “Bridging the gap between Research and Operations”.
Keywords: applications; instrument development; research; snow depth; snowfall data

Measuring Snow Depth Using RPAS Photogrammetry in a Subalpine Coastal Region of British Columbia (Extended Abstract) - Alexandre Landry; William Floyd; Will McInnes; Keith Holmes; Santiago Gonzalez Arriola; Alex Cebulski; Trevor Dickinson; Stewart Butler; Derek Heathfield; Brian Menounos (88th Annual Western Snow Conference, 2021)
Mountain snow in British Columbia is primarily monitored using automated remote weather stations, which measure snow depth (SD), snow water equivalent (SWE), and multiple weather parameters, and a manual snow survey program, with records dating back to the 1930’s The network provides excellent information to track change through time and data are effectively used to provide regional forecasts for both flooding and drought, however there is still high uncertainty when scaling these measurements to the watershed level. In addition, there is potential for the current network of stations and snow courses to have more frequent snow free years due to climate change, and gaining a better understanding of how they represent snow that occurs above them is needed. Advances in remote sensing technologies present important opportunities to accurately measure the high degree of spatial variation in SD, and use existing methods (Hill et. al., 2019; Strum et. al., 2010) or develop new approaches to improve estimates of snow density and SWE at finer spatial resolutions. To help address the limitations of relying on discrete, in-situ SD sampling and reduce the uncertainties in overall snowpack measurements, small remotely piloted aircraft systems (RPAS) based structure-from-motion photogrammetry (SFM) has emerged as an effective technology. While they are not capable of measuring areas at the same scale as full-size aircraft or satellites, certain RPAS can be used to capture data across several square kilometres, are much less cost prohibitive and their potential to produce 3D models at high accuracies and very fine spatial resolutions is becoming increasingly well established.
Keywords: point cloud filterin; remote sensing; RPAS; snow depth; structure from motion photogrammetry; vegetation

An Improved Temperature-Index Snowmelt Model on a Watershed Scale Using an Hourly Time Step for Real-Time Flood Forecasting in British Columbia, Canada (Poster) - Charles Luo (88th Annual Western Snow Conference, 2021)
One of the important indicators of a good real-time flood forecasting system is its time efficiency or the ability to produce timely forecasts. The majority of watersheds in British Columbia, Canada are large-scale snowmelt-dominated watersheds. Therefore, a simple but efficient snowmelt model helps improve time-efficiency of the real-time flood forecasting system. The temperature-index snowmelt model is one of this kind. However, it is more accurate when applied on a forest stand scale rather than on a watershed scale, and its time step is usually one day. The real-time flood forecasting system in British Columbia is the CLEVER Model, in which a watershed is simplified into a single node, and which adopts an hourly time step. In this study, the commonly used equation of temperature-index snowmelt model was improved and adapted to the application on a watershed scale using an hourly time step so that relative high forecasting accuracy and time efficiency were both achieved in the CLEVER Model.
Keywords: real-time flood forecasting; snowmelt model; time-index method; watershed model

SNOWCLIM: High Resolution Snow Model and Data for the Western United States (Extended Abstract) - A.C. Lute; John Abatzaglou; Timothy Link (88th Annual Western Snow Conference, 2021)
Seasonal snowpack shapes the climatic, hydrologic, ecological, economic, and cultural characteristics of many global regions. In many mountain regions, recent decades have seen less precipitation falling as snow, lower peak snow water equivalent (SWE), shorter snow duration, and earlier snowmelt runoff as a result of anthropogenic climate change (Knowles et al., 2006; Mote et al., 2018; Choi et al., 2010; Fritze et al., 2011). These developments are expected to continue in the coming decades, resulting in substantial declines (>50%) in seasonal snowpack for areas such as the western US and significant impacts to human and natural systems (Fyfe et al., 2017; Huss et al., 2017). Understanding these changes and their implications often requires snow models and modeled snow data products (hereafter snow data) that satisfy at least one of several criteria. These criteria might include that the data is a) simulated with physics-based representations of energy and mass transfer processes, b) spatially continuous, c) high spatial resolution, d) large extent, e) multivariate, and f) multitemporal. There are two major hurdles to the development of a snow dataset that meets these criteria: computational cost and appropriate forcing data.
Keywords: climate change; gridded data; snow modeling

Basic Science of Rain on Snow - Bruce McGurk; Randall Osterhuber; Rick Kattelmann (88th Annual Western Snow Conference, 2021)
Rain on snow is a common event in the Sierra Nevada that occasionally generates floods, but has also generated coFnsiderable speculation and conjecture. This paper will summarize basic snowpack formation, structure, and response to melt and rain on its surface. Water transmission through snow is complex because the snowpack structure depends on the characteristics of the storms that created it, and no two years ever produce a snowpack with the same characteristics. The Sierran snowpack above 2100 m ranges from 2-5 m in depth at peak accumulation, and by spring, it is composed of 8-12 major layers that correspond to the prior major storm events. Melt and/or rain water transmission through snowpack is complex because the layers have varying temperature and densities, and the presence of crustal boundary layers that form during sunny, inter-storm periods. Rain on snow is transmitted both vertically and laterally along layers and interfaces, and steeper slope increases the horizontal speed and amount that may be delivered directly to stream channels. Vertical flow channels are often created that allow relatively rapid delivery of water to the soil surface. Rain can melt snow, particularly when lower or mid-elevations become snow-covered in cold storms and then are subsequently exposed to warm storms with high temperatures and winds. Contributions of that melted snowpack are typically small compared to the amount of rain that fell, some of which creates immediate runoff. Rain-on-snow frequency and magnitude are increasing in the central Sierra Nevada, and the rain is reaching higher elevations more often (Osterhuber, 2019). Because runoff magnitude and timing are directly linked to the extent of the basin that receives rain as well as snowpack condition, this issue demands increased awareness and study of the snowpack as well as improved forecasting and verification of the rain-snow elevation of an incoming storm.
Keywords: flow fingers; ice crusts; Rain on snow; snow layers; snowpack; water transmission

Snow As a Driver of Soil Biogeochemical Cycling in the Semiarid Dryland Cereal Production Systems of the Northern Great Plains (Poster) - Caitlin Mitchell; Stephanie Ewing; Robert Payn; Tobias Koffman; Eric Sproles (88th Annual Western Snow Conference, 2021)
In the Judith River Watershed (JRW) of the Upper Missouri River Basin in central Montana (Figure 1), extensive non-irrigated cereal crop production occurs on thin, well-drained soils susceptible to water loss and nitrate leaching1,2. This landscape consists of fluvial terraces and alluvial fans with shallow, unconfined aquifers that are vulnerable to accumulating nitrate leached from overlying soils and thus commonly host groundwater concentrations twice the EPA drinking water standard of 10 mg N L-1. In these non-irrigated agricultural systems of the Northern Great Plains, snow provides a vital source of winter and spring water for crop production 3,4, yet the role of snow as a driver of nitrate dynamics in these soils is less understood5. Additionally, the distribution of snow across these relatively flat cultivated areas is highly variable, with wind patterns and the character of crop stubble dictating when and where snow accumulates, melts, and infiltrates – ultimately contributing water to soil storage4.
Keywords: nitrate; prairie snow; soils; water isotope

Topographic Correction of Snow Albedo Measured from a UAV (Extended Abstract) - Andrew Mullen; Eric A. Sproles; Jordy Hendrikx; Joseph A. Shaw; Charles Gatebe (88th Annual Western Snow Conference, 2021)
The albedo of seasonal snowpack exerts considerable control on the Earth’s energy balance and is highly variable throughout space and time. Accurate quantification of snow albedo can be achieved through physically-based modeling approaches that are initialized or updated by optical satellite observations. Near-surface measurements are critical for validating both modeled and satellite-based reconstructions of snow albedo. Uncrewed Aerial Vehicles (UAVs) equipped with upward and downward-facing pyranometers provide high-resolution measurements of broadband albedo, spatially distributed across landscapes at scales not attainable by current satellite technologies. UAV surveys can deploy across heterogeneous terrain to acquire representative measurements of a diverse range of snow-covered environments, providing an improved source of calibration and validation data over traditional point-based measurements. Since UAV measurements can be taken near the surface (10 m - 100 m), they greatly reduce atmospheric and geolocational error sources. Near-surface measurements are still susceptible to other sources of error that must be corrected for if measurements are to be used operationally. Variable terrain introduces error in albedo measurements as reflectance measurements are not representative of surface conditions when they are taken at an oblique angle to the surface, introducing the need for topographically corrected albedo measurements. The tilt of the UAV platform can also compound this error.
Keywords: albedo; Landsat 8; Topographic; uncrewed aerial vehicle

A New Instrumental Way to Measure Snowfall SWE in Mountain and Polar Catchments Directly, on the Kilometer-Scale and in Near Real Time (Poster) - Hamish D. Pritchard (88th Annual Western Snow Conference, 2021)
The Snow Water Equivalent (SWE) of snowfall is important but difficult to measure. While numerous techniques have been developed, measurements are still too sparse, too poorly distributed, too infrequent, too biased and too small to represent the variability of SWE in mountain landscapes. Snow pillows, pluviometers and other instruments have not solved this problem: precipitation products have large biases over mountain ranges worldwide. A novel measurement technique can now provide direct observations of snowfall SWE in polar and alpine settings accurately and on far larger spatial scales than most existing in situ methods, over areas comparable to model and satellite resolutions. By sensing water-pressure changes in lakes it is directly sensitive to the mass of new snowfall over the whole area of the lake, rather than a proxy for mass or a measurement at a point, and it is capable of high-frequency, high-resolution, low-cost and low-bias SWE measurements that do not saturate over time. Tests of this technique show it to be highly sensitive to falling snow, and highlight the sometimes-large errors present in conventional instruments, precipitation models and products.
Keywords: lake; pressure; snowfall; SWE; water

Benefit/Cost Ratios for Snow Management Techniques on Dryland Agricultural Lands - H. Steppuhn; R.P. Zentner (88th Annual Western Snow Conference, 2021)
At least a third of the land covered by winter-accumulated snow across western North America between the 40th and 60th latitudes includes agricultural fields and livestock ranges. Snow-covers on these lands constitute a valuable natural resource available for management to increase dryland crop growth and commodity production. Managing the deposition of snows complements most cropping systems very well. Snow-covers insulate, protect, and provide water for overwintering and spring-seeded crops against freezing temperatures, damaging winds, and drought. The basic objective in designing techniques for utilizing more of the snow available is to provide snow-retention capacity equal to the expected delivery of snow to the field or rangeland being managed. The benefit/cost ratios associated with snow management vary with the technique. They depend on many factors: initial costs, amortization life, snow-cover accumulations and storage capacities, winter temperatures, melt water captures, historic annual soil recharges from snow, crop choices and yields, weather-related demands, annual commodity returns, producer tolerances of inconveniences, field implement availability, etc. For annual cropping of cereal grains on the Canadian Prairies, one study reported estimated benefit/cost ratios ranging from 0.70 for field fencing to 68.0 for crop stubble height increases with ample snow and from 0.01 to 6.40 with scant snow, respectively. The costs for many techniques are so low that snow management can be practiced for 3, 4, or so years in sequence before costs, including interest, start outweighing benefits from one good snow year.
Keywords: benefit/cost ratio; dryland agriculture; grazing livestock; hay crop; snow management

Toponomy Based on Winter, Cold, and Snow for Municipalities in Western and Northern Canada - Jerry Toupin (88th Annual Western Snow Conference, 2021)
Toponomy is the science/art of naming places. This article examines how winter, cold and snow can influence the name of municipalities and other entities in Western and Northern Canada. Since this country is one of the coldest in the world during wintertime, one would expect several places named after these terms. A list has been set up for British Columbia, Alberta, Saskatchewan and Manitoba covering Western Canada and Yukon, Northwest Territories and Nunavut for Northern Canada.
Keywords: names; places; toponomy; weather; Winter in Canada

Impact of the Spatial and Temporal Variability of Snowpack Condition on Internal Liquid Water Fluxes - Eole Valence; Michel Baraer (88th Annual Western Snow Conference, 2021)
The seasonal snow cover plays an important hydrological role in cold regions. The terrestrial cryosphere, which is highly sensitive to climate change, raises questions about how the evolution of snowpack characteristics will affect water resources in non-mountainous environments. The present paper presents the first results from a multimethod study on the interconnections between the snowpack structure and its internal liquid water fluxes. Fieldwork for the study was conducted at the experimental watershed of Ste-Marthe QC, Canada (BVE Ste-Marthe during winter 2020–2021. We combined the application of drone-based high-frequency ground-penetrating radar (GPR), near-infrared (NIR) and red-green-blue (RGB) photogrammetry, time-domain reflectometry (TDR moisture), stable isotopes of water, and monitoring of snowpack properties throughout the winter season. We focused on weekly drone-based GPR surveys conducted over a flat and a sloped zone of the study site. Two-way travel time (TWT) transects extracted from the radargrams are superimposed to snow depth from HD digital elevation models to compute permittivity profiles. Results show differences in hydrological response to the mild episode on March 11. The use of drone-based GPR for the study of spatiotemporal snowpack properties variability appeared extremely promising.
Keywords: drone-based GPR; effective permittivity; high-frequency GPR; rain-on-snow; UAV photogrammetry

Colorado Airborne Snow Observatories (CASO) Expansion Plan Project (Extended Abstract) - Taylor Winchell; Laurna Kaatz; Emily Carbone; Ken Curtis; Page Weil (88th Annual Western Snow Conference, 2021)
The Colorado Airborne Snow Observatories (CASO) Expansion Plan project is a state funded effort to develop a plan that communicates the water-management value of Airborne Snow Observatories (ASO) flights and proposes steps towards a statewide ASO program. The project began in April, 2021, and is scheduled to conclude in November, 2021. The planning and organizing team for the project consists of Denver Water, Northern Water, Dolores Water Conservancy District, Lynker, and Airborne Snow Observatories Inc. In addition to the planning team, the project has a stakeholder workgroup with over 100 individual members representing a wide variety of water interests—municipal, environmental, agricultural, recreation, state government, federal government, tribal government, and the academic/research community.
Keywords: Airborne Snow Observatory; ASO; Colorado; stakeholder workgroup; Water management

2019 Title, Contents, and Minutes (87th Annual Western Snow Conference, 2019)

Snow Cover Trends Over High Mountain Asia from Modscag - Chelsea Ackroyd; S. McKenzie Skiles; Karl Rittger; Joachim Meyer (87th Annual Western Snow Conference, 2019)
Snow from the Hindu Kush Himalaya (HKH) significantly contributes to the water resources that millions depend upon downstream (Immerzeel et al., 2010). Several countries, including Bhutan and Pakistan, depend on snowmelt for agriculture and energy-generating purposes, both of which are main components of these local economies (Sharma et al., 2014; Atif et al., 2018). In addition to its socioeconomic impacts, snow cover in this region also contributes to Earth’s intricate feedback systems. A decrease in snow lowers the surface albedo and increases the energy absorbed, known as the snow albedo feedback; a highly effective radiative forcing mechanism that contributes to climate change (Hall and Qu, 2006). As the HKH encompasses more snow and ice than anywhere else in the world outside of the polar regions (Panday et al., 2011), a decline in snow would alter the earth’s energy budget. Therefore, it is important to understand how snow patterns are changing over time in this region.

Transformation of the SNOTEL Temperature Record – Methodology and Implications - Chris R. Brown; Brian Domonkos; Troy Brosten; Tony DeMarco; Alex Rebentisch (87th Annual Western Snow Conference, 2019)
SNOTEL (SNOw TELemetry) sites collect voltage output data from in-situ temperature sensors (along with other environmental sensors) and transmit these values to the National Water and Climate Center (NWCC) where they are calculated into temperature values using a prescribed algorithm. Beginning in the 1990s, the YSI 44019A thermistor with the 44211A thermilinear package (the extended range YSI temperature sensor) replaced the YSI 44230 temperature sensor as the default temperature sensor deployed at SNOTEL sites because of its broader temperature range. Temperature was calculated from output voltage using a linear least-squares regression developed at the NWCC. There is a step shift in SNOTEL temperature data beginning in the late 1990s, thought to be caused primarily by the switch to the extended-range YSI temperature sensor and the associated algorithm to calculate temperature at SNOTEL sites. A working group within the Natural Resources Conservation Service Snow Survey and Water Supply Forecasting Program conducted an empirical study to characterize the extended range YSI temperature sensor and develop a polynomial algorithm to better calculate temperature from output voltage. The working group has proposed transforming the historical SNOTEL extended-range YSI sensor temperature record and incoming values using this new algorithm. SNOTEL temperature data is used by many public and private entities in varying ways and transforming the dataset could affect products or management decisions that have already been made. The working group would like to gather feedback from users of SNOTEL temperature data on the implications of transforming the historical dataset and incoming data.
Keywords: instrumentation changes; SNOTEL; temperature correction; temperature sensor; thermistor

Montane Forest Water Use Under Increased Episodic and Earlier Snowmelt - Ava Cooper; Adrian Harpold (87th Annual Western Snow Conference, 2019)
Western U.S. montane forests rely disproportionately on snowmelt, which potentially makes them sensitive to changes in snowpack to alter large-scale water and carbon budgets. We used an aspect transect of sap flow and meteorological measurements in Sagehen Creek watershed, in the Sierra Nevada mountains, to empirically determine controls on the timing of water use by conifer forests. We determine which environmental variables (temperature, humidity, shortwave radiation, and soil moisture) are limiting sap flow across the growing season using a boundary lines analysis. We find that all sites exhibit transitions from energy limitations in spring, to water limitations in summer, and back to energy limitations in fall. Response of sap flow to predictors was more variable during spring than fall, which is consistent of more episodic temperature limitations in the spring. Later snowmelt leads to substantial transpiration prior to snow disappearance and trees were air temperature limited less of the time. Shifts from rain to snow under climate change might diminish existing forest refugia as snowmelt becomes more similar across slope aspects. Future efforts focused on modeling the relationship between snow water inputs and transpiration will be important to understanding the potential effects of climate change.

Rain–Snow Transition Elevation from Wireless Sensor Network in the American and Feather River Basins - Guotao Cui; Roger Bales; Martha Conklin; Robert Rice; Francesco Avanzi; Peter Hartsough (87th Annual Western Snow Conference, 2019)
Snowpack in the Sierra Nevada is important storage of winter precipitation, which provides snowmelt to support California’s water supply during dry seasons. In mountainous areas, snow cover shows large temporal and spatial variability and sensitive to changes in precipitation (rainfall or snowfall) and temperature. To determine the phase of precipitation, which is essential information in runoff forecasting and water resources management, one method is to derive the rain-snow transition elevations during storm events. This study evaluates a ground-based method to obtain rain-snow transition elevation with measurements from strategically designed Wireless Sensor Network (WSN) in the American River and Feather River basins (Figure 1).

A Field Study of Snowpack Ablation at Sagehen Creek Field Station - Stephen Drake; Holly J. Oldroyd; Anne W. Nolin; Alex Greenwald; Sydney Weiss; Keith S. Jennings; Mikey Johnson; Gavin R. Shields (87th Annual Western Snow Conference, 2019)
Preliminary results of a field experiment at Sagehen Creek Field Station, CA during the 2018/2019 winter season are presented. We deployed five flux towers across a subalpine forest/meadow transition zone to compare ablation processes of proximal sites. Differences in longwave and shortwave radiation, air temperature, and sublimation were observed between the five sites, varying with solar aspect, tree density, and other locale-specific parameters. Longwave exitance from snow had a sphere of influence less than 10 m whereas shortwave insolation had a range of influence up to an order of magnitude greater and depended on sun angle and tree height. Sublimation differences between sites were magnified as wind speed increased. Drifted snow caused by an isolated tree was not significant for this warm snow site.
Keywords: ablation; forest; hydrology; radiation; snow; surface energy fluxes

Forest Canopies Influence the Deposition and Concentration of Debris, Lightabsorbing Impurites, and Pollutants in the Sierra Nevada Snowpack - Kelly E. Gleason; Joseph R. McConnell; Monica M. Arienzo; Nathan Chellman; Christine Hedge; Adrian Harpold (87th Annual Western Snow Conference, 2019)
Forests are typically warmer than surrounding open areas, particularly in warm mid-latitude climates, and forest canopies radiate longwave radiation throughout the winter, driving mid-winter snowmelt throughout the snow accumulation period. During winter, forest canopies shed organic debris onto the snowpack below, which concentrates on the snow surface during snowmelt, and may further accelerate snowmelt due to reduced snow albedo. Snowpack, as long as it remains frozen, serves not only as a reservoir of water, but also as a time-resolved repository of local and regionally-sourced particles, including black carbon (BC), dust, organic debris, and pollutants. We evaluated how forests may alter the depositional process of particles and pollutants into the snowpack beneath forest canopies, as well as how warm conditions in forests influence the redistribution of particles and pollutants in the snowpack. We measured BC, dust, organic debris, and the elemental composition of pollutants throughout snowpacks in an open meadow and beneath a nearby pine forest each month during winter and early spring of 2017 at the Sagehen Experimental Forest in the Northern Sierra Nevada Mountains. Overall, snowpacks under the forest canopy had much greater concentrations of organic and inorganic debris, which concentrated on the snowpack surface throughout the snow season. While concentrations of BC, dust, and pollutants were similar under the forest canopy and in the open meadow during winter. During spring snowmelt, BC and dust became concentrated on the snowpack surface under the forest canopy and in the open meadow. Phosphorus and sulfur concentrations were greater under the forest canopy, while bismuth was greater in the open meadow during spring snowmelt. Nitrate concentrations on the snowpack surface were similar between sites, but reduced earlier in the meadow likely due to enhanced photodegradation. Throughout the snowpack season, debris, BC, dust and pollutants were much more variable under the forest canopy than the open meadow. Forest canopies serve as a source of large debris to the snowpack, but have little influence over the deposition and concentration of more regionally sourced light absorbing particles in the snowpack, and differential influence on the deposition and concentration of pollutants in the snowpack.
Keywords: accelerated snowmelt; black carbon; canopy debris; pollutant concentrations; Sagehen Experimental Forest; snow albedo

Forest Disturbance and the Impacts on Maritime Snow in the Oregon Cascades - Mikey Johnson; Anne Nolin (87th Annual Western Snow Conference, 2019)
The maritime mountain snowpack in Oregon’s Cascades is a critically important source of flows for the Willamette River Basin. Recent warm winters have reduced snowpack due to precipitation falling as rain rather than snow. Furthermore, landscape-altering forest fires have altered the energy balance, affecting snowpack retention. This research investigates changes in snow water equivalent (SWE) due to warmer climate and fires in the McKenzie River Basin. The McKenzie River supplies water and hydropower to the city of Eugene Oregon and is a key tributary of the Willamette River. In 2003 the B&B Complex Fire (367 km2) burned through Santiam Pass, at the headwaters of the MRB, severely burning the forest surrounding the Hogg Pass SNOTEL site. For this study, data were acquired from multiple SNOTEL and meteorological sites for the 20 years before and 15 years after the fire. We examined pre- and post-fire differences in SWE at the Hogg Pass SNOTEL site, in comparison with the nearby and unburned McKenzie SNOTEL site. We also modeled the changes in SWE, calibrating the model to the unchanged McKenzie SNOTEL and rerunning the model with a clear-cut forest cover to simulate disturbance. Next, we tested this model at the Hogg Pass SNOTEL for the years of pre- and post-fire. Results show that the measured SWE at the Hogg Pass SNOTEL it noticeably less in the years following the fire. Results from the modeled disturbance overestimate SWE at all times during the post-fire 2004 water year. From this, we conclude that the model’s landcover doesn’t fully represent the impacts on the snowpack following a forest fire. Further model development is needed to include these processes. This study is particularly relevant to water resource and forest managers who seek to understand how the declining seasonal snowpack will affect water availability and could increase the likelihood of more forest fires during the dry months.
Keywords: climate change; forest fires; maritime snowpacks; McKenzie River Basin

How the Reversal of the Magnetic Field of the Sun Modulates Snowfall in the Sierra Nevada Mountain Range of the Western United States - John A. Kleppe; Daniel S. Brothers (87th Annual Western Snow Conference, 2019)
We have shown in previous papers the major driving forces of winter precipitation, in the form of snow, in the Sierra, Cascade, and Rocky mountain ranges are the reversal of the sun's magnetic field and a statisticallyindependent "carrier" signal being generated by the Earth's large-scale atmospheric circulation parameters. In this paper we present the mechanism by which our proposed Sun-Earth magnetic carrier suppressed amplitude modulation system modulates the formation of the Sierra snowpack resulting in the generation of signals detected in the SWE records. We show how solar magnetic activity affects atmospheric circulation in the western tropical Pacific including the connections, between the El Nino-Southern Oscillation, the Walker circulation, and the resulting variability in the lower thermosphere. A combined solar and geomagnetic index for thermospheric climate is used along with wavelet analysis to explain how the reversal of the sun's magnetic field modulates the Sierra mountain snowpack. The results of this work will provide a very useful basis for studying drought patterns related to the magnetic activity of the sun.
Keywords: El Nino; Snow water equivalent; solar magnetic reversal

Towards a Decision Support Tool for Understanding the Effect of Forest Thinning on the Sierra Nevada Snowpack - Sebastian A. Krogh; Adrian Harpold; Patrick Broxton (87th Annual Western Snow Conference, 2019)
Snowmelt from the Sierra Nevada is a key water resource in the western US supporting economic development and ecological functions. Previous forest management practices have revealed that snowmelt volume depends on the complex interaction between changes to sublimation from canopy interception and net radiation at the snow surface. Despite decades of research, we lack insight into how to thin a forest to maximize snow accumulation and retention in complex topography. To better understand how different forest treatments might impact the snowpack, this study uses the Snow Physics and LiDAR Mapping (SnowPALM) model to simulate snowpack changes under a virtual forest thinning scenario over two mountainous watersheds at the west shore of Lake Tahoe, California. SnowPALM uses information about canopy density and height from lidar data to simulate tree-scale snow processes at 1-meter resolution. Questions addressed in this research are: what type of forest thinning are the most efficient to increase snow accumulation and melt volume, where do they have the largest impact, and what mechanism are driving these impacts? Simulations from this study will be used to produce a decision support tool for stakeholders, forest managers and policy makers at the west shore of Lake Tahoe.
Keywords: forest thinning; Lake Tahoe; LiDAR; snow hydrology

Snowpack Variability Across Forest Stand Boundaries in a Moderate Snowpack - Adrian Marziliano; Ryan Webb (87th Annual Western Snow Conference, 2019)
Snowpack in the southwestern United States is the largest source of water for irrigation and municipal use for much of the western states. The Colorado River alone provides water for some 40 million residents. As climate change continues to effect snowfall each year, the need for more accurate snow budget estimates will become increasingly important. The advancement of snow measurement methods and technologies has allowed for greater efficiency in data collection for calculating snow water equivalent (SWE) distribution. For these new technologies to be effectively utilized, a better understanding of the influences on snowpack variability is necessary. This study observes variability with regards to snow depth and density that could affect the accuracy of SWE estimates across forest stand boundaries. A forest stand boundary in the Sandia Mountains was studied to investigate variability between open and canopy transect locations. Snow pits and depth transects are utilized to study snowpack properties and changes thereof in the transect area. These results have the potential to increase the accuracy of water supply estimates from snowpack to increase the effectiveness of future water management budgets.
Keywords: energy budget; forest stand boundary; moderate snowpack; snow hydrology; snow variability; water resource management

Reconsidering the Utility of the April 1st Snow Water Equivalent Metric for Water Resource Applications - Keith N. Musselman; Nans Addor; Julie Vano; Noah P. Molotch (87th Annual Western Snow Conference, 2019)
Snow is the primary source of water in western North America (Li et al., 2017). In mountainous regions, seasonal snowpack accumulates in the winter and subsequently melts in the spring, effectively delaying the timing of downstream water delivery by as much as a half-year. Because of this capacity to store much of the annual precipitation and extend the delivery of meltwater into the arid spring and summer when demand is highest, snowpack is often referred to as a natural water tower. The date on which the snowpack mass, or snow water equivalent (SWE), reaches an annual maximum at a given location is literally and figuratively a watershed moment – dividing winter accumulation from spring melt and providing useful insight into the expected spring runoff. For these reasons, snowpack is vigilantly monitored across the West to inform reservoir operation and seasonal water supply forecasts that critically support agricultural and resource management decisions. For the past century, April 1st has been used to approximate the average date of maximum SWE. In fact, seasonal water supply forecasts are largely structured on this date. For example, before the 1950s water supply forecasts in the western U.S. were almost exclusively made for April to September – a period that includes both the snowmelt and agricultural irrigation seasons (Pagano et al., 2004). More recently, forecast target periods have been shortened to April to July to exclude the less-predictable summer rainfall (e.g., the monsoon season) in favor of the more-reliable delivery of meltwater. In warmer regions such as Arizona, New Mexico, and Idaho, forecast periods begin earlier to coincide with earlier snowmelt seasons and/or unique user needs such as earlier agricultural planting schedules. The consistent use of the April 1st metric in water resource applications – and compelling examples of warmer regions where operational forecasts deviate from that target date – begs numerous questions. First, how does the date of maximum SWE vary across western North America? Second, how has this date changed over the past 30+ years of observation in response to reported warming and snowpack declines (e.g., Mote et al., 2018)? Third, what is the hydrologic relevance of the date of maximum SWE? And fourth, how might this change this century? To address these questions, we present a long-term analysis of SWE data from 969 snowpack monitoring stations in western North America. This includes data from the US SNOTEL network, Alberta Environment and Parks, the Government of British Columbia, and the California Cooperative Snow Survey. The average date of maximum SWE varies geographically (Figure 1). The snowpack of the Sierra Nevada and inter-continental regions such as Idaho peak within a few days of April 1st, while the snowpack in the U.S. Pacific Northwest and Southwest peaks nearly a month earlier. In continental regions including Colorado, Wyoming, Montana and the Canadian Rockies, the timing of maximum SWE occurs closer to May 1st. Despite the large regional variability, the median date of maximum SWE computed on all stations and for the full period of record was within a few days of April 1st.
Keywords: April 1st; earlier snowmelt; maximum SWE; Snow water equivalent; SWE

Rain-On-Snow on Donner Summit, California - Randall Osterhuber (87th Annual Western Snow Conference, 2019)
Rain-on-snow events occur regularly during winter in the Donner Pass area of California, and their frequency is increasing. These storms have the potential to dramatically alter the stratigraphy of the snowpack, initiate rapid streamflow response, and cause local and downstream flooding. This paper reviews rain-on-snow events on Donner Summit, California at 2098 m elevation. Examined are case studies, rain-on-snow event size, duration, frequency, timing, anecdotal field observations, and supporting hydrometeorological data and snowpack response. Since the mid-1970s, personnel at the UC Berkeley Central Sierra Snow Laboratory have collected detailed information on precipitation type, highlighting the frequency and increasing trend of liquid precipitation during the (historic) snow season.
Keywords: flood; rain-on-snow; rainfall; snowpack outflow

Assimilating Subsampled Airborne Lidar: How Much Lidar is Enough? - Justin Pflug; Jessica D. Lundquist (87th Annual Western Snow Conference, 2019)
Airborne lidar snow depth retrievals are vital for water resource management in basins with limited snow observations. However, airborne lidar remains impractical to collect frequently over large domains due to the high economic cost. In this study, we investigated the extent to which lidar coverage improved modeled snow evolution using a distributed model and assimilation scheme. Full-coverage Airborne Snow Observatory snow depth data in Tuolumne, California and the Olympic Mountains of Northwest Washington State were used as a baseline in which to test the improvement in modeled snow water resources when optimizing flight frequency, timing, and spatial coverage. Collections over multiple seasons in Tuolumne were also used to investigate the impact when assimilating observed snow patterns. Our results indicate that errors in distributed models make snow depth difficult to determine at fine spatial resolutions. However, patterns from lidar in previous seasons are informative enough to train modeled accumulation in following years, therefore reducing the need for repeated, full lidar collections.
Keywords: assimilation; distributed modeling; LiDAR; snow patterns; tradespace

Forecasting the Effects of Snow Drought on Streamflow Volumes in the Western U.S. - Joshua T. Sturtevant; Adrian A. Harpold (87th Annual Western Snow Conference, 2019)
Mountain snowpack supplies critical water resources to natural ecosystems and downstream populations, particularly in semi-arid regions such as the Western U.S. Extremely low snowpack, or snow drought, can arise from inter-annual climate variability but is worsened by long-term declines in snowpack. Snow drought has negative implications for water availability as earlier, slower, and smaller snowmelt fundamentally changes runoff patterns including runoff efficiency and groundwater recharge rates. We explored the implications of snow drought on streamflow in the Western U.S. through the investigation of historical (1980-2014) observational data from the U.S. Geological Survey and Natural Resource Conservation Service for 59 watersheds. Our primary focus was evaluating the accuracy of April-July streamflow volume forecasts using the statistical method of Principal Component Regression (PCR). Early results indicate that forecast errors are highest during snow drought years, but that these errors vary across basins and are affected by precipitation received after the forecast issue date. We also show that forecast errors have a strong positive correlation with the inter-annual variability of runoff efficiency. Our objective is to refine statistically-based forecasting methods by introducing non-linearities into the forecast equations or subsetting the data into dry and wet years in order to improve streamflow volume forecasts during snow drought years.
Keywords: climate change; NRCS; snow drought; streamflow; Water supply forecasting

2018 Title, Contents, and Minutes (86th Annual Western Snow Conference, 2018)

Determining Trends in Snowline Elevation in the Indus Basin using MODSCAG - Chelsea Ackroyd; S. McKenzie Skiles; Joachim Meyer; NASA-JPL/ICIMOD SERVIR Team (86th Annual Western Snow Conference, 2018)
The amount of streamflow within the Indus Basin is highly dependent on snowmelt from the Himalayan mountains, even in comparison to other contributing factors such as glaciers and monsoonal rainfall. Because snow levels are sensitive to changes in climate, the water supply in this region and the millions of people downstream who rely on this finite resource are particularly susceptible to any change in temperature or precipitation. In order to observe the climate patterns in this basin, we produced a snowline elevation using both the MODIS Snow Cover and Grain Size product (MODSCAG) to determine the snow cover extent as well as ASTER data to determine the elevation. The changes in snowline elevation in the Indus Basin were assessed over a large portion of the current MODIS record (2000-2017). Based on these results, we are able to identify major climate trends and determine how such changes have impacted the Indus Basin over approximately the last two decades. (KEYWORDS: snowline elevation, Indus Basin, MODSCAG, remote sensing, snow cover)

Mapping Snow Cover on Mount Ranier, WA: Synthetic Aperture Radar Compared to MODIS Visual Imagery - Kate Baustian; Summer Rupper; Rick Forster; McKenzie Skiles (86th Annual Western Snow Conference, 2018)
In order to constrain the effects of climate change in mountain watersheds, an understanding of the spatial extent and timing of snowmelt is necessary. However, lack of field records and difficultly modeling in remote and complex terrain, lead to uncertainty in precipitation and temperature measurements across many mountainous regions. In this study, Synthetic Aperture Radar (SAR) data from the European Space Agency’s Sentinel-1 satellite is used to map wet snow over Water Year 2016 on Mount Rainier, a stratovolcano in the Cascade Range of Western Washington. Then, SAR wet snow maps are compared to a MODIS-derived factional snow-covered area product called MODSCAG. Results match an expected seasonal pattern while demonstrating the potential of SAR to provide high temporal and spatial resolution information that is not currently captured in common snow-covered area products. In the future, SAR could be used to improve understanding of snowpack characteristics in the Western United States. (KEYWORDS: Synthetic Aperture Radar, MODIS, MODSCAG, remote sensing, snow covered area, wet snow)

Ultrasonic Snow Depth Sensor Refurbishment and Testing at the NRCS National Water and Climate Center Electronics Maintenance Facility, Portland, OR - Chris R. Brown (86th Annual Western Snow Conference, 2018)
The Natural Resources Conservation Service (NRCS) National Water and Climate Center (NWCC) Electronics Maintenance Facility (EMF) in Portland, OR provides assistance and guidance to the NRCS Snow Survey and Water Supply Forecasting program regarding the use of electronic instrumentation to collect hydrologic and climatic data at SNOTEL (Snow Telemetry) and SCAN (Soil Climate Analysis Network) sites. Snow depth is an important component measured at SNOTEL sites. The most common sensor used to measure snow depth within the SNOTEL program is the ultrasonic snow depth sensor. Ultrasonic snow depth sensors are to be refurbished and tested at EMF or replaced every six years. When a snow depth sensor is returned to EMF, all the major electronic components, along with any degenerate sensor body components, are replaced by technicians, and the refurbished sensor is run through a ten-point test to ensure that it meets manufacturer and programmatic specifications. Sensors that meet specifications are redeployed at SNOTEL sites and field-checked annually. (KEYWORDS: SNOTEL, snow depth, direct snow measurement, instrumentation)

The Effect of Forest Structure on Snowpack Along Arizona's Mogollon Rim - Patrick Broxton; Willem J.D. van Leeuwen; Joel Biederman (86th Annual Western Snow Conference, 2018)
Keywords: Airborne LiDAR; Arizona; Forest Structure; Modelling; SWE

Does Dust and Pollution Aerosol Acting as Cloud Nucleating Particles Appreciably Impact Water Resources in the Colorado River Basin? - William R. Cotton; Vandana Jha (86th Annual Western Snow Conference, 2018)
Over the last decade, there have been numerous modeling and observational studies which suggest that anthropogenic aerosol pollution such as emitted by many industries, automobile exhaust, and coal-fired power plants, are quite hygroscopic and as such can serve as particles on which cloud droplets form or what we call cloud-condensation-nuclei (CCN). In the case of wintertime orographic clouds such as in Colorado, too many CCN lead to numerous cloud droplets which are so small that they suppress rain formation by collision and coalescence of cloud droplets (not very important for those clouds), but more importantly suppress snow formation via cloud droplets being collected by ice particles or what we call riming. Previous modeling studies by our group as well as other researchers suggest that aerosol pollution will result in reduced precipitation in the Colorado mountains, particularly in relatively wet storms. Another aerosol source important to precipitation processes is wind-blown dust. While some dust particles can serve as CCN, their numbers are so few that they are not competitive with natural or pollution aerosols in rain formation or ice particle riming. But dust is also known to be the most important natural source of ice nuclei (IN). Thus, long-range transported dust and locally produced in say the four corners region flow into the Colorado mountains and essentially seed those clouds with IN, much like purposely-produced cloud seeding, and enhance precipitation from wintertime orographic clouds. Here we present the first attempt to examine the combined impact of both aerosol pollution and dust on precipitation over the Colorado mountains for an entire snow year, the months of October to April in the year 2004-2005, which is a relatively wet snow year. (KEYWORDS: dust, pollution, aerosol, cloud condensation nuclei, ice nuclei, Colorado)

Classifying Forest-Edge Snow Depth Variability in Multiple Climates - William Ryan Currier; Jessica D. Lundquist (86th Annual Western Snow Conference, 2018)
Forest shading, scour, and wind related deposition result in significant snow depth variability between different sides of the forest edge (Broxton et al., 2015; Church, 1933; Geddes et al., 2005; Hiemstra et al., 2002, 2006; Marr, 1977; Musselman et al., 2008). The net effect of these physical snow processes is greater snow accumulation and longer snow retention on either leeward or north-facing forest edges (Golding & Swanson, 1978; Hiemstra et al., 2002, 2006; Lawler & Link, 2011; Tabler, 2003). Understanding the dominant modes of snow depth variability between forest-edges as a result of these physical processes is valuable when predicting watershed scale processes including streamflow magnitude, timing, and temperature, particularly during late summer flows (Clark et al., 2011; Leach & Moore, 2014; Luce et al., 1998, 1999; Lundquist et al., 2005; Lundquist & Dettinger, 2005; Sun et al., 2018).

From Drought to Floods: A Water Balance Analysis of the Tuolumne River Basin During Extreme Conditions, 2015-2017 - Andrew R. Hedrick; Danny G. Marks; Scott Havens; Mark Robertson; Micah Johnson; Micah Sandusky; Hans-Peter Marshall; Kat J. Bormann; Thomas H. Painter (86th Annual Western Snow Conference, 2018)
The mountain snowpack responds in various ways to changes in precipitation and temperature regimes. Climate predictions overwhelmingly agree that temperatures will continue to rise, but future shifts in precipitation are more uncertain in the current literature (Luce et al., 2016). Regardless of future precipitation trends, winters are shortening and the likelihood of extreme events is increasing (Jentsch et al., 2007). One way to determine the effect of extreme events on water resources in snow-dominated catchments is to disaggregate the individual physical processes at work into the constituent components.

Research and Development in Advancing Fluidless Snow Water Content Monitoring - Heggli, Anne; Heggli, Matthew; Trauman, Todd (86th Annual Western Snow Conference, 2018)
The U.S. Department of Agriculture (USDA) has coordinated the cooperative effort in snow surveying and water supply forecasting in the Western States since 1935. This initially involved the Research and Development (R&D) of progressive snowpack monitoring techniques, eventually bringing automated measurements that transmitted data directly to their office. The advances in snowpack monitoring provided more reliable and timely forecasts vital for farmers, business owners, and communities. The technology that is currently used to continuously measure Snow Water Equivalent (SWE), the snow pillow, was developed in the 1960’s, over 50 years ago. The snow pillow has been the only reliable SWE sensor despite the inherent limitations. With limited improvements in SWE monitoring to date, Alpine Hydromet set out to develop technology towards bringing a better solution for operators. This summarizes the R&D of two SWE sensors that aim to phase out the traditional fluid snow pillow while developing more reliable and robust technologies; the Fluidless Snow Pillow (FSP) and Cosmic Ray Detector (CRD). This analysis presents an indepth analysis of comparative data from the winter of 2016-17 and 2017-18 (partial winter through April, 2018) as tested at the UC Berkeley Central Sierra Snow Laboratory (CSSL). (KEYWORDS: snow water content, snow pillow, fluidless snow pillow, cosmic ray)

A Proposal for a Change in Winter Snowpack Suspension Criteria Used in the Conduct of Cloud Seeding Programs in Utah - Randall Julander; Jordan Clayton; Don Griffith; Candice Hasenyager (86th Annual Western Snow Conference, 2018)
Cloud seeding has long been recognized as a method of precipitation augmentation. In any given year, natural precipitation may range from exceptionally low to record highs. Clearly augmentation at low and average accumulations produces substantial water supply benefits and is the primary purpose for cloud seeding – to increase water supply. However, there needs to be clear criteria by which, in high accumulation years, cloud seeding is to be suspended due to the potential for snowmelt flooding. Years that have high snowpacks also have the highest potential for longer term, sustained high streamflow and flooding, years with lower snowpacks can and do produce flood events but normally require more extraordinary climatological phenomena to produce flooding and thus lower overall potential. As there are many and sundry causes for flooding and to be clear, the flood potential to be mitigated by snowpack cloud seeding suspension is specifically springtime snowmelt flooding/runoff. Other suspension criteria are used in the conduct of the Utah cloud seeding programs (e.g. no seeding during storms with high freezing levels that could produce winter flood events). Various other flooding mechanisms such as rain on frozen soil, urban flooding from impervious surfaces, flooding resulting from channel blockages, etc. would not be impacted by or mitigated by snowpack suspension criteria. To address the snowmelt flooding issue, streamflow points were selected that were either unimpaired or minimized upstream management. The USDA Natural Resources Conservation Service SNOTEL stations were generally selected based on high elevation and geographic location relevant to the watershed being investigated. An attempt to correlate Snow Water Equivalent (SWE) index values to observed historical flood events was largely unsuccessful. The 95th percentile or approximately the 20-year recurrence interval was used for the index suspension criteria because it assures a robust water supply for the water year and yet is low enough to reduce flood potential as many municipalities utilize the 100-year recurrence for storm water design. (KEYWORDS: cloud seeding, SNOTEL, water supply, Utah, suspension criteria)

Detection of Reversal of the Magnetic Field of the Sun in Snowfall Records in the Sierra, Rocky and Cascade Mountain Ranges of the Western United States - John A. Kleppe; Daniel S. Brothers (86th Annual Western Snow Conference, 2018)
The major driving forces of winter precipitation, in the form of snow, in the Sierra, Rocky, and Cascade mountain ranges are shown in this paper to be the reversal of the sun's magnetic field and a statistically independent "carrier" signal being generated by the Earth's large-scale atmospheric circulation parameters. We present wavelet analyses of several long-term Snow Water Equivalent (SWE) records from the Sierra, Rocky, and Cascade mountain ranges and found linkages between sunspots (i.e., the magnetic activity of the sun), and SWE. It is important to note the 11 year and 22-year visible sunspot cycles are NOT found in the SWE data, but rather, we found evidence of a Sun-Earth magnetic carrier suppressed amplitude modulation system that modulates the formation of the snowpack resulting in the generation of signals detected in the SWE records. The ISSN data were selected to match the Water Year (1 October to 31 March) and signed to account for the magnetic polarity of the sunspots. It is important to note the magnetic cycle of the sun is not 11 years but rather it requires the sum of two sunspot cycles, which is approximately 22 years, to return to its original magnetic polarity. The resulting ISSN series was demodulated using suppressed carrier amplitude modulation methods and correlated to the corresponding SWE series. The correlation coefficient amongst each of the stations in similar climate regions is surprisingly high, which suggests SWE variation is regionally correlated and that each of these sites experiences the same forcing function. The resulting comparison suggests the "footprint" of the sun is detected in the SWE data; and, it appears to be a forcing mechanism in the drought cycle of the Sierra, Rocky, and Cascade mountain ranges in the western United States. (KEYWORDS: snowpack, sunspots, solar magnetic reversal, rotational, cosmic).

Observations of the 2017 Total Solar Eclipse on Solar Panel Voltage Output at the Starr Ridge, Oregon Snotel Site and on a Home Solar Array in Northern California - Jon Lea; Jolyne Lea; Frederick J. Lourence (86th Annual Western Snow Conference, 2018)
The August 21, 2017 total solar eclipse which crossed the United States, offered an opportunity to observe the effect on the voltage output of a SOLAREX MSX-10, a 10-watt solar panel, located at the Starr Ridge, Oregon SNOTEL site. The panel was placed on the ground at a 10 percent angle, and aligned such that at the start of the eclipse the face of the panel was perpendicular to the sun, and would remain in full sun for the duration of the eclipse. Observations were taken at approximately 5 to 10 minute increments with a small handheld volt meter. Data points showed the drop and recovery of the panel output voltages during the eclipse. Panel output declines became most pronounced beginning at 87 percent eclipse coverage of the sun. Recovery of the panel output to voltage levels capable of providing charge to batteries occurred at 2 minutes after the conclusion of the total eclipse. Similar concurrent observations were taken on a home installed 32 panel solar photovoltaic (PV) network located in northern California. The eclipse effect on both voltages and the wattage produced by the panels were observed, and monetary losses calculated. (KEYWORDS: total solar eclipse, SNOTEL, solar panel, voltage output, Oregon)

On the Use of Snow and Climate Information in Statistical Seasonal Streamflow Forecasting - Flavio Lehner; Andrew W. Wood; Dagmar Llewellyn; Douglas B. Blatchford; Angus G. Goodbody; Florian Pappenberger (86th Annual Western Snow Conference, 2018)
Seasonal streamflow predictions provide a critical management tool for water managers in the American Southwest. These forecasts rely primarily on observations of snowpack and precipitation accumulation, which help to quantify the hydrologic memory that enables relatively accurate streamflow forecasts at seasonal lead times. In recent decades, persistent prediction errors for spring and summer runoff volumes have been observed in a number of watersheds in the American Southwest. While mostly driven by interannual to decadal precipitation variability, these errors also relate to the influence of increasing temperature on snow and streamflow in these basins. Here we show that incorporating seasonal temperature forecasts from operational global climate prediction models into streamflow forecasting models adds prediction skill for watersheds in the headwaters of the Colorado and Rio Grande River basins. Current dynamical seasonal temperature forecasts now show sufficient skill to reduce streamflow forecast errors in snowmelt-driven and temperature-sensitive basins. Such predictions can increase the reliability of streamflow forecasting and water management systems in the face of continuing warming as well as decadal-scale temperature variability, and thus help to mitigate the impacts of climate non-stationarity on streamflow predictability.

Remotely Monitoring Snow Water Equivalent Using Basic Photogrammetry - Peter Marshall (86th Annual Western Snow Conference, 2018)
Accurately monitoring the snow water equivalent (SWE) in watersheds and water supply areas is increasingly important in a changing climate as average temperatures are predicted to rise, resulting in diminishing mountain snowpacks. Recent research has shown that it is possible to accurately convert snow depth measurements to snow water equivalent using estimated bulk snow density; multiplying snow depth by the average density of the entire snowpack. Measuring snow depth is relatively simple and cost-effective in comparison to SWE measurements. This study describes a local-scale application of a snow density model with snow depth measurements taken using basic photogrammetry. The study site was situated at 1325 m on a sub-alpine ridge in the Capilano Watershed in British Columbia. Snow depth is estimated from images of a graduated snow depth pole, which is then converted to SWE. For this study, bulk snow density was calculated from historical (c. 1936) average monthly snowpack density at five nearby snow course sites. Calculated SWE values using this snow density model averaged 95% of the periodic manual validations, and proved to be more accurate and reliable than measurements from nearby automated SWE sensors. This technology can be used to fill data gaps and provide additional valuable information to water supply managers at a relatively low cost. (KEYWORDS: snow water equivalent, snow depth, snow density, photogrammetry, hydrology)

Uncertainty in the Future of Seasonal Snowpack Over North America - Rachel R. McCrary; Linda O. Mearns (86th Annual Western Snow Conference, 2018)
Snow cover extent and snow water equivalent (SWE) are rapidly changing over North America. This study investigates the uncertainty in the projected changes in North American snow cover for the middle of the 21st century using the North American Regional Climate Change Assessment Program (NARCCAP) ensemble of dynamically downscaled regional climate models (RCMs). Across the NARCCAP models, temperature is projected to increase everywhere while precipitation is shown to increase everywhere except the western U.S. In this region, the NARCCAP models disagree on the sign of the change in precipitation during the Fall and Winter. Corresponding with these changes in temperature and precipitation, the NARCCAP models robustly show that SWE is projected to decrease over most of North America. The only exception to this is in the high-latitudes, where SWE is projected to increase during the coldest months corresponding with increases in precipitation. There is considerable uncertainty in the magnitude of changes in SWE over north America, especially in the west. Variations in magnitude correspond with baseline SWE amounts from the current climate simulations as well as variations in the drivers of the change, namely temperature and precipitation. Changes in temperature and precipitation also lead to changes in the timing of the snow cover season. The first snow covered date is projected to occur later in the fall while the last snow-covered date is shown to occur earlier in the spring. These shifts result in a reduction in the total number of snow-covered days. There are notable differences across the ensemble in the change in the number of snow-covered days in the western US. Also, changes in the first and last dates with snow cover are uncertain in the central plains of North America, primarily due to interannual variability in this region. (KEYWORDS: North American snow cover, snow water equivalent, climate change, climate models, NARCCAP)

Colorizing the Cloud -- Adding RGB Information to Lidar Point Cloud from Aerial Imagery - Joachim Meyer; S. McKenzie Skiles; Jeffrey S. Deems; Kat Bormann (86th Annual Western Snow Conference, 2018)
Remote sensing products from photogrammetry and lidar scanner have the potential to create a rich dataset when combining information from both sources. This paper presents a first option for the Airborne Snow Observatory (ASO) to couple lidar with the aerial imagery taking with every flight by incorporating the images into the data processing workflow. The image information is matched for each individual point in the point cloud based on their coordinates. Combining and making use of all the recorded information per flight ensures maximum utilization of all available data and can open up research opportunities. (KEYWORDS: Lidar, point cloud, RGB, Structure from Motion, snow depth)

Snowdrift Modeling Using a Linear Particle Distribution Equation - Noriaki Ohara (86th Annual Western Snow Conference, 2018)
A snowdrift is affected by numerous factors including but not limited to wind field, local turbulence, boundary layer thickness, surface roughness, particle Reynolds number, snow particle size distribution, particle shape, and density of snow particles in the air. Therefore, snow redistribution has been ignored in most practical hydrology models, and snowdrifts around well-defined snow fences have been projected mainly by empirical knowledge rather than process-based considerations. This study organized these various effects by particle motion processes rather than flow (wind) regime and particle characteristics in order to develop a predictive model for snow redistribution. The particle motion processes were characterized by three parameters: snow particle dispersion, snow drift (snow surface advection), and snow surface erosion coefficients. Among them, a linear erosion term for a fetch-eddy effect was the new addition to the existing advection dispersion equation. The newly formulated equation was named Eulerian Particle Distribution (EPD) equation, and the linear components of the EPD equation were named the Linear Particle Distribution (LPD) equation. Using analytical solutions under a few well-defined boundary conditions, possible snow particle distribution patterns were successfully mapped. The LPD equation was found to be able to describe most of the one-dimensional particle deposit patterns behind an object, including porous and solid snow fences and a tree. The snow redistribution model based on the LPD theory also reproduced snow stratigraphy observed by ground penetrating radar (GPR). Inversely, this theory may provide us an opportunity to estimate the time-averaged particle motion parameters, such as diffusion, drift, and erosion coefficients, from fieldobserved particle distributions. The model applications and numerical algorithm for snow drift patterns in irregular terrain will be presented. (KEYWORDS: snow drift, Eulerian particle distribution, particle distribution, snow redistribution, snow erosion, snow fence)

A New GrainSize Lookup Table for the Airborne Snow Observatory - Matthew Olson; McKenzie Skiles (86th Annual Western Snow Conference, 2018)
The Airborne Snow Observatory (ASO) is a coupled lidar and imaging spectrometer system developed by NASA-JPL to more accurately quantify important snowpack properties. Along with snow depth and water equivalency, ASO has the ability to drastically improve measurements of snow albedo, a major factor regulating the absorption of solar radiation and consequently snowmelt. Snow grain size is one of the primary parameters controlling the broadband albedo of a snowpack. Imaging spectrometry has provided the ability to examine snow grain size over basin-wide scales. Nolin and Dozier (2000) developed a method using imaging spectrometer data to estimate the optical grain size of a snow surface by relating the reflectance centered around an ice absorption feature at 1030 nm to optical grain size. Due to the operational demands of product delivery (24-hour turnaround time), the Nolin-Dozier approach to grain size retrievals has not yet been implemented in the CASI processing pipeline. Additionally, the CASI imaging spectrometer only covers a portion of the grain size absorption feature, requiring an updated relationship between the ice absorption feature and the grain size. Here, we created a look up table for the CASI spectral range and resolution using two methods, and compare grain size retrievals to current operational methodology. (KEYWORDS: snow hydrology, snow melt, snow energy balance, optical grain size, remote sensing)

Extremes of Opportunity: Examining Recent Trends in Warm Season Extreme Precipitation for New Mexico River Basins - Maryam Pournasiri Poshtiri; Erin Towler; Dagmar Llewellyn; Andreas F Prein (86th Annual Western Snow Conference, 2018)
We explore recent trends in precipitation characteristics within the state of New Mexico and southern Colorado, relevant to the Rio Grande and Pecos basins, where increasing temperatures and decreasing snowpack threaten to reduce the water available for storage and use. To determine how changing precipitation could potentially help to mitigate decreasing water supply, we examine both magnitude and frequency of daily precipitation characteristics for the warm season (June - October) and individual months therein, with a focus on the upper quantiles and extremes within the period 1981 to 2017. We find that the dominant sign of the precipitation trend depends on the season/month examined. Negative trends dominate the warm season, June, and August, while positive trends dominate July and for some September indicators. However, the majority of locations in the study area did not show any significant trends. The increasing trends for the July indicators show the most potential for water supply, with the location of these significantly positive trends mainly concentrated in the southeastern and eastern part of the study region. The frequency of days above the 99th daily precipitation quantile for September also shows increasing trends at some southern and southeastern locations, but this heavy precipitation could be difficult to capture for water supply. However, across most characteristics examined, we find that significant trends are more detectable in the frequency indicators than in the magnitude indicators. As such, for times and locations showing increasing trends, this suggests that water managers looking to exploit changes in precipitation might not need to plan for larger events, but rather for more frequent events. (KEYWORDS: decreasing snowpack, extreme precipitation, warm season, trends, New Mexico)

Filling the Holes in the Space-Time Cube of Snowpack Evolution with Lasers, Cameras, Computers, and Snow Shovels - Mark S. Raleigh; Jeffrey S. Deems (86th Annual Western Snow Conference, 2018)
An information revolution in high-resolution snow observation is producing unprecedented applications in snow research and management of snow-dominated watersheds. Lidar technology has transformed our view and understanding of the spatial nature of snow depth. Between and after lidar flights, sparse in situ measurements are the only direct snowpack data. The central problem is that large gaps in the evolution of snowpack properties through space and time remain even when high-resolution repeat lidar are combined with time-continuous spare point observations. What is needed are additional tools and sources of information to “fill in” the snow data cube. In this project, we assess how time-lapse photogrammetry can help guide modeling decisions and assess model realism. The study focuses on the well-instrumented Senator Beck Basin, a small headwaters basin near Red Mountain Pass, Colorado. Daily maps of binary snow cover and a new dust-on-snow index are derived from a time-lapse camera at a 3 m resolution through the 2013 snowmelt season. A high-resolution (20 meter) snow model is applied using five methods for distributing precipitation spatially, including terrain-based approaches (e.g., lapse rates) and data-driven approaches (e.g., scaled by snow depth patterns from airborne lidar data). The different modeling approaches show a range of structure in spatial snow patterns, with data-driven approaches yielding higher spatial complexity, which are also seen in the camera data. Relative to camera observations, the models tend to estimate higher snow-covered area in the snowmelt season. As suggested by the camera-derived dust indices, this result may be explained by the lack of dust-enhancement in the modeled snowmelt. This study demonstrates the value of time-lapse cameras for identifying strengths and shortcomings of snow models, thereby guiding snow estimation approaches when high resolution snow depth data are unavailable. (KEYWORDS: snow distribution, time-lapse, modeling, dust-on-snow)

Modelling Future Snow Cover and Runoff with Climate-Adjusted Parameters - Al Rango; Jaroslav Martinec; Emile Elias; Ryann Smith (86th Annual Western Snow Conference, 2018)
The effect of a warmer climate on snow cover and runoff was evaluated in the Rio Grande Basin near del Norte (3416 km2, 2436-4229 m a.s.l.) using the reference hydrological year 2001 and an above average snow year, 1987, for comparison. The parameters of the SRM model were adjusted to the new climate for model runs. The depletion curves of the snow coverage for a temperature increase T+4°C show that the seasonal snow cover in 2001 has been melted away before 1 April in the lower half of the basin. In the snow-rich year (1987), the depletion of the snow coverage was also accelerated. Consequently, the runoff in the winter half year (October-March) was tripled in 2001 and doubled in 1987. The runoff in the summer half year was reduced correspondingly. Runoff peaks in 1987 were shifted to earlier dates. These predictions of the future snow cover and runoff in mountain basins are important for hydroelectricity production, flood control, and agriculture. (KEYWORDS: Snowmelt Runoff Model, climate change, Rio Grande, streamflow prediction)

Was the 2016 Gap in San Joaquin River Runoff Caused by Lack of Cloudseeding? - Maurice Roos (86th Annual Western Snow Conference, 2018)
The San Joaquin River basin in the southern Sierra has had cloud seeding programs for over 60 years, mostly funded by Southern California Edison. In 2016, no funds were available for the project, so seeding stopped. Water year runoff was near normal in the Central Sierra, but fell off progressively to the south to only about 50 percent on the Kern. However, there was an additional dip in San Joaquin River runoff of 8 or 9 percent. Could this dip be due to the lack of cloud seeding in WY 2016? (KEYWORDS: cloud seeding, runoff, San Joaquin, drought)

Avalanche in Western Canada - Who is in Charge? - Jerry Toupin (86th Annual Western Snow Conference, 2018)
Every year several centimeters (feet) of snow fall in Canada. In fact, this land remains one of the snowiest countries in the world as more than 1000 cm of snow may fall in Western Canada in certain parts of the Canadian Rockies (British Columbia, Alberta, Yukon and the Northwest Territories) from as early as September to late May or yearlong for some summits (peaks). Avalanche is a common phenomenon for this part of North America and with more and more human activities ranging from infrastructure to backcountry trips. Fatalities, road and rail closures and delays are on the rise and costing millions of dollars to the Canadian economy. In the past few decades, Canada has developed a high level of expertise to better control avalanche and save lives. This article depicts how the Canadian army (National Defense and the Canadian Forces), Parks Canada, the Canadian Avalanche Association, Avalanche Canada (Center) and several other stakeholders have developed and implemented tools and methods to protect everybody. (KEYWORDS: avalanche, monitoring, awareness, protection, winter, snow, Western Canada)

Relationships Among Snow Depth, Snow Water Equivalent, Streamflow and Virus Activity in Two Colorado Subwatersheds, 2004 to 2016 - Dustin Ward; Debra Peters; Luis Rodriguez; Angela Pelzel-McClusky; Justin Derner; Scott McVey; Emile Elias (86th Annual Western Snow Conference, 2018)
Vesicular stomatitis (VS) is the most common vesicular disease affecting livestock (domestic horses, cattle, pigs) throughout the Americas. VS is a vector-borne disease with more than >1500 infected premises in the western US from 2004-2016. The ecology of the host-vector-virus-environment system is the subject of a large, collaborative USDA research effort. Initial findings indicate VS incidents were spatially distributed near the stream network and temporally related to streamflow conditions with all first incidents (n=35) occurring following peak annual streamflow. These spatial and temporal relationships showcase the importance of hydrological contributions to the emergence and distribution of VS and indicate that snow conditions may play an important role in VS emergence. Peters et al. (2017) report that VS infected premises can be evaluated based upon outbreak (2004, 2014) and expansion (2005, 2015) years. Here we evaluate the relationships between monthly snow depth, snow water equivalent, streamflow and the number of VSV infected equine premises in two watersheds (Big Thompson and Saint Vrain) with a high number VS infected premises. The water content of snowpack and snow depth within both watersheds the months prior to a VS outbreak were both lower (2004) and higher (2014) than years with no infected premises. Conversely, outbreak years had higher autumnal and late season monthly streamflow than years with few or no VS infected premises. The complex water management system of reservoirs and irrigation canals along the Front Range of Colorado and VS vectors may buffer the relationship between SWE, snow depth and virus transmission observed in other locations. More detailed analyses of water conveyance associated with VS infection is needed in these watersheds to evaluate the impacts of local water conditions on the vector-host relationship, particularly related to observed elevated autumnal and summer streamflow co-occurring during outbreak years. (KEYWORDS: vesicular stomatitis, snow water equivalent, host-vector-virus-environment system, water management, virus transmission)

Combining Ground Penetrating Radar with Terrestrial LiDAR Scanning to Observe the Spatial Distribution of Liquid Water Content in Seasonal Snowpacks - Ryan Webb; Noah Molotch; Michael Fend (86th Annual Western Snow Conference, 2018)
An important consideration for water resource planning is snowmelt runoff timing. Runoff timing can be determined by the difficult to observe physical process of water movement through a seasonal snowpack. The aim of this study is to present a novel method that combines light detection and ranging (LiDAR) with ground penetrating radar (GPR) to non-destructively observe the spatial distribution of bulk liquid water content in a seasonal snowpack during spring snowmelt. We develop these methods in a manner to be applicable within a short time window, making it possible to spatially observe rapid changes that occur to this property (sub-daily timescale). We applied these methods at three experimental plots across elevational gradients in Colorado, showing the high variability of liquid water content in snow. Volumetric liquid water contents ranged from near zero to 19% within the scale of meters. We also show the rapid changes in bulk liquid water content that occur over sub-daily time scales. Results of this study show the importance of the lateral flow of water in higher elevation snowpacks and how this process may change in a future climate. The presented methods have a reasonable amount of uncertainty in bulk liquid water content (maximum of 1.5%) making this an applicable method for future studies to observe the complex spatiotemporal dynamics of liquid water in snow. (KEYWORDS: snowmelt, flowpaths, liquid water in snow, dye tracers, GPR, LiDAR)

2017 Title, Contents, and Minutes (85th Annual Western Snow Conference, 2017)

Disentangling the Importance of Snowmelt Rate, Timing, and Amount of Runoff Production - Theodore Barnhart; Christina Tague; Noah Molotch (85th Annual Western Snow Conference, 2017)
Mountainous regions are responsible for approximately 32% of global discharge [Meybeck et al., 2001] and within that, snow dominated regions provide water for one-sixth of the global population [Barnett et al., 2005]. Snowpack and the risks associated with a changing snowpack have been valued in the trillions of dollars globally [Sturm et al., 2017], indicating the importance of understanding how changes in snowpack will cascade into changes in runoff production. In the western United States alone, approximately 70% of runoff is derived from snowmelt [Sturm et al., 2017]. Given the social, ecological, and economic value of mountain derived water it is pressing to understand how changes in mountain hydrology will manifest as changes in runoff.

Has the Annual Point Snowfall on the Canadian Prairie Increased or Decreased - H.W. Cutforth; J. Nimegeers; H. Steppuhn (85th Annual Western Snow Conference, 2017)
This study was initiated to determine if the annual Oct 1st through Apr 30th accumulation of daily snowfall at a central location on the Canadian prairie has varied in magnitude over the last 56 years. This requires that the longterm snowfall from 1960-61 through 2015-16 had to be separated from any inherent cyclic variation in the record by averaging these data into 14 four-year periods. The accumulated daily snowfall plus any rainfall was collected and measured as water equivalents in a Nipher-shielded precipitation gauge. The first 16 years of this Nipher precipitation record averaged 15 mm greater than during the following 40 years. During those times when rain fell during the snowfall months, a separate standard rain gauge was activated and its measure also recorded. The differences in recorded water equivalents accumulated in the two gauges constituted the daily snowfall record. The annual snowfall has failed to significantly increase or decrease during the last 40 years, while the daily sum of rain plus snowfall has gained an average of 0.85 mm per year. This implies that the 34 mm increase in combined rain and snow precipitation over the last 40 years resulted from an increase in rainfall during the Oct-Apr period, while the snowfall magnitudes remained constant. (KEYWORDS: climatological station, Nipher-shielded gage (gauge), winter rain, winter precipitation, annual snowfall)

Cross-Validation of Gridded Precipitation Datasets and a Regional Climate Simulation for the Interior Western United States - Bart Geerts; Xiaoqin Jing; Yonggang Wang; Changhai Liu (85th Annual Western Snow Conference, 2017)
This study compares orographic precipitation estimates in the interior western United States (IWUS) from four gauge-driven gridded datasets, a radar-based dataset, and a 10-year, 4 km convection-permitting simulation aided by gauge measurements. Gauge-driven gridded precipitation estimates disagree in areas where gauges are sparse, especially at higher elevations. The radar-based dataset underestimates the winter precipitation in IWUS because of blockage and lack of low-level radar coverage in complex terrain. The model simulation compares well against gauge measurements for winter precipitation. Comparison between model and gauge-driven datasets suggests their differences are related to elevation, gauge density and wind speed. The substantial disagreement between model and the gridded datasets over some mountains may motivate the re-evaluation of some gauge records and the installation of new gauges in regions marked by large discrepancies between modeled and gauge-driven precipitation estimates. (KEYWORDS: gridded precipitation, climate, DAYMET, SNOTEL, climate simulation)

A Spatial and Temporal Analysis of Radiative Forcing Across a Regional Scale it the Western United States - Janelle Gherasim; S. McKenzie Skiles (85th Annual Western Snow Conference, 2017)
Snow is a unique land cover type, and varies significantly in reflectance from other types of surfaces on Earth. Uncontaminated, or ‘clean’, snow has a very high spectral albedo. This is reduced by the deposition of light absorbing particulates, like dust from arid and disturbed landscapes, which darken the snow surface and enhances the rate of snow melt. The instantaneous enhanced surface absorption of solar radiation by dust on snow is known as radiative forcing. Radiative forcing by dust on snow can be monitored at the regional scale with the MODIS Dust Radiative Forcing in Snow (MODDRFS) product. Here present results from the Western US, namely on the Rocky Mountains and Sierra Nevada Mountains. We show the effect of dust on snow has high interannual variability, and dust radiative forcing is consistently higher in the Rockies relative to the Sierra Nevada. Gaining a better understanding of the spatial and temporal patterns of dust on snow in the Western US will help in formulating effective management of water resources in a region that is dependent on snow melt to meet water demands. (KEYWORDS: dust-on-snow, albedo, snowmelt, remote sensing)

Toward a Greater Understanding of Snowmelt Hydrology in Utah - Randall P. Julander; Jordan Clayton (85th Annual Western Snow Conference, 2017)
Visual inspection of annual hydrographs from most rivers in the western U.S. supports the notion that snowmelt provides the majority of streamflow in these areas. In Utah, the snowmelt period of April-July provides an average of 71% of annual streamflow with 29% coming in the remaining 8 months, begging the question: what proportion of streamflow comes from snowmelt? Previous estimates have been rough and have ranged from 60% to 80% or so; uncertainty stems from complexities such as rain on snow events, the geographic and temporal distribution of precipitation events, and the partitioning of rainfall/snowmelt into streamflow. However, the quantification of streamflow derived from summer precipitation is fairly simple on streams that have no upstream regulation. It can be reasonably assumed that any rise in flow with a corresponding storm event is due to precipitation, and the event flow can be separated from the base flow component of the hydrograph. We find that the contribution of summer-month precipitation to annual streamflow in Utah is extraordinarily low: typically 1% to 2%. Using soil moisture and well depth data we also demonstrate that vast areas of Utah watersheds are incapable of producing event flow from summer precipitation due to consumptive losses from evapotranspiration and other factors. We use these data to infer that 98% to 99% of streamflow in Utah watersheds originates from melting snow and associated processes. This analysis is likely representative of areas within other western states that have cool continental climates, abundant snowfall, long-duration snowpacks (meaning that substantial portions of the snowpack do not typically melt during the winter), and sedimentary bedrock, such as eastern Nevada, western Colorado, portions of Idaho and Montana, and elsewhere. (KEYWORDS: snowmelt, streamflow, Utah, soil moisture, SNOTEL)

Characteristics of Moisture Pathways Associated with Large Precipitation Events in the Upper Colorado River Basin - Johnathan P. Kirk; Thomas W. Schmidlin (85th Annual Western Snow Conference, 2017)
Declining streamflow in mountain snowpack-sourced basins across the western United States in recent years has necessitated further investigation into the spatiotemporal trends of snowpack accumulation each season. Previous studies have shown that substantial proportions of annual precipitation occur during relatively few large precipitation events (LPEs) and consequently, such events tend to be significant predictors of streamflow for many basins, including the Upper Colorado River Basin (UCRB) (McCabe, 1996; Werner & Yeager, 2013; Bolinger et al., 2014). While primary pathways of atmospheric moisture from the Pacific Ocean into the inland interior have been identified in previous studies (e.g. Rutz et al., 2015), comparatively little analysis has been done to examine the moisture pathways associated with LPEs at the watershed-level amid the interior west.

Solar Forcing of Drought Detected in Snowfall Records of the Central Sierra Nevada, Western United States - John A. Kleppe; Daniel S. Brothers (85th Annual Western Snow Conference, 2017)
This paper presents wavelet analyses of snow water equivalent (SWE) data from three sites near to the Lake Tahoe Basin (Lake Lucille, Ward Creek, and Mt. Rose) with continuous measurement records since 1910; and a fourth site which is ~180 km to the south at Mammoth Pass with records back to 1928. The correlation amongst the four stations is surprisingly high (0.88), which suggests SWE variation is regionally correlated and that each of these sites experiences the same forcing function. When the International Sunspot Number (ISSN) data are modified to account for magnetic polarity of the sunspots to reflect the reversal of the magnetic field of the sun every ~11 years, the modified ISSN series can be demodulated using suppressed carrier amplitude modulation methods and correlated to the 100 year SWE series. Based on the results presented in this paper, we propose the major driving forces of winter precipitation, in the form of snow, in the northern and central Sierra are the reversal of the sun's magnetic field and a statistically independent "carrier" signal being generated by the Earth's atmospheric circulation parameters including orbital (inclination, eccentricity, precession, obliquity, and rotational), depth of the atmosphere, and heating by the sun. (KEYWORDS: snowpack, sunspots, solar magnetic reversal, rotational, cosmic)

Are Model Complexity and Transferability Antithetical? Insights from Validation of a Variable-Complexity Snow Model on New Conditions - A.C. Lute; Charles Luce (85th Annual Western Snow Conference, 2017)
The related challenges of predictions in ungauged basins and predictions in ungauged climates point to the need to develop environmental models that are transferable across both space and time. Hydrologic modeling has historically focused on modelling one or only a few basins using highly parameterized conceptual or physically based models. However, model parameters and structures have been shown to change significantly when calibrated to new basins or time periods, suggesting that model complexity and model transferability may be antithetical.

Sensitivity of Snow and Hydrological Dynamics to Climate in a Catchment Characterized By Wind-Driven Redistribution of Snow - Adrienne Marshall; Timothy Link; Linda Tedrow; Gerald Flerchinger (85th Annual Western Snow Conference, 2017)
Under anthropogenic climate change, warming temperatures and altered precipitation regimes are expected to alter snow hydrology in the western United States. In catchments with wind-driven snow redistribution, the transition from snow to rain may be either moderated or exacerbated in parts of the watershed that currently receive snow subsidies. The hydrological sensitivity may depend on the seasonal variability of changing precipitation and temperature, and magnitude or the effect may vary inter-annually. To test these dynamics, we applied the Simultaneous Heat and Water (SHAW) model to a 30-year hourly meteorological record from the Upper Sheep Creek catchment in the Reynolds Creek Experimental Watershed. The model was applied to three hydrologic response units: a drift-subsidized site with quaking aspen stands, and two landscape units with mountain big and low sage, respectively, with low sage particularly susceptible to scour.

National Snowschool Program and Weather Station Pilot Project - Kerry McClay; Charlie Luce; Tom Black; Abigail Lute (85th Annual Western Snow Conference, 2017)
Winter Wildlands Alliance’s National SnowSchool Program introduces K-12 students to the joy of exploring our nation's winter wildlands. A growing national education program utilizing an innovative snowhydrology curriculum, SnowSchool annually engages over 30,000 participants across 60 sites. However, one potential problem with a field trip program like SnowSchool is little or no connection back to the classroom. The result can be a weak “one-and-done” experiential program that fails to spark further learning. To counteract this trend, Western Wildlands Alliance and the US Forest Service Rocky Mountain Research Station installed a new snowpack monitoring weather station at the Bogus Basin SnowSchool site near Boise, Idaho. The station’s online snowpack data and WWA’s unique web-based educational activities provided teachers with a classroom resource that transformed learning at SnowSchool from a 1-day outing into a 3-month science exploration. To understand the impact of this pilot project we collected pre/post student science quizzes. Results demonstrated significant gains in student learning. (KEYWORDS: Bogus Basin, Winter Wildlands Alliance, SnowSchool, environmental education)

Multi-Channel Ice Penetrating Radar Traverse for Estimates of Firn Density in the Percolation Zone, Western Greenland Ice Sheet - Tate Meehan; John Bradford; H.P. Marshall; Erich Osterberg; Bob Hawley; Bob Hawley; Thomas Overly; Gabe Lewis; Karina Graeter; Forrest McCarthy (85th Annual Western Snow Conference, 2017)
To better predict the response of the Greenland Ice Sheet (GrIS) to future warming, leading edge Regional Climate Models (RCM) must be calibrated with in situ measurements of recent snow accumulation and ablation. Mass balance estimates averaged across the entire Greenland Ice Sheet (GrIS) vary between models by more than 30 percent, and regional comparisons of mass balance reconstructions in Greenland vary by 100 percent or more. Greenland Traverse for Accumulation and Climate Studies (GreenTrACS) is a multi-year and multi-disciplinary science traverse in the western percolation zone of GrIS. During spring 2016, we used multi-channel 500MHz radar in a multi-offset configuration to survey more than 800 km from Raven Camp towards Summit Station. Multi-offset radar measurements can provide high precision electromagnetic (EM) velocity estimates of the firn to within ±0.003 m/ns. EM velocity, in turn, can be used to estimate firn density. Using the CRIM equation we estimate the average firn density to a depth of ~25 meters. Preliminary radar-derived average density estimates agree with cumulative average density estimates from a firn core measurement (~40 kg.m-3), despite the spatial heterogeneity of the firn. (KEYWORDS: multi-offset, GPR, Greenland, Ice Sheet, GreenTrACS, firn, density)

The Influence of Forest Canopy Structure on Snow Interception: Design and Implementation of a New Model - C. David Moeser (85th Annual Western Snow Conference, 2017)
Seasonal snow in forested areas can account for 17% of total winter terrestrial water storage. Snow interception ranges from 0 to 60% of the total annual snowfall in forested areas and creates large snow storage differences between open and forested environments. Many snowmelt models have included interactions of canopy with snow-cover, but these models included overly simplistic representations of interception processes and could not reproduce the natural heterogeneity in under-canopy snow cover. This study developed and implemented an interception model valid for discrete time steps, various scales, and heterogeneous canopy structure. New forest structure metrics derived from aerial LiDAR data were developed and introduced into the new model to better describe forest structure. Inclusion of these novel forest structure metrics allowed the new interception model to mimic the heterogeneous canopy structure layout, while prior modeling efforts demonstrated homogenous interception estimations even under highly heterogeneous canopy conditions. The large variance of estimated interception between points from the new model were validated from ~84,000 manual measurements and translated to approximately double the variance of under-canopy snow depth, snow-water equivalent, and canopy sublimation compared to prior models.

Effect of the Tree Canopies in Microwave Radiometric Remote Sensing of Snowpack - Seyedmohammad Mousavi; Roger De Roo; Kamal Sarabandi; Anthony W. England (85th Annual Western Snow Conference, 2017)
Effective management of the freshwater reservoir requires almost daily monitoring the spatial and temporal distribution of the snow water equivalent (SWE) and snowpack wetness. Both microwave radar and radiometers systems have long been proposed and implemented as powerful remote sensing tools in retrieving the physical parameters of interest due to their all-weather operation capability. In case of microwave radiometry, microwave remote sensing of dry snowpack is based on frequency-dependent differential scattering by the ice grains in the snowpack, referred to as scatter darkening. Scatter darkening has been developed as a SWE remote sensing technology over the last three decades. However, the presence of tree canopies in a given scene can affect the SWE estimation of snowpack. Hence, the knowledge of the brightness temperature of tree canopies is important in order to better predict and recover the SWE of the snowpack. We have used the microwave radiometers at three different frequencies; namely, 1.4 GHz, 19 GHz, and 37 GHz, mounted on our boom truck to look at the snowpack. The measurements have been done in Grand Mesa National Forest in Colorado as the NASA SnowEx campaign in Feb 2017. In this paper, the effect of the snow on tree canopies on their brightness temperature is discussed. Moreover, the elevation angular dependence of the brightness temperature of the tree canopies is investigated.

Trends in Snow-Line Elevation Along the Wasatch Front, Utah from MODIS Fractional Snow-Covered Area - Hannah Peterson; S. McKenzie Skiles (85th Annual Western Snow Conference, 2017)
The main source of water for the over 2 million people that reside along the Wasatch Front is annual melt of the mountain snowpack. There has been vast infrastructure developed to capture and transport melt water as it flows out of the mountains in the spring and summer. This natural reservoir is at risk, as population continues to increase and the climate warms and becomes more variable, this water source will become less reliable, straining the current water delivery system. Therefore, it is important to quantitatively understand how the snowpack has been changing over time, in order to predict and forecast how it will change, spatially and temporally, in the future. This project assesses changes in the Wasatch Front’s snowline elevation and snow-covered area, on April 1st, over the last 18 years from the MODIS Snow-covered Area and Grain Size (MODSCAG) fractional snow-covered area product (fSCA). Although the data set does not span a multi-decade time series, which is typically preferred for climate analysis, the analysis shows a positive trend in snow-line elevation (toward high elevations) and negative trend in snow-covered area (declining snow-covered area).

Recent Changes in the Sierra Snowpack of California - Maurice Roos; Angelique Fabbiani-Leon (85th Annual Western Snow Conference, 2017)
The mountain snowpack is an important element of California’s water supply. Winter precipitation in the high mountains is held over in the form of snow as natural water storage for the spring and summer dry season when irrigation demands are high. Historically, snowmelt furnished about 30 percent of the water supply for irrigated and urban users. In a warmer climate, less snow is expected and accumulation would be more limited to the higher portion of mountain watersheds. In a paper 5 years ago at the Western Snow Conference (Roos and Sahota, 2012), contrasting trends were described. For a northern Sierra group of snow courses, a decline in April 1 measured water content was noted; however, for another group of southern Sierra courses, a small increasing trend in water content was noted. In both north and south, there was a decreasing trend in the volume of April through July runoff (mostly snowmelt) compared to total water year nature runoff. Now, after the drought, a recheck and update of these charts show that the southern Sierra snowpack also shows a decreasing trend, although not as much as in the north. One possible reason for the original trend is that the extensive cloud seeding programs in the southern Sierra temporarily offset an overall decreasing trend caused by warmer temperatures in the past two or three decades. As warming in the 21st century has increased, the changes have more than offset the small incremental increase by the weather modification programs.

Snow Depth Variations from Storm Trajectory and Mountain Topography in the Tuolumne River Basin - Jeremy Saldivar; S. McKenzie Skiles (85th Annual Western Snow Conference, 2017)
The Western United States relies heavily on water from snowmelt to sustain water demand through summer months. Understanding the snow water equivalent (SWE), the product of depth and density, of a snowpack is crucial for budgeting water appropriately. The varied topography of mountainous regions makes measuring snowpack depth difficult. It has recently been demonstrated by the Airborne Snow Observatory (ASO; NASA-JPL) that differential mapping of snow depth with an airborne scanning lidar is an efficient and accurate way to monitor snow depth at the watershed scale. Snow depth time series from ASO in the Tuolumne Basin, CA show that snow does not accumulate evenly. Factors such as the trajectory of a storm, snow accumulation rates, and aspect/elevation can affect snow deposition patterns. Here, we use ASO measured snow depth on April 2014, April 2015, and March 2017 and two acquisitions before and after a precipitation event (April 8, 2015) to assess variation in snow depth across the basin. Results show that the most snow is present on northerly aspects and at elevations from 10,000 - 12,000 feet. Potential for future research includes looking at a different storm event and more basins as LiDAR generated snow depths become available.

Constraining Physical Controls on Snow Hydrology Along the Wasatch Front, UT, - S. McKenzie Skiles; Steven Clark; Jeremy Andreini; Matt Olson; Hannah Peterson (85th Annual Western Snow Conference, 2017)
Like much of the Western US, the million plus people that live in the Salt Lake City metropolitan area, located along the Wasatch Front, UT, depend on snowmelt to meet water demands. A persistent reduction in the mountain snowpack would introduce stress into the current water delivery system. Impacts to snow water storage during accumulation are mainly due to increasing temperatures; more precipitation falls as rain instead of snow. Impacts to storage during ablation are mainly due to increasing net solar radiation, controlled by albedo, which drives snowmelt in almost all snow covered environments. Combined, a shallower, warmer snowpack has a lower albedo, which shifts snowmelt timing and magnitude, and further reduces water yields via increased evapotranspiration. Deposition of light absorbing aerosols, which accumulate in the snowpack through the winter and concentrate at the surface as snow melts, further compounds albedo decay. The Wasatch snowpack is at risk for deposition of both black carbon, particularly in the winter during persistent cold air pools (inversions), and dust, particularly in the spring when regional wind speeds and dust emission peak. Current snowmelt forecasting methods are not capable of accounting for the physical processes that control snow accumulation and melt, which limits their ability to adapt to changing snowmelt regimes. This is mainly due to the lack of observations to document processes, establish relationships based on first principles, and validate physically based snow energy balance models. During Water Year 2017 fieldwork efforts in the four main watersheds that dominate water deliveries to Salt Lake City, UT were aimed at addressing this paucity of data to better constrain physical controls on snow hydrology along the Wasatch Front. Here, initial results from fieldwork efforts completed between Jan-Jun 2017 are presented, as well as a remote sensing analysis to assess historical variation in snow line elevation.

The Influence of Cloudiness, Temperature, and Precipitation Variabilities on Snowmelt Variations in the Western U.S - Edwin Sumargo; Daniel R. Cayan (85th Annual Western Snow Conference, 2017)
We investigate the influence of cloudiness variability on spring snowmelt and streamflow variations in the mountains of western U.S., and how it compares to that of precipitation (P), daily maximum and minimum temperature (Tmax and Tmin). We derive daily cloud albedo (αcloud) from GOES visible albedo product to represent cloudiness. Daily snowmelt (ΔSWE) is obtained from 235 SNOTEL and CDEC snow water equivalent records. Daily streamflow fluctuations (ΔQ) are derived from 79 USGS/HCDN stream discharge records. Multivariate regression models are developed for five different sets: where αcloud, P, Tmax and Tmin surface are predictors, and successively, where each one of the predictors is removed. αcloud, Tmax, Tmin and P altogether account for 3%-62% of ΔSWE variance over Feb-Jul, averaging ~23%. The results further show the dominance of αcloud influence, with increasing αcloud role and decreasing Tmax, Tmin and P roles in warmer months and in drier years. Greater αcloud contribution in dry years suggests the diminished importance of other hydrological factors in dry years, such as heavy precipitation events and fluctuations associated with higher snowpack. ΔQ responses to αcloud, Tmax, Tmin and P exhibit similar patterns, but with lower explained variances.

Snow, Cold, and Winter: What Does that Mean for Canada in the 20th and 21st Centuries - Jerry Toupin (85th Annual Western Snow Conference, 2017)
Canada and Canadians are known throughout the world namely because of snow, cold and winter. At the beginning of the 20th century the vast majority of the population was still rural (1901) and continues to battle against winter, snow and cold. People remained isolated. Following the Industrial Revolution, expansion of cities was inevitable in developed countries and by 1921 more than 50 percent of the Canadian population was already migrating to cities. Urbanization was in place yet winter remained a difficult season for most people. The 20th and the 21st centuries brought major changes in how Canadians faced the cold season. This article depicts how technology, to some extent, changed the way people live through winter in Canada. The 20th century saw the introduction of cars, and snowmobiles, the St. Lawrence Seaway, commercial aviation and improved roads, as well as better government policies (services). The 21st century offers more accurate long-term and short-term weather winter forecasting. The applications of more and more “apps” for smartphones and other electronic devices are now major tools to possibly improve the quality of life during the wintertime in Canada. Nanotechnology or the engineering of functional systems at the molecular scale (including graphene: the material of the future) could lead to nanomaterials and major change for the 21st century and beyond.

Using Ground Penetrating Radar to Assess the Variability of Snow Water Equivalent And Melt in a Mixed Canopy Forest - Ryan Webb (85th Annual Western Snow Conference, 2017)
Snow is an important environmental variable in headwater systems that controls hydrological processes such as streamflow, groundwater recharge, and evapotranspiration. These processes will be affected by both the amount of snow available for melt and the rate at which it melts. In complex mountainous terrain, a number of factors can affect snow water equivalent (SWE) and melt including slope, aspect, canopy type, and canopy density.

2016 Title, Contents, and Minutes (84th Annual Western Snow Conference, 2016)

Recognizing the Human Faces in the Context of Reduced Snowpack - Acker, Thomas L.; Smith, Dean Howard (84th Annual Western Snow Conference, 2016)
Our research focuses on agriculture in Arizona, California Nevada, Oregon and Washington using inperson interviews with community members to determine the possible indirect and induced economic losses from a reduction in irrigation-based income and employment. Whereas agricultural-based output accounts for less than 2% of economic output value throughout the western states, many urban and rural communities heavily rely on this  output for their very existence. Thus, reductions in snow-based and aquifer-based irrigation will have severe impacts on said communities. Understanding the snow/water/energy/food nexus throughout the west is vital. The western states rely on snow pack to produce much of the electricity utilized in pumping water - both surface and ground - for agricultural purposes. Using modern economic tools, the impacts of the agriculture economic base can then be evaluated in terms of generating secondary economic activity as the wages and profits from the direct jobs are spent within the local economy. Initially, the interviews focused on people directly involved with the management of water at various levels. More recently the focus has been on the indirect and induced impacts of the necessary changes in water management practices. While the extended drought is having positive impacts on some business  sectors, others are having difficult times. (KEYWORDS: agriculture, economic modeling, water management, drought, water use transfers)

Using Snow Water Equivalent Reconstruction for Operational Use: Two Case Studies - Edward H. Bair; Karl Rittger; Carrie Vuyovich; Bruce McGurk; Jeff Dozier (84th Annual Western Snow Conference, 2016)
In the snow water equivalent (SWE) reconstruction method, the snowpack is built up in reverse from downscaled energy balance forcings and satellite-based estimates of fractional snow covered area (fSCA). For melt modeling, we have developed a full energy balance model called ParBal that relies on satellite-based measurements and does not need ground-based inputs. Using ParBal to compute the melt, SWE reconstruction has been shown to be accurate when compared with a variety of validation sources, most recently by comparison with Airborne Snow Observatory (ASO, Painter et al., 2016) measurements in the Upper Tuolumne Basin, CA USA (Bair et al., 2015; Bair et al., in review). The major disadvantage is that reconstructed SWE estimates are only available retrospectively. While this limitation cannot be overcome, we present two case studies where reconstructed SWE can be used in an operational context. 1) We run ParBal as a melt only model, examining seasonal and daily melt without reconstructing the snowpack. Although we cannot reconstruct snow on the ground in this manner, we can potentially make near real-time estimates of snowmelt if these daily melt estimates are then fed through a routing model and compared with streamflow measurements. ParBal can be driven by: a) Global Data Assimilation System (GDAS, Kleist et al., 2009) meteorological forcings, now available at 1/9° spatial resolution and at 3 hr intervals with almost no latency; and b) Moderate Resolution Imaging Spectrometer Snow Covered Area and Grain Size (MODSCAG, Painter et al., 2009) snow cover data, available daily with one or two day latency. 2) We use machine learning techniques to build statistical relationships between remotely-sensed products, such as the ones mentioned in 1), and reconstructed SWE in Afghanistan. This approach allows real-time SWE prediction in remote areas that previously had little or no baseline for comparison

Rapid Snowmelt Leads to Greater Streamflow Across the Western United States: Streamflow Sensitivity to Changes in Snowpack Across Trans-Basin Diversions - Theodore B. Barnhart; B. Livneh; J.F. Knowles; A. Harpold; D. Schneider; D. Gochis; N.P. Molotch (84th Annual Western Snow Conference, 2016)
Snowmelt is the primary source of surface water in the western United States and for approximately one sixth of the global population (Barnett et al., 2005). Climate change is altering the magnitude of the mountain snowpack and the timing and rate of snowmelt (Mote et al., 2005; Clow, 2010; Harpold et al., 2012). These changes could have profound implications for the water resources of the western United States (Milly et al., 2008). We ask how these changes to the mountain snowpack impact how snowmelt is partitioned between evapotranspiration (ET) and streamflow across the western United States. We hypothesize that rapid snowmelt is able to quickly satisfy atmospheric demand for water and bring the soil column to field capacity, inducing infiltration past the root zone and generating streamflow. Regional- or watershed-scale differences in the sensitivity of streamflow to changes in snowmelt could strain existing water transfer agreements, especially across trans-basin diversions.

Capturing Spatial Variability in the Influence of Topography and Vegetation on Snow Depth in the Tuolumne River Basin, CA - Ian W. Bolliger; Noah P. Molotch; Alexei Pozdnukhov; Margaret S. Torn (84th Annual Western Snow Conference, 2016)
Understanding spatial nonstationarity in the influence of topography and vegetation on patterns of snow water equivalent (SWE) can improve distributed SWE models and guide investigations of physical processes that generate this variability. In this study, we seek to understand the nature of this nonstationarity and improve upon a basin-scale statistical snow depth model by allowing for spatial patterns within observed relationships. To accomplish these objectives, we apply geographically weighted regression (GWR) (Fotheringham, Brunsdon, and Charlton, 2002) to gridded, 3m-resolution, LiDAR-derived elevation, canopy height, land cover classification, and snow depth products from the Tuolomne River Basin in California. The data are obtained from the Airborne Snow Observatory (ASO) (“ASO | NASA Airborne Snow Observatory” 2015), with snow depth observations from early April flights in 2013, 2014, and 2015 and topographic/vegetation features from 2014. Preliminary results suggest that our approach leads to a ~10% decrease in error relative to a comparable global model and that the spatial patterns in local relationships between snow depth observations and topographic and vegetation features are persistent across seasons. Furthermore, they suggest that the scale of nonstationarity in these relationships may fall between 50-100m, but that there is also a wide range in the magnitude of spatial variation across features.

Predicting Weather Using Sea Surface Temperature Anomalies - Timothy J Brewer (84th Annual Western Snow Conference, 2016)
During the winters of 2013-2015, southern Idaho, USA, experienced significantly below normal precipitation during very stable weather conditions resulting in very low water supplies during the following summers.  Looking for an explanation, pictorial data from several years were compared to identify patterns linking sea surface temperature anomalies (SST) and patterns in cyclonic lows in weather systems.  The data indicate that the relatively warmer and cooler areas of SST cause cyclonic and anti-cyclonic atmospheric behavior, respectively.  The cyclonic weather systems create blocks preventing cyclonic weather systems to the west from moving eastward faster than the blocking systems are moving.  A ridge of high pressure will form between the two systems providing feedback that strengthens the pattern.  Three significant locations were identified as the major sources of energy affecting winter weather patterns over the northern hemisphere land masses:  the tropical waters off Southeast Asia, the eastern tropical Pacific Ocean, and the eastern tropical Atlantic Ocean.  Over land masses, the easternmost and southernmost weather systems almost always govern the interactions.  Examples are provided to illustrate the interactions of the dominant forces causing persistent weather patterns.  (KEYWORDS:  sea surface temperature anomaly, stability of weather patterns, blocking systems, atmospheric energy, jet stream, water supply)

The Water Year 2015 Snow Drought in Washigton State: What Does It Tell Us About Future Drought Risk? - Joe Casola (84th Annual Western Snow Conference, 2016)
In many locations across the Washington State, the 2015 water year exhibited some of the lowest snow accumulations in the observational record. The low snowpack conditions, both in the Cascades and more broadly across the Northwest, set the stage for summer drought conditions that had negative impacts on water supplies, especially for agriculture, ecosystem health, and hydroelectricity production.   This paper presents data from SNOTEL stations throughout the Washington Cascades, illustrating the pervasiveness of low-snowpack conditions for the 2015 water year. Based on the SNOTEL records and observations of temperature and precipitation at meteorological stations in the region, it is clear that temperature was the driver of low-snowpack conditions, with a large proportion of the winter precipitation being delivered via atmospheric river events with high freezing levels.    Comparison of the seasonal temperature anomalies to future projections shows that the 2015 water year is a good analog for average temperatures around the mid-21st century. At the same time, aspects of the atmospheric circulation that helped contribute to the anomalous warmth and the paucity of cold storms resemble recognizable patterns of natural atmospheric circulation variability. The particular pattern evident in the 2015 water year (the Pacific North American pattern) is likely to continue to play an important role in the interannual variability of snowpack.    Information about future climate often focuses on changes that are tied to forcing from greenhouse gas emissions, and omit information about interannual circulation variability. Given that 2015 illustrates the important role that this variability can play in contributing to snow conditions, the paper recommends a more integrated approach when communicating to water managers about future 21st century snowpack conditions.  (KEYWORDS: drought, climate change, Washington State, atmospheric river, 2015)

Estimating Snowmelt Contribution from the Gangotri Glacier Catchment into the Bhagirathi River, India - Rodney M. Chai; Leigh A. Stearns; C. J. van der Veen (84th Annual Western Snow Conference, 2016)
The Bhagirathi River emerges from the terminus of the Gangotri Glacier at 4000 m.a.s.l., and is a major tributary of the Ganges River. The Ganges is the world’s third-largest river by discharge and provides water to over 350 million people in India and Bangladesh. The discharge of the Bhagirathi, which is driven by seasonal snow cover and melt, therefore has significant impacts on the downstream water supply to a population larger than the United States. Discharge data are scarce along the Ganges River, particularly in the headwaters. The Snowmelt Runoff Model (SRM) is a simple temperature index model that uses relatively few parameters to model runoff. This makes it ideal in remote areas like the Himalayas where it is difficult to get on-the-ground data that an energy balance model would require.  A digital elevation model was used to divide the basin into elevation bands, and MODIS tiles were used to determine snow-covered area for 2010 and 2011. The results show that of the three SRM parameters, SCA showed the strongest correlation with both observed and modeled discharge in 2010, with R2 values of 0.64 and 0.56 respectively. In 2011, however, all three SRM parameters performed poorly with both observed and modeled discharge.  (KEYWORDS:  SRM, Gangotri glacier, snow covered areas, Ganges River)

An Evaluation of Terrain-Based Downscaling of MODIS-Based Fractional Snow- Covered Area Datasets Over the Tuolumne River, CA, Based on LiDAR-Derived Snow Data (Extended Abstract) - Nicoleta C. Cristea; Jessica D. Lundquist (84th Annual Western Snow Conference, 2016)
Remotely-sensed snow covered area (SCA) datasets with both high spatial and temporal resolutions are needed for research, planning, and management of hydrologic and ecologic resources. MODIS-based products provide good temporal resolution (daily), but on coarse scale grids (~463 m). This coarse spatial scale can be refined through applying downscaling procedures, which consist of using the fractional snow cover area product (fSCA, the percentage snow cover within a MODIS pixel area) to assign binary (presence/absence) SCA data on higher resolution grids. Current methods rely on representing ablation effects on snow spatial variability by using topographic radiation-derived slope factors and relative elevation as primary indicators of snow presence/absence (Walters et al., 2015), or a degree-day approach (Li et al., 2015). In both studies satellite-derived data were utilized for model input and validation. Uncertainty associated with the input and validation data in assessing downscaling performance could be better understood if reliable, platform-independent fine scale SCA data were available. Here, we propose such a framework for testing and developing a new downscaling procedure based on LiDAR-derived snow depth data collected over the Tuolumne River watershed, CA. Our new downscaling procedure is based on terrain-derived indices that are representative of both ablation and accumulation, drivers of snow spatial variability in complex terrain. The use of the LiDAR-derived dataset has several advantages over using the satellite data. First, the validation data is more accurate, as LiDAR-derived data are high resolution (1-3m). Second, accurate fSCA datasets can be derived from the high resolution LiDAR-derived snow data at the MODIS scale to be used as input data. Third, the downscaling performance can also be tested over vegetated areas, where LiDAR-derived data is presumably more accurate than the satellite data.

Snow Disappearance Timing in Warm Winter Climates is Dominated by Forest Effects On Snow Accumulation - Susan E. Dickerson-Lange; Rolf F. Gersonde; Jason A. Hubbart; Timothy E. Link; Anne W. Nolin; Gwyneth H. Perry; Travis R. Roth; Nicholas E. Wayand; Jessica D. Lundquist (84th Annual Western Snow Conference, 2016)
Forests modify snow processes and affect snow water storage as well as snow disappearance timing. However, forest influences on snow accumulation and ablation vary with climate and topography, and are therefore subject to substantial temporal and spatial variability. Prediction of where and how forest cover will accelerate versus delay snow disappearance timing has valuable forest management applications, particularly in regions of extensive forest cover and intensive timber harvest such as the Pacific Northwest (PNW), USA. However, an improved understanding of how different forest-snow processes combine to contribute to snow disappearance timing is needed before applying empirical models (Varhola et al., 2010; Lundquist et al., 2013), or physically-based hydrologic models (Ellis et al., 2013; Du et al., 2016) to management practices. We therefore utilize multiple years of snow observations from across the PNW to assess forest-snow interactions in the relatively warm winter conditions characteristic of maritime and transitional maritime-continental climates (Figure 1). We (1) quantify the difference in snow magnitude and disappearance timing between forests and open areas and (2) assess how forest modifications of snow accumulation and ablation combine to determine whether snow disappears later in the forest or in the open.

Snowmelt Runoff in the Sierra Nevada and South Cascades during California’s 4th Year of Drought - Gary J. Freeman (84th Annual Western Snow Conference, 2016)
For California statewide the 2015 water year, which followed three prior dry years, produced several new hydrometeorological records including but not limited to low runoff, dryness and warmer than normal minimum  temperatures.  The 2015 spring freshet from snowmelt reflected the general lack of snowpack, setting several new records for low spring flows leaving most of California reservoirs less than full.  Headwaters which drained the Sierra’s exposed granites suffered some of the lowest late summer and fall flows on record.  Northern California’s rivers such as the Pit, McCloud, Upper Sacramento, Klamath, and North Fork Feather River above Lake Almanor which have portions of their watersheds overlaying the High Cascades volcanic aquifer systems while at some of their lowest flow rates on record still managed to maintain higher flow rates than for the Sierra exposed granites. While water year precipitation was less than normal, the majority of precipitation occurred in December 2014 with storms delivering the majority of water year precipitation during a couple weeks mostly in the form of rainfall.  A large number of the storms that entered California during the 2015 water year occurred as atmospheric rivers with rainfall occurring on the higher headwater areas of the Sierra.  The relatively high elevation southern Sierra was much drier than northern California, so despite its higher elevation conducive to snowfall, precipitation was among the driest on record, leaving only a shallow snowpack on summits above 2,700-3,300 meters elevation.  Precipitation and unimpaired flows for the past four years were analyzed and compared with prior drought periods to gather perspective as to the severity of the drought.  Years such as the 2015 water year can provide foresight into what California’s late summer and fall mountain flows may look like with continued warming temperatures.  Several studies have indicated a significant reduction in snowpack for California’s mountain areas by the end of the 21st century.  (KEYWORDS: drought, climate change, snowpack, volcanic aquifer systems).

Comparing a SNOTEL Extended-Range Air Temperature Sensor and Equations to a NIST-Certified Sensor in an Environmental Chamber - Deborah S. Harms; Cathy A. Seybold; John Weeks; Jolyne Lea (84th Annual Western Snow Conference, 2016)
In the National Snow Survey program, air temperature is one of the parameters that is measured at a SNOTEL site.  The original YSI air temperature sensor did not adequately measure the temperature range that was found throughout the network.  Therefore, the extended-range YSI air temperature sensors were installed over time at all the telemetered stations.  The new sensor required a different algorithm to convert the voltages (measured by the sensor) to degrees C.  This conversion occurred in the server at the National Water and Climate Center.  At the time, the algorithm used was developed at the center and was not the manufactured-recommended algorithm.  Since the conversion, there has been some concerns that the algorithm or the sensor has overestimated the air temperature.  To test for this, we installed 6 extended-range YSI temperature sensors and one certified Fluke sensor in an environmental chamber.  The chamber was set to start at -50° C and then step 5° increments to +50° C.  We then reversed the stepping from hot to cold in the same increments.  The sensors were connected to a Campbell CR10X data logger and the millivolts from the sensor were recorded every 15 minutes.  The measured millivolts were converted into degrees Celsius by the existing equation and the manufacturer-recommended algorithm.  Both derived temperatures were compared to the certified sensor in the analysis.  It was shown that the existing algorithm showed higher temperatures in the middle of the temperature profile.  The manufacture’s recommended algorithm did match more closely to the certified sensor throughout the profile.  It was recommended that the data be remapped with the manufacturer-recommended algorithm or that a lookup table be developed to correct for the middle ranges of the air temperature profile.  (KEYWORDS:  SNOTEL air temperature, NRCS, air temperature, YSI extended range)

An Assessment of Differences in Gridded Precipitation Datasets in Complex Terrain - Brian Henn; Andrew J. Newman; Ben Livneh; Christopher Daly; Jessica D. Lundquist (84th Annual Western Snow Conference, 2016)
Hydrologic modeling and other geophysical applications are sensitive to precipitation forcing data quality, and there are known challenges in spatially distributing gauge-based precipitation over complex terrain. We conduct a comparison of six high-resolution, daily and monthly gridded precipitation datasets over the Western United States. We compare the long-term average spatial patterns, and interannual variability of water-year total precipitation, as well as multi-year trends in precipitation across the datasets. We find that the greatest absolute differences among datasets occur in high-elevation areas and in the maritime mountain ranges of the Western United States, while the greatest percent differences among datasets relative to annual total precipitation occur in arid and rain-shadowed areas. Differences between datasets in some high-elevation areas may exceed 200 mm yr-1 on average, and relative differences range from 5-60% across the Western United States. (KEYWORDS:  orographic precipitation, precipitation uncertainty, hydrologic modeling, distributed datasets)

Hydrograph Characteristics in Relation to Low, Normal, and High Snowpacks in Utah – A Water Management Tool - Randall Julander (84th Annual Western Snow Conference, 2016)
Long term (>30 year) daily snow water equivalent (SWE) observations enable researchers to establish relationships between various SWE and hydrograph characteristics. The shape and magnitude of snowmelt hydrographs in Utah depend predominantly on the magnitude of the snowpack being melted.  As observed, years with low snowpacks melt out earlier, have lower peak flows and lower total flow volume than average or high snowpack years, and vice versa for high snowpack years.  However, in relation to melt-out dates at SNOTEL sites, a higher proportion of the annual April-July flow in low years is shifted toward the end of the hydrograph, whereas a larger proportion of flow occurs prior to melt-out in higher snowpack years. This paper examines the timing of peak flow and the proportion and distribution of flow relative to the timing of snowpack melt out at selected watersheds and SNOTEL stations across the state of Utah. The ability to predict the temporal distribution of streamflow based only on the magnitude of snowpack and the melt out date at specific SNOTEL sites could improve water management, especially where limited or no seasonal water supply forecasts are available. (KEYWORDS:  SNOTEL, Snow Survey, SWE, hydrograph, peak flow)

Validation of Airborne Thermal Infrared Remote Sensing of Snow Surface Temperature in the Upper Tuolumne Watershed, Yosemite National Park, California, USA - Eric Keenan; Karl Lapo; Nicoleta Cristea; Nicoleta Cristea; Chris Chickadel; Jessica Lundquist (84th Annual Western Snow Conference, 2016)
Here we present 5-m spatial resolution thermal infrared measurements of snow surface temperature collected by a small airplane flying over the upper Tuolumne watershed in Yosemite National Park in February, 2016. The plane captured spatial and temporal variations in the temperature of the snow’s surface, while concurrent ground measurements provided a reference point to evaluate the aerial measurements’ accuracy. Thermal infrared measurements provide a diagnostic tool used to assess model representation of many key processes, including snowmelt rates, sensible and latent heat fluxes, and longwave radiation. Comparisons between airborne observations and ground based measurements indicate airborne observations reliably quantify snow surface temperature to within approximately 2°C. This difference indicates a considerable reduction in uncertainty when compared to modeled snow surface temperature. By correcting ground-based thermal infrared measurements for view angle snow surface emissivity effects, differences between ground based and airborne observations are reduced to approximately 1.5°C. (KEYWORDS:  surface temperature, remote sensing, ground validation, infrared)

The Need for Including Surface Temperature in Land-Model Evaluations (Extended Abstract) - Karl E. Lapo; Mark Raleigh; Eric Keenan; Nicoleta Cristea; Jessica Lundquist (84th Annual Western Snow Conference, 2016)
Physically-based models form the basis of our understanding of snow processes, especially in climates and locations with limited observations. However, process representations vary greatly between snow models. As the basis of our physical understanding, it is critical that we understand what model components are necessary for representing snow processes accurately. Snow model intercomparison studies repeatedly demonstrate divergence between simulated values, such as the snow water equivalent (SWE), but are unable to conclude what model processes are responsible (Slater et al., 2001; Feng et al., 2008; Rutter et al., 2009; Essery et al., 2013). This inability to describe what makes a snow model “good” degrades the community’s understanding of current and future energy and water cycles. We interpret this divergence between models to signify, at least in part, that the surface energy balance (SEB) of snow is not well known. In response, we argue for the inclusion of surface temperature (Ts) observations in future modeling studies and observation sites to better constrain the snow SEB.

Spatial Analog Models of Snow - A.C. Lute; Charles Luce (84th Annual Western Snow Conference, 2016)
Empirical modeling of physical processes is essential to the advancement of our scientific understanding and to the improvement of more complex physically based and conceptual models. In the face of climate change, these models must not only be grounded in strong knowledge of the natural world; they must also be transferable to conditions not observed in the historical record. Here we develop empirical spatial analog models of April 1 SWE and Snow Residence Time at SNOTEL sites based on winter temperature and precipitation. We find that spatial analog models capture the nonlinear relationship between the independent and dependent variables, provide very strong fits to the data, and provide additional insight into physical mechanisms.  A non-random cross-validation test indicates that the models transfer well to warmer conditions. Finally, we provide an example of how this simple empirical model can be leveraged to obtain information from more complex global climate models in a straightforward and computationally efficient manner.
Keywords: model transferability; snow; spatial analog

The Effect of the Vertical Canopy Structure on Snow Processes Scenarios: Simulations of the Vertical Resolved Energy Fluxes and Snow Using a Higher-Order Closure Multi-Layer Soil-Vegetation-Atmospheric Model - Laura McGowan; Kyaw Tha Paw; Helen Dalhke; Shu-Hua Chen; David Pyles (84th Annual Western Snow Conference, 2016)
Snow cover is a critical driver of the Earth’s surface energy budget, climate change, and water resources. Variations in snow cover not only affect the energy budget of the land surface but also represent a major water supply source. In California, US estimates of snow depth, extent, and melt in the Sierra Nevada are critical to estimating the amount of water available both California agriculture, urban and environmental users. However, accurate estimates of snow cover and snowmelt processes in forested areas still remain a challenge. Canopy structure influences the vertical and spatiotemporal distribution of snow, and therefore ultimately determines the degree and extent by which snow alters both the surface energy balance and water availability in forested regions. In this study we use the Advanced Canopy Atmosphere Soil algorithm (ACASA), a multilayer soil vegetation atmosphere numerical model, to simulate the effect of different snow covered canopy structures on the energy budget, water budget, temperature and other scalar profiles within different forest types in the Sierra Nevada, California. ACASA incorporates a higher order turbulence closure scheme which allows the detailed simulation of turbulent fluxes of heat and water vapor as well as the CO2 exchange of the within canopy layers. As such ACASA can capture the counter-gradient fluxes within canopies that may occur frequently, but are typically unaccounted for, in most snow hydrology models. Four different canopy types were modeled ranging from bottom heavy canopies with most of the biomass located near the ground to top heavy canopies with most of the biomass located near the top of the canopy. Preliminary results indicate that the canopy stand structure associated with the different canopy types fundamentally influence the vertical scalar profiles (including those of temperature, moisture, and wind speed) in the canopy and thus alter the interception and snow melt dynamics in the forested land surfaces. The differences in the vertical scalar profiles resulted in over one week difference in the complete melt of the seasonal below canopy snowpack between canopy types in high-snow scenarios. In addition, the turbulent transport dynamics, including counter-gradient fluxes are discussed in the context of the snow energy balance and potential misattribution of water sources within the vertical canopy that could occur when counter-gradient fluxes are not considered.  (KEYWORDS:  snow, canopy interception, turbulence, counter-gradient fluxes)

Harnessing the Seasonal Predictability of Streamflow (Extended Abstract) - Pablo Mendoza; Julie Vano; Andy Wood; Elizabeth Clark; Bart Nijssen; Eric Rothwell; Martyn Clark; Levi Brekke; Jeffrey Arnold (84th Annual Western Snow Conference, 2016)
In the western United States, most operational forecasts of seasonal streamflow either use: (i) regression equations based on in situ observations (e.g., snow water equivalent, rainfall) or (ii) hydrologic model simulations that employ current hydrologic conditions and historically observed weather sequences to generate an ensemble of possible futures (e.g., Ensemble Streamflow Prediction, ESP) (Day, 1985; Wood and Lettenmaier, 2006; Pagano et al, 2014;). In this project, we are developing a framework that includes benchmark forecasts and new techniques which include additional predictive information.  More specifically, the framework currently generates forecasts for a range of techniques (statistical, dynamical, and hybrid methods) that leverage predictability from both the land surface and climate

Exploring the Impacts of Reduced Snowpack Due to Light Absorbing Aerosols in Snow, Including Potential Influence on Wildfires - Catalina M. Oaida; Yongkang Xue; Thomas H. Painter (84th Annual Western Snow Conference, 2016)
The mountain snowpack is an essential resource for both the environment as well as society. Recent studies have shown light-absorbing aerosols (LAA) in snow such as desert dust and black carbon to be important players in surface energy and water budgets of mountain areas across Western United States (WUS). The presence of LAA in snow, by shifting snowmelt timing, can have an impact on soil and vegetation conditions in subsequent months. Based on historical data, strong correlations were found between snowmelt timing and wildfire activity, with the suggestion that a shorter snow season can lead to drier soil and vegetation conditions, which implies greater opportunities for wildfires. In this study, we aim to investigate the impact of a reduced snowpack and earlier snowmelt due to LAA in snow on wildfire risk across various regions of WUS, including the Cascade, Sierra Nevada, and southern Rocky Mountains.  To achieve this goal, we employ a regional climate model with a physically-based snow scheme that accounts for presence of LAA in snow. By comparing the LAA-loaded and LAA-free simulations over 10 years, we explore the changes induced by LAA to the water balance, as well as potential implications to wildfires. (KEYWORDS: dust and black carbon in snow, runoff changes, regional climate modeling, western United States, hydrologic cycle, wildfire risk)

Investigating the Response of an Operational Snowmelt Model to Unusual Snow Conditions and Melt Drivers - Mark S. Raleigh; Jeffrey S. Deems (84th Annual Western Snow Conference, 2016)
In the mountainous western United States, operational runoff forecasting centers typically use streamflow observations to calibrate coupled snow-hydrology models over multi-decadal periods.  When seasonal or annual snow conditions deviate from mean historic conditions, such as with extreme events (e.g., snow drought) or hydrologic disturbances (e.g., dust-on-snow), the accuracy of operational models can degrade.  Recently, streamflow forecasting errors in the Upper Colorado River Basin (UCRB) have been linked to interannual variations in dust radiative forcing, as retrieved from remote sensing.  Here we build off previous work in the UCRB to quantify spatial and temporal variations in optimal operational snow model parameters and evaluate linkages with interannual variations in snow accumulation (e.g., low vs. high snow years), spring snowstorm regime, spring temperature, and dust radiative forcing. Using 30 years of snow pillow data and corrected air temperature data at 110 stations in the Colorado-Utah-Wyoming domain, we derive optimal snow model parameters with independent calibrations at each site and year. Results show coherent spatial and temporal patterns in the model melt factors that are most strongly linked to peak snow accumulation and dust-on-snow.  These results have implications for operational forecasting, which uses fixed snow model parameters, irrespective of normality in snow conditions.
Keywords: dust-on-snow; melt factors; operational snow model; snow accumulation; Upper Colorado River Basin

Warning from the Past – The Message, Meteorology, and Myths form the Great West Coast Winter of 1861-1862 - Lawrence Schick (84th Annual Western Snow Conference, 2016)
The extreme flooding and cold of 1861-62 was like nothing ever documented for the West Coast of the United States. The two month onslaught of winter storminess was relentless. In an eight week period, at least six major storms pummeled the West Coast. From southern Washington State to Southern California, the flooding was so extreme, the high water marks of many major Western rivers remain records to this day.   The core of the extreme winter was actually a series of storms from early December 1861 to late January 1862. The severe weather affected Washington, Idaho, Oregon, California, Nevada, Utah and Arizona. Snows were deep, cold was intense and rainfall extreme.  The floods were catastrophic.  The Central Valley of California filled to a 300 mile long lake. The lower Colorado River peaked at 400,000 cfs. Fresh water “floated” on top of the near offshore waters of California. The author isolates several major atmospheric river weather patterns at the root of this sequence of unsettled weather. This investigation also dispels the common myths of 1861-62 flooding, then proposes lessons learned. (KEYWORDS: 1861-62, flooding, Pacific coast, California Central Valley, little ice age)

Inter- and Intra-Annual Variability in Snow Albedo, Grain Size, and Snow Covered Area from the Airborne Snow Observatory during Low Snow Years (2013-2015) - Skiles, S.McKenzie; Thomas H. Painter; Kat J. Bormann (84th Annual Western Snow Conference, 2016)
The Sierra Nevada snowpack is critical to the state of California, and the consistently lower than average snowfall during the dry winters of 2012-2015 contributed to statewide water stress. These ‘snow drought’ years could become more frequent in a warmer future; therefore it is of interest to understand spatial and temporal trends in snow properties during low snow years. Here we assess inter- and intra-annual variability in snow-covered area, snow albedo, grain size, and impurity radiative forcing across three low snow years in the Tuolumne River Basin above Hetch Hetchy Reservoir. Snow properties retrievals are made by the Airborne Snow Observatory (ASO), a coupled imaging spectrometer and lidar platform, which has been measuring spatial and temporal distribution of both snow water equivalent and snow albedo across key basins in the Western US since 2013. It is generally understood that net solar radiation (as controlled by variations in snow albedo and irradiance) provides the energy available for melt in almost all snow-covered environments, yet there are no spaceborne sensors that can adequately capture trends in this critical snow property at relevant spectral, spatial, and temporal scales in mountainous terrain. This data set offers the unprecedented opportunity to improve our understanding of what controls snow albedo in mountain basins, and its relationship with spatial and temporal snowmelt patterns.  (KEYWORDS:  remote sensing, snow hydrology, snow albedo, snow grain size, Airborne Snow Observatory)

The Battle of Winter Along the St. Lawrence Valley and in the Rest of Canada from 1760 to 1900 - Jerry Toupin (84th Annual Western Snow Conference, 2016)
Soon after the fall of New France (1534-1760, 1763) under French King Louis XV to the British Empire (English King George II and George III), more than 65,000 French Canadians were left under new rule along the shores of the St. Lawrence River towards the end of the 18th century and the early 19th century. For the ex-French colony, winter, snow and cold did not get easier after the battle on the Plains of Abraham around Quebec City (13 September 1759). This article looks at how the French colony, now under British government that led to the foundation of Lower Canada (1791-1841) and Upper Canada (1791-1841) and later Canada (1867), developed ingenious strategies to endure winter along what is called the snowiest valley in the world (The St. Lawrence Valley in Eastern Canada), considering its population (now more than 8 million), latitude (±45̊ N) and the nature of the climate (type Dfb; a continental temperate climate according to Köppen’s World Climate Classification or type 23C; a moderate, fairly wet continental climate from Litynski’s World Numerical Climate Classification). (KEYWORDS: Cold, snow, winter, Canada, St. Lawrence Valley, 1760-1900).

Satellite-Monitored Snow Cover in Western North America: A Comparison of Water Year 2015 to Median Conditions - Joel W. Trubilowicz; W.J. Floyd; D.V. D’Amore; A.L. Bidlack (84th Annual Western Snow Conference, 2016)
Snow covered area (SCA) is readily monitored via satellites, and can illustrate complex spatial patterns of accumulation and melt that cannot be captured via point measurements.  Along with its important relationship to total water supply, snow also insulates surface soil horizons, provides protection for plant root systems during freezing events, and can delay the onset of soil drying and the fire season.  Traditional snow course and snow pillow measurements illustrated that the water year of 2015 saw snow levels that were substantially below normal in much of western North America.  However, the determination of a 'normal' SCA pattern (and the subsequent determination of what is abnormal) for a region requires the processing and analysis of vast amounts of spatial data, and is often not logistically feasible.  Using emerging technologies for processing massive spatio-temporal data, we calculated the near-term (2000-2015) normal monthly snow covered area at 500 m spatial resolution for more than 4.2 million km2 to illustrate how the water year of 2015 departed from typical conditions in the eight major hydrologic basins of western North America. Over the 96 months/basins available for analysis, 27 new monthly minimums for SCA were recorded in the water year of 2015. The most severe departures from the near-term normals were in the more coastal and southern basins. (KEYWORDS:  Remote sensing, snow covered area, climatology, snow drought)

Streamflow and Snow Contribution to the Boulder Creek Watershed under Climate Change (Climate Perturbations?) - Qinghuan Zhang; Mark Williams (84th Annual Western Snow Conference, 2016)
Hydrological processes in mountainous watersheds control downstream processes, such as ecosystem interactions and groundwater recharge. The impact of climate change on the water cycle in mountainous regionsparticularly on snow and ice-is non-linear and requires more detailed research to help quantifying uncertainties in projections related to climate forcing. In this study, the VIC model is applied to the 270 km2 Boulder Creek Watershed at Orodell, Colorado, to simulate streamflow amount under a meteorological drought condition, and changes in snow water equivalent. The model parameters were first adjusted using current climatic forcings and streamflow measurements. The Nash-Sutcliffe efficiency (NSE) for streamflow from 2006 to 2010 is 0.77, rootmean-square-error (RMSE) is 0.45, and percent bias is 0.1%, which are within acceptable range. Sensitivity analyses show that the effect of 1℃ increase in temperature is the same as 5% ~7% decrease in precipitation on streamflow. With an increased temperature, the timing of peak flow will appear early. Under the condition of decreased precipitation or increased temperature, values of daily streamflow, runoff efficiency, and snow water equivalent will decrease. Understanding the response of streamflow to precipitation and temperature perturbations is significant in regulating water supply, and maintaining water balance in the mountainous areas under future climate change.   (KEYWORDS:  Boulder Creek, climate change, Variable Infiltration Model,)

Multi-Platform Data Fusion for more Accurate Spatial Estimation of the Sierra Nevada Snow - Zeshi Zheng; Ziran Zhang; Noah P. Molotch; Steven D. Glaser; Roger C. Bales; Martha Conklin (84th Annual Western Snow Conference, 2016)
Over 100 wireless sensors for monitoring realtime snow conditions were deployed in ten clusters distributed across the headwaters of the American River Basin of the Sierra Nevada.  The sensors are strategically placed to measure snow depth, temperature, relative humidity, solar radiation, and soil moisture across elevation gradient, heterogeneous slope, aspect and canopy-covered montane regions. Meanwhile, time series of snow water equivalent (SWE) maps were reconstructed using National Land Data Assimilation Systems (NLDAS) data and fractional Snow Coverage Area (fSCA) from MODIS for 2001-2014 snowmelt seasons using energy-balance model (Guan et. al., 2013) and the maps would be reconstructed every year after the snow melt-out date. Both data sources are spatially blended using k-nearest neighbors algorithm for extrapolating the current snow conditions from the sensor-networks data.
Keywords: American River; Sierra Nevada; snowpack; SWE; wireless sensors

2015 Title, Contents, and Minutes (83rd Annual Western Snow Conference, 2015)

Comparison and Error Analysis of Reconstructed SWE to Airborne Snow Observatory Measurements in the Upper Tuolumne Basin, CA - Edward H. Bair; Karl Rittger; Jeff Dozier; Robert E. Davis (83rd Annual Western Snow Conference, 2015)
We present scientific and computing improvements to our new reconstruction model compared to a previous model. Snow water equivalent (SWE) reconstruction involves building a snowpack up in reverse, from melt out to peak SWE, given estimates of melt energy and fractional snow covered area (fSCA). The model was initially tested at an energy balance site on Mammoth Mountain, near the Upper Tuolumne basin, where nearly all the output could be verified and the disappearance of snow was known precisely. A full energy balance version of the model, that computes melt hourly, accurately estimated SWE and most energy balance terms. We were not able to verify a key parameter, the snow albedo, possibly because of low snow depths that affected our ability to measure solar radiation reflected by the snow. A net radiation/degree-day version of the model, that computes melt daily, underestimated SWE, probably because of its coarse daily time step. We then used SWE from the Airborne Snow Observatory (ASO) in 2014 as ground truth to verify the energy balance reconstruction model. Given the high spatial and spectral resolution of ASO measurements, we assume they are an accurate ground truth. Compared to the Snow Data Assimilation System (SNODAS) and the Advanced Microwave Radiometer 2 (AMSR2), reconstruction (with two different fSCA inputs) was by far the most accurate, with a bias of 36-40 mm at the basin wide maximum SWE, and an RMSE of 32-43 mm for all ASO measurement dates. The AMSR2 SWE estimates were generally too low, probably because of deep snow and interference from the canopy. SNODAS tended to overestimate SWE, perhaps because of an overreliance on measurements from snow pillows which are purposely located at heavy snow sites. Finally, we tested the reconstruction model over snow pillows located across the entire Sierra in 2014. The bias was 3 mm and the RMSE 140 mm at the maximum SWE accumulation, showing significant lower than a previous model. Presentation slides (PDF)
Keywords: Airborne Snow Observatory; reconstruction; Sierra Nevada

Spatial and Temporal Snow Dynamics at the Southern Margin of North American Continental Snow Distribution - Jonathan J. Donald; Temuulen "Teki" Sankey (83rd Annual Western Snow Conference, 2015)
Snow is crucial for stream flow and water use needs of large populations throughout the western United States, especially in the arid southwest. Accurate estimates of spatial distribution and temporal dynamics of snow cover are important for forecasting as well as understanding sensitivity to future climate change. We examined regional-scale temporal trends in snow distribution across central and northern Arizona using MODIS MOD10 snow products, consisting of two tiles of 2,928 daily images between October 1, 2003 and June 1, 2014. The area studies covered a 245,041 km2 area of 51 HUC8 watersheds. We employed a Mann-Kendall test to examine the temporal trends during this time period, and compared these trends at SNOTEL point locations for temporal context. We found the MOD10 snow product performs well in estimating Arizona’s thin and discontinuous snow distribution. Mann-Kendall time-series analysis indicate significantly increasing trends in the annual number of snow covered days (SCD) over the 12-year period at elevation transitions such as the Mogollon Rim in central Arizona, while significantly decreasing trends are observed at a few locations of lower elevations leading to the desert margins in eastern Arizona. These results are important in understanding the role forest restoration might play in snow accumulation and retention.
Keywords: accumulation and retention; ephemeral snow cover; MOD10; northern Arizona; sensitive snow; snow trend

From Snow to Flow: Estimating the Timing of Peak Streamflow from SNOTEL Ablation Curves - Kara J. Ferguson; James McNamara; Ron Abramovich; Josh Johnston (83rd Annual Western Snow Conference, 2015)
Predictions of peak streamflow timing in snow-dominated river systems are essential for proper water management and recreational availability. This study evaluates historic snow and streamflow data from 11 river basins throughout Idaho to investigate the relationship between snowmelt at SNOw TELemetry (SNOTEL) sites and peak streamflow within each basin. The goal is to provide a simple predictive tool that estimates the probability of peak streamflow occurring within a certain number of days as ablation progresses from 0 to 100%. For individual basins we evaluate melt-out levels in increments of 10% from each SNOTEL site and use a probabilistic modeling approach to develop cumulative distribution function (CDF) curves which illustrate the probability of peak streamflow occurring within a given number of days from the date at which the SNOTEL site reaches each melt-out level. Results from the CDF curves also provide anecdotal indices of peak streamflow timing.
Keywords: melt-out timing; peak streamflow; probability; SNOTEL

Planning Beyond California's Three-Year Drought - A 2015 Hydroelectric Planning Perspective - Gary Freeman (83rd Annual Western Snow Conference, 2015)
Following three dry years, precipitation for the month of December 2014 was 131% of the Sierra Region’s 120-year December average; however October-December 2014 as a 3-month period continued to remain below average. On December 31, 2014, precipitation for the California Department of Water Resources (DWR) northern California 8-station index was 129% of its historical 30-year average. However DWR’s southern California 5- station index was only 70% of its 30-year historical average. Precipitation was much above average in northern Sierra and drier than average for the southern Sierra. In spite of this unbalanced situation statewide, the overall increase in precipitation appeared to many as a dramatic turnaround from one of the most severe droughts in California’s recorded history. However, in spite of this dramatic precipitation recovery, California’s snowpack at the end of December statewide was only 49% of average, thus remaining much below average, mostly due to the higher snowline accompanying the relatively warm December storms. For Pacific Gas & Electric Company which has historically produced about 38 percent of its conventional hydroelectric energy from the aquifer outflow of large volcanic springs in northern California and approximately 37% of its conventional hydroelectric energy from the snowpack, the fall rains after satisfying an unusually large soil moisture deficit made little difference in the outflow rates and added only meager amounts of recharge to northern California’s porous volcanic aquifer storage which had lost approximately four million acre feet from underground storage since 1999. The 2014 calendar year was highly unusual beyond its single characteristic of being dry. Minimum daily temperatures for the 12-month period for the Sierra Region were the warmest in 120 years of record. This additional heating resulted in some of the driest soils moisture conditions for California in the past 1200 years. While rain dominated precipitation caused flood damage in December for parts of California, river flows quickly declined following the December rains. Aquifer outflows in northern California continued to remain much below normal following December’s wetness. As of January 1, 2015, precipitation for the remainder of the water year would need to increase to about 135% of average to get 100% of average annual conventional hydro generation.   Presentation in PDF
Keywords: climate change; drought; hydroelectric; reservoirs; Sierra

Communicating Drought-Related Water Resources Forecast Information in California - How Drought Has Driven Improvement in the Delivery of Water Resources Forecast Information for Water Managers, the Media, and the Public - Alan Haynes (83rd Annual Western Snow Conference, 2015)
Drought is a seemingly straightforward concept, essentially a prolonged lack of sufficient precipitation over a given area. California has one of the most highly managed water systems in the world and it is difficult for municipal water users to be connected to the origin of their water or the extent of drought when there is such an intensive reliance on irrigation and the water always flows when the tap is turned on. The California Nevada River Forecast Center (CNRFC) uniquely combines weather, hydrology, and climate every day to create water resources forecasts that extend out to one year in the future for California (and much of Nevada). However, the secondary mission is to provide water resources forecast information for the enhancement of ecological and economic interests. Hydrologic forecasting becomes more difficult under low flow conditions at the same time that scrutiny of the forecasts increases. One product used to help convey the extent of the drought was the DWR’s Major Reservoirs Daily Graph. Another product that was especially useful to highlight in communicating the extent of the drought was the DWR’s 8-Station Northern Sierra Precipitation Index. Additionally, the use of social media allowed the CNRFC to interpret conditions for the general public. Future drought-driven improvements in CNRFC products and services include the ability to view three year look-back plots of seasonal and water year hydrologic forecasts. Since droughts reflect cumulative multi-year precipitation deficits, drought visualizations should include corresponding cumulative deficits and the CNRFC offered these depictions.   Presentation in PDF
Keywords: CNRFC; drought; Forecasting

Trends in Snowpack Across California - Minxue He; Mahesh Gautam; John King; Mitchel Russo; David Rizzardo (83rd Annual Western Snow Conference, 2015)
This study conducts a comprehensive trend assessment of snowpack conditions across California, a state where snowpack is critical in terms of storing water from winter precipitation and releasing it in late spring and early summer when demands of water are typically the highest. The Mann-Kendall and Theil-Sen trend tests using trendfree pre-whitening and bootstrap approaches are applied to the historical monthly (February 1st to May 1st) snow water equivalent (SWE) measurements recorded at 260 snow courses in the state. Most sites have a record longer than 50 years. The longest record is 104 years (1911-2014). The focus is on the April 1st SWE and the peak snow mass date (PSMD). For April 1st SWE, the study indicates that only 6% (5% downward, 1% upward) of the snow courses have statistically significant trends. At a regional scale, only the Feather River watershed shows a downward trend. For PSMD, eight sites tend to peak earlier (downward trends) while only one site peaks later (upward trend). Overall, state-wide trends in snowpack are not observed, yet there are significant trends at limited sites and regions in light of the warming climate.   Presentation in PDF
Keywords: California; Mann-Kendall and Sen’s trend tests; peak snow mass date; snow courses; Snow water equivalent

Snow Pillows, LiDAR, and Streamgauges: Incorporating Snow and Streamflow Observations in the Basin Water Balance - Brian Henn; Martyn P. Clark; Dmitri Kavetski; Bruce McGurk; Thomas H. Painter; Jessica Lundquist (83rd Annual Western Snow Conference, 2015)
Prior studies have suggested that point measurements of SWE may not be spatially representative of the basin snowpack. The development of remotely-sensed snow observations, such as the Airborne Snow Observatory (ASO) and MODIS-based snow cover estimates, allows for relating point and distributed estimates of snow. We examine how SWE at courses and pillows compares with distributed ASO SWE in water year 2014 in a highelevation basin in Yosemite National Park. We find that peak basin-mean ASO SWE was less than that found by averaging regional snow pillows, but that it melted at a slower rate than pillow SWE during the ablation season. Based on this, we develop an approach for bias-correcting historical snow pillow indices of SWE to better represent the basin mean. We then calibrate an ensemble of lumped hydrologic models to infer basin-mean precipitation from streamflow and SWE. Models calibrated to only streamflow observations have substantial uncertainty in inferred precipitation. Including appropriate SWE observations in the calibration is found to reduce this uncertainty. However, calibrating to fractional snow cover in addition to streamflow did not improve the consistency of the models. We suggest that this approach can improve understanding of water balance components in high-elevation, sparsely-measured basins.   Presentation in PDF
Keywords: basin hydrology; hydrologic modeling; orographic precipitation; remote sensing

A Simple Algorithm for Identifying Periods of Snow Accumulation on a Radiometer - Karl E. Lapo; Laura M. Hinkelman; Christopher C. Landry; Adam K. Massmann; Jessica D. Lundquist (83rd Annual Western Snow Conference, 2015)
Downwelling solar, Qsi, and longwave, Qli, irradiances at the earth’s surface are the primary energy inputs for many hydrologic processes, and uncertainties in measurements of these two terms confound evaluations of estimated irradiances and negatively impact hydrologic modeling. Observations of Qsi and Qli in cold environments are subject to conditions that create additional uncertainties not encountered in other climates, specifically the accumulation of snow on uplooking radiometers. To address this issue, we present an automated method for estimating these periods of snow accumulation. Our method is based on forest interception of snow and uses common meteorological observations. In this algorithm, snow accumulation must exceed a threshold to obscure the sensor and is only removed through scouring by wind or melting. The algorithm is evaluated at two sites representing different mountain climates: 1) Snoqualmie Pass, Washington (maritime) and 2) the Senator Beck Basin Study Area, Colorado (continental). The algorithm agrees well with time-lapse camera observations at the Washington site and with multiple measurements at the Colorado site, with 70 to 80% of observed snow accumulation events correctly identified. We suggest using the method for quality controlling irradiance observations in snow-dominated climates where regular, daily maintenance is not possible. Code for running the quality control algorithm can be found at https://github.com/klapo/moq.
Keywords: Colorado; interception; radiometer; Senator Beck Basin; solar irradiance

Persistent Wave Structures and Western Droughts - Marshall Liddle; Hans Moosmüller; John Lewis (83rd Annual Western Snow Conference, 2015)
We propose that anomalous sea surface temperatures and polar ice extent caused and maintained the highly persistent large-scale tropospheric wave structure over North America during the winter of 2014. This wave structure led to a persistent regime of dry weather in the western US and cold, wet weather in the Midwest and eastern US. The sea surface temperature anomalies acted as waveguides. The polar ice extent anomaly acted to maintain a meridional feedback of polar wave energy, oriented along a narrow longitudinal range, which stabilized and reinforced the existing stationary wave over North America. The research testing this conjecture is ongoing, based on analyses of archived sea surface temperature data, polar ice extent data, and comparisons between similarly persistent winter weather patterns during other years. It is our hope that this effort will contribute to a broader understanding of dominant large-scale wave modes in the troposphere—modes that are determined in any particular case by a finite roster of thermal and geographic forcings.
Keywords: drought; persistence; polar ice extent; Rossby wave; sea surface temperature

Spatiotemporal SWE Variability of the Columbia River Basin - Abigail Lute; John T. Abatzoglou (83rd Annual Western Snow Conference, 2015)
Understanding the spatial and interannual variability of snowpack in montane regions such as the western U.S. is a key component of water management. Studies in this vein have typically focused on west wide analyses and found correlations with the El Nino Southern Oscillation and the Pacific Decadal Oscillation. However, smaller scale, subregional analyses may offer different insights into the spatiotemporal variability of snowpack which may be useful for water management at local scales as well as ecological assessments and planning. We consider March 1, April 1, and May 1 snow water equivalent at 243 sites within the Columbia River Basin over the years 1983-2012. A rotated principal component analysis is performed and resulting scores and loadings are correlated with a range of topographic and climatic variables. The first and second components of April SWE are strongly linked to latitudinal shifts in the jet stream. The second component is also correlated with the occurrence of Pineapple Express events. The third component is strongly correlated with interannual temperature and precipitation variability.
Keywords: Columbia River Basin; interannual variability; principal component analysis; spatial variability; SWE

Temperature Trend Biases in Gridded Climate Products and the SNOTEL Network - Jared W. Oyler; Solomon Z. Dobrowski; Ashley P. Ballantyne; Anna E. Klene; Steven W. Running (83rd Annual Western Snow Conference, 2015)
In the mountainous western U.S., temperatures from high-resolution gridded climate products are often used to assess climate impacts on local hydrology and ecosystem processes. However, there has been little formal analysis on the ability of these products to accurately capture temporal variability and trends in climate. Here, we summarize and expand upon recent assessments of trend biases in the widely used PRISM and Daymet data products (Oyler et al., 2014, 2015). Throughout the western U.S., we find that PRISM and Daymet contain systematic cold and warm trend biases. Most notably, we show that the products have propagated an extreme warm bias from the SNOTEL station network across large areas of mountainous terrain. Presentation slides (PDF) - Artificial Amplification of Warming Trends Across the Mountains of the Western United States
Keywords: Daymet; inhomogeneities; PRISM; SNOTEL; temperature trends

The Influence of a Heterogeneous Mixed-Conifer Canopy on Snow Accumulation and Melt - Eryn E. Schneider; Andrew J. Larson; Kelsey G. Jencso (83rd Annual Western Snow Conference, 2015)
The patterns of snow accumulation and ablation have been linked to the timing and quantity of available water in the semi-arid forested mountain watersheds. Forest patterns are often used as surrogates for processes where we expect that spatially recognizable structures give rise to ecohydrological processes. Forest canopies exhibit heterogeneity manifested as a mosaic of differing species, spatial arrangements, and canopy densities that differentially intercept precipitation and absorb or reflect radiation; thereby controlling the processes of snow accumulation and ablation. In this study we examined how heterogeneous canopy structure influenced the spatial variability of snow water equivalent (SWE) and disappearance date. High resolution, empirical snow measurements were collected at peak accumulation and monitored regularly throughout the melt season on two, 4.48 ha, fully georeferenced, mixed-conifer plots in western Montana. In 2014, peak accumulation occurred on March 18 and snow lasted 48 days with peak snow water equivalent ranging from 0 -17.9 cm. Percent canopy cover ranged from 0-86%. Higher canopy density areas had lower snow accumulation and earlier disappearance dates. By linking canopy patterns to specific snow processes, we will be able to improve process based models to provide more accurate predictions of water availability. Model predictions can be scaled up to management relevant scales and provide managers with empirical management recommendations for optimizing water resources given climate change and increased drought.   Presentation in PDF - Spatial Variation of Snow Water Equivalent and Snow Disappearance Date Beneath a Mixed-Conifer Canopy
Keywords: forest canopy; mixed-conifer forest; snow disappearance date; Snow water equivalent; spatial heterogeneity

Variability of Cloud Cover and its Relation to Springtime Snowmelt and Runoff - Edwin Sumargo; Daniel R. Cayan (83rd Annual Western Snow Conference, 2015)
Much of the variability in water supply and an important part of the uncertainty in water supply forecasts are driven by the variability in solar insolation, which in turn is modulated by cloud cover. Here we investigate the space/time variability of cloud and incoming radiation and how it may affect snowmelt and streamflow. We use NASA/NOAA Geostationary Operational Environmental Satellite (GOES 9-11 and 15) albedo product (α) spanning from 1996 to 2012 during the daytime (8-16 PST) over the westernmost U.S. (25-50 °N, 113-130 °W) with 4-km spatial and 30-minute temporal resolutions. Only elevations above 800 meters are included to avoid contaminations from coastal marine and low stratus clouds. A translation of cloud albedo (αcloud) to incoming surface radiation yields results that are well correlated with time series from surface radiometers at selected Sierra Nevada locations. Cloud albedo varies considerably from day to day, month to month, and even from year to year. To determine the most prominent spatial αcloud patterns and their temporal variability, we conduct a Rotated Empirical Orthogonal Function/Principal Component (REOF/PC) analysis. The 5 leading REOFs account for ~66% of the total αcloud variance. The leading REOF (~19%) covers portions of the Sierra Nevada and the Cascades and has a relatively high variance during the springtime, indicating its pertinence to snowmelt. During spring and early summer, these anomalous cloud patterns exhibit significant influence on snowmelt and runoff (R2 > 30%), with anomalously high αcloud producing lower snowmelt/runoff and vice versa. Correlations reveal a strong change in the response to incoming radiation of snowmelt and streamflow over the seasonal transition from winter-to-spring-to-summer. Dry years and wet years exhibit considerable difference in cloud amount and pattern, with lower overall springtime cloudiness in drier years, which leads to higher surface radiation available for snowmelt.   Presentation in PDF
Keywords: cloud variability; empirical orthogonal function; satellite remote sensing; snowmelt; streamflow

Understanding the Spatial Distribution of Snow Water Equivalent in Paired Basins in Southwest Montana, USA - Jason Welz; Jordy Hendrikx; Stuart Challender; Paul Stoy (83rd Annual Western Snow Conference, 2015)
The goal of this research, which was the focus of a master’s thesis, was to build upon previous investigations of the processes controlling the spatial distribution of snow water equivalent (SWE) in alpine environments. This involved taking a comprehensive look at the widely accepted physiographic variables of: elevation, slope, aspect, solar radiation, and wind exposure, but also avalanche activity, which has been given limited explicit inclusion. The paired basin design adopted in this study, between hypothesized avalanche-prone and avalanche-free basins, has been previously used to correlate avalanche activity with snowmelt runoff. However, it has not been used in an attempt to parse out which variables have the dominant influence on SWE distribution between adjacent areas of very similar physiographic character. While most previous studies have focused on the period of peak SWE to study its distribution, this current research considered the evolution of the controlling variables throughout snowpack development, and subsequent melt-out. A robust dataset of snow depth and SWE measurements were collected January 31 - July 10, 2013 on Cedar Mountain near Big Sky, MT. Physiographic variable values were extracted from a 10 m resolution digital elevation model (DEM) at snow sample points and input as predictors of observed SWE in multiple linear regression (MLR) and binary regression tree (BRT) models to spatially distribute SWE across the study area. Optimal models were selected by various measures of goodness of fit and cross-validation criteria. Calculated R2 values for MLR models (0.17-0.57) and BRT models (0.33-0.66) were comparable to previous studies indicating a relative level of success in predictive performance. Subsequent analysis of each optimal model’s variable selection and predicted SWE distributions revealed differences in the spatial and temporal patterns of this metric between the paired basins, confirming some well-understood processes as well as offering new insights.   Presentation in PDF
Keywords: avalanche; binary regression tree; paired basin; Snow water equivalent; spatial distribution

2014 Title, Contents, and Minutes (82nd Annual Western Snow Conference, 2014)

Snow Water Equivalent Estimates in the Hindu Kush and the Sierra Nevada Using Passive Microwave and Reconstruction - Edward H. Bair; Jeff Dozier; Carrie Voyuvich; Robert E. Davis (82nd Annual Western Snow Conference, 2014)
Accurate measurement of spatially distributed snow water equivalent (SWE) in mountain watersheds is perhaps the most significant problem in snow hydrology. We examine SWE measurements from two techniques. The first uses passive microwave estimates, provided by the National Snow and Ice Data Center, from the AMSR-E sensor aboard the Aqua satellite. Passive microwave (PM) has been used to estimate SWE for decades, and while it is subject to numerous problems, it is the only source of global real-time SWE estimates. Recently, SWE Reconstruction has been shown to be accurate at estimating basin-wide SWE in the Sierra Nevada. Reconstruction combines a melt model with snow covered area measurements to retroactively build the snowpack, from disappearance back to its peak. Reconstruction can only be used retrospectively, so it cannot be used to estimate today’s SWE. Thus, we use Reconstruction of prior water years to better understand the strengths and weaknesses of PM SWE estimates. Our test case is California’s Sierra Nevada, where we have full natural flow estimates and a large network of SWE sensors for comparison. Our application area is the Hindu Kush range in Afghanistan, where there are neither stream flow nor ground-based SWE measurements. Both regions are snowmelt dominated and subject to drought. Using annual SWE estimates from Reconstruction for verification, our results show that annual PM SWE estimates are biased in California and Afghanistan. In California, SWE estimates from AMSR-E are too low, by up to 10×. In the Amu Darya, one of the largest basins in Afghanistan, SWE estimates are too low by about 2×, while in 5/8 basins, PM SWE estimates are consistently too high. In terms of ranks, PM performs poorly, having low Spearman rank correlation coefficients. An exception is the Amu Darya, where the Spearman correlation coefficient is 0.81 for the eight years studied. We examine potential sources of error. Consistent with previous studies, we find that PM error is caused by shallow snow, deep snow, and forest cover. The explanation for the relatively low bias in SWE and relatively high correlation of rank for the Amu Darya appears to be a snowpack that was neither shallow nor exceptionally deep in a region that is nearly devoid of tree cover.
Keywords: Afghanistan; AMSR-E; passive microwave; reconstruction; Sierra Nevada

Use of Snow Data From Remote Sensing in Operational Streamflow Prediction - Stacie Bender; Paul Miller; Brent Bernard; John Lhotak (82nd Annual Western Snow Conference, 2014)
The Colorado Basin River Forecast Center (CBRFC) issues operational forecasts of streamflow for the Colorado River Basin and eastern Great Basin. As part of a multi-year collaborative effort, CBRFC has partnered with the research-oriented Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate remotely sensed snow data from NASA’s MODIS instrument into operational hydrologic forecasting and modeling at CBRFC. Snowpackconditions indicated by MODIS informCBRFC forecasters when determining causes of divergence between modeled and recently observed streamflow. The first two years of the collaborative partnership have yielded improved forecasts at select locations, in select cases, using information from remotely sensed snow data. CBRFC and JPL also retrospectively analyzed relationships between the MODIS-derived snow datasets and streamflow patterns for several watersheds within CBRFC region. The collaboration is expected to continue over the next several years as CBRFC and JPL work to further improve modeling of snowmelt and prediction of snowmelt-driven streamflow in operational hydrologic forecasting.
Keywords: operational hydrology; remote sensing; snow observations; snowmelt forecasting; Streamflow forecasting

Predicting Streamflow Hydrograph Recession from Soil Moisture Loss at Utah SNOTEL Sites - Jordan Clayton (82nd Annual Western Snow Conference, 2014)
This analysis uses decreases in soil moisture (SM) at Utah SNOTEL sites during the summer months to predict discharge at nearby stream gaging locations during the recessional portion of the annual hydrograph using data from water years 2008-2012. The following characteristics were evaluated: (a) the influence of the SM loss at mid-depths (8”) on hydrograph recession; (b) the influence of moisture loss from deeper portions of the soil (20”) on late-season baseflow; and (c) the timing of this transition. Thirty-four pairings were used between SNOTEL sites and nearby stream gages in select locations throughout Utah, for 3-5 years each depending on data quality, to generate 143 total comparisons of soil moisture loss and stream discharge. Regressions were fairly strong (r2 > 0.8) where the SNOTEL site was in a location with slow meltout rates, ample infiltration, and minimal summer precipitation. In a few cases the correlation was remarkably strong (r2 > 0.95), even for SNOTEL sites located far from respective stream gages (e.g. >20 mi, >3500’ elevation difference for the best pairing). At such sites, transition timing in 2013 (between hydrograph recession and baseflow, and between predominantly 8” vs. 20” SM loss) was well predicted from 2012 data given the similarity in water years, with discharges at the transition point predicted from SM loss in 2012 less than 30% different than observed values in 2013. Conversely, predictions of discharge were poor where timing was not coincident between soil moisture and discharge due to poor infiltration, intense summer precipitation, flow control structures, or other factors. An index of the robustness of each pairing was generated to attempt to develop predictive relations for where this type of analysis might be most successful for a given type of water year (normal, abnormally dry, or abnormally wet) based on watershed characteristics (e.g. average peak SWE, basin runoff production, etc.); however, results suggest that identification of high quality pairings may need to be site-by-site.
Keywords: SNOTEL; Snow water equivalent; soil moisture; streamflow recession; Utah; Water supply forecasting

Impact of Future Climate On Water Availability of Snowmelt-Dominated Watersheds of the Upper Rio Grande Basin - Emile Elias; Albert Rango; Caiti Steele; John F. Mejia (82nd Annual Western Snow Conference, 2014)
Climate change is predicted to further limit the water availability of much of the arid southwestern U.S. In this study, the Snowmelt Runoff Model is used to evaluate the impacts of increased temperature and altered precipitation of a changed climate on snow covered area, streamflow timing and seasonal and total volume in the Upper Rio Grande. Simulations investigate a fairly hot and dry future condition at the end of the 21st century using a regionally recommended general circulation model downscaled to existing climate stations. Twenty-four subbasins of the Upper Rio Grande containing appreciable snowmelt and a long-term gauging station are simulated. Total basin snow covered area decreased by 55%due to future temperatures. SRM simulation shows that total annual 2099 volume for all basins was between 13% and 33% lower than 1999 total annual volume. Among the 24 basins there is considerable range in decrease in snow covered area (6-87%), total volume reduction (4-34%) and runoff timing shift (0-60 days early) indicating that climate change impacts are best evaluated at the subbasin scale in mountainous regions. Daily hydrographs for the snowmelt basins show higher streamflow in March and April, but less from mid-May until the end of the water year. SRM simulation provides a rapid and effective evaluation of the most resilient basins under a changed climate for planning and management purposes.
Keywords: climate change; Rio Grande Basin; snowmelt runoff model; water resources

The 2014 California Drought - Dealing with Extreme Dryness From A Hydroelectric Planning Perspective - Gary J. Freeman (82nd Annual Western Snow Conference, 2014)
The 2013 calendar year was the driest year on record for California. For San Francisco based Pacific Gas and Electric Company (PG&E), which operates the largest investor owned hydroelectric system in the United States, the water management planning challenges, which were encountered during the first three months of 2014 and the twelve unusually dry months preceding 2014 were unlike those of earlier droughts. The acceptance of both the concept of climate change impacts as well as new paleo-climatological research findings about California and the southwest were for the first time being given serious consideration in the Company’s water release planning. The prospect that the persistent high pressure region blocking the storm track into California fromthe Eastern Pacific and Gulf of Alaska could possibly remain “parked in place” became a principal scenario needed for effective planning. In terms of snow water equivalent (SWE), the February 2014 statewide snow surveys were less than 15% of the historical February 1 average. The demands on downstream water release requirements for maintaining biological flows, whitewater rafting, and other recreational opportunities have continued to increase in the past 38- 39 years from the 1976-1977 drought, which were two successive very severe dry years. Conditions leading into the 2014 drought included 15-years of generally declining wetness over much of California causing the northern California’s porous volcanic aquifer storage to decline significantly from the aquifer’s relatively high mid-1990’s storage state. Also water year runoff from rain-shadowed areas of the northern California’s Sierra and southern Cascades have been in a state of trending decline since the 1976-1977 drought, a condition likely attributable to impacts from climate change. Utilizing the latest research findings available in 2014 on climate change and drought, the approach to reservoir and power production planning at PG&E changed from that utilized with prior droughts. Rather than assuming median likelihood or some low level of exceedances probability for remaining seasonal precipitation, the planning would take place as if the high pressure system pattern would continue to persist with no additional runoff expected.
Keywords: climate change; drought; hydroelectric; reservoirs; Sierra

Percent Bias Assessment of Water-Supply Outlooks in the Colorado River Basin - Brent Harrison; Roger Bales (82nd Annual Western Snow Conference, 2014)
Water-supply forecasts on various watersheds are intended to predict the April through July (snowmelt) runoff and assist in estimating the total water-year runoff, and are thus are very important to users of water from those watersheds. Water-supply outlooks, a type of forecast, are made on major contributing watersheds of the Colorado River. This study reviewed the characteristics of twenty-eight watersheds on the Colorado River. During that review, a strong linear relationship was found between watershed elevation and yield. As elevation increased, the runoff yield increased in a linear fashion. When studying the relationship between runoff and area, it was found that there was a non-linear relationship between increasing area and increasing runoff. The skill level of April to July forecasts was examined using percent bias as a representative summary measure of forecast skill. Review of percent bias of forecasts during dry, near normal and wet years indicates that in dry years the forecasts have a positive bias while those in wet years have a negative bias. Forecasts for near normal runoff years show limited or no bias toward over or under prediction. Seventy percent of the values for the absolute value of percent bias for individual forecasts were 40 percent or less.
Keywords: bias; Colorado River; forecast; forecast skill; runoff

Optimizing Hydrologic Models Using Multi-Temporal LiDAR - Andrew Hedrick; Hans-Peter Marshall; Adam Winstral; Kelly Elder (82nd Annual Western Snow Conference, 2014)
The high degree of spatial variability of snow in complex terrain remains the greatest hurdle for obtaining more accurate forecasts of snow water equivalent in the Western United States. Expanding on previous work using repeated manual snow survey transects, we employ four independent airborne LiDAR scans of a 1-km2 study site at Walton Creek in northern Colorado at different moments during the accumulation period (snow-free, early season, mid-season, and max-SWE) to show that distribution patterns of snow depth maintain consistency from year to year. Though the LiDAR acquisitions occurred throughout different winter seasons, drifting and scouring locations remained relatively unchanged for the three snow-on surveys. By normalizing and standardizing each of the three datasets of snow depth we determined a correlation cutoff value for extracting drift and scour locations from the remainder of the study area. Next, we used the known drift and scour locations to optimize and tune the terrain parameters of the wind redistribution model component of Isnobal, a physically-based, energy- and mass-balance snow model developed by the USDA-ARS. Finally, the optimal cutoff values for the wind model terrain parameters are applied to a nearby site with similar physiographic features to Walton Creek where changes in snow depth were estimated from the early- and mid-season LiDAR surveys. Early results reveal that this technique can predict broad areas of drift and scour, but struggles with very small-scale features, likely due to physical factors that are not accounted for by the simple wind model.
Keywords: drift; Isnobal; LiDAR; scour; snow extent

Doing Hydrology Backward: Estimating Mountain Precipitation Patterns from Streamflow - Brian Henn; Martyn P. Clark; Dmitri Kavetski; Jessica D. Lundquist (82nd Annual Western Snow Conference, 2014)
Estimation of basin-mean precipitation in mountainous areas may be difficult due to high spatial variability and time-varying precipitation patterns. Streamflow offers additional information about the water balance of the basin with which to estimate precipitation. We apply a methodology for inferring basin-mean precipitation from streamflow using Bayes’ Theorem, and adapt this approach to snow-dominated basins in the Sierra Nevada mountain range of California. As part of this approach, we develop and couple a temperature-index snow model to an existing lumped hydrologic model. We infer 1981-2006 annual average precipitation across four basins and compare the results to those obtained from similar approaches based on climatological precipitation patterns. We also use the approach to identify an example of year-to-year variability in precipitation patterns, finding that the inferred precipitation patterns generally match other observations from two anomalous water years. The method offers the potential for inferring spatial precipitation patterns at a level of precision that could improve upon current methods. Future work on this approach will focus on identifying spatial patterns of precipitation across a more extensive collection of basins and water years.
Keywords: Bayes; precipitation; streamflow; water balance

Payette River Basin, Idaho: High-Resolution Modeling and Gauging - Mel Kunkel; Derek Blestrud; Pat Holbrook; Shaun Parkinson; Brandal Glenn; Matt Fletcher; Sean Elliot; Al Pittman (82nd Annual Western Snow Conference, 2014)
Idaho Power Company (IPC) is a hydroelectric based utility serving eastern Oregon and most of southern Idaho. Snowpack is critical to IPC operations and the company has invested in a winter orographic cloud seeding program for the Payette, Boise, and Upper Snake River basins to augment the snowpack. IPC and the National Center for Atmospheric Research (NCAR) are in the middle of a multi-year study to determine precipitation enhancement due to winter orographic cloud seeding in the Payette River basin.As part of this study, a target/control network has been established in the Payette River basin of Idaho using 15 SNOTEL gauges in or near the Payette River basin along with 14 IPC installed high-resolution precipitation gauges. The IPC precipitation gauges record to a hundredth of an inch (verses a tenth of an inch for SNOTEL) and can be used to determine precipitation enhancement from both individual storm systems as well as seasonal precipitation. Forecasts from a high resolution (1.8 km) WRF model, generated at the University of Arizona, for precipitation in the seeded and non-seeded areas will be compared against observed precipitation and used to determine the precipitation enhancement due to cloud seeding.Model to model and model to precipitation gauge comparisons will be compared in both seeded and unseeded areas in an effort to develop temporally and spatially explicit quantitative precipitation maps for the accumulation and variability in the basin.
Keywords: cloud seeding; gauging; high-resolution; modeling; Payette River

Dust-On-Snow Effects on Colorado Hydrographs - Chris Landry; Kim Buck (82nd Annual Western Snow Conference, 2014)
Desert dust emitted from the greater Colorado Plateau and deposited onto the Colorado Mountain system has increas ed in frequency and intens ity over recent decades . The consequent dust - induced reductions in snow albedo are affecting Colorado snowmelt hydro graphs by accelerating snowmelt rates, when dust is exposed at or near the snowcover surface. A combination of dust intensity per storm, depth of dust layers, and spring weather patterns affect how dust influences the change in spring snowmelt and runoff p at terns. These factors can be used to calculate melt forcing from dust, and this information can be used regionally to improve runoff forecasting. (Annotated selection of PowerPoint slides from the presentation at the 2014 Western Snow Conference by Landry, additional editing by Proceedings Editor) Presentation slides (PDF)
Keywords: albedo; CODOS; Colorado; dust on snow; runoff

Above-Canopy Snow Transport Rate in the Central Colorado Subalpine Zone - Charles F. Leaf (82nd Annual Western Snow Conference, 2014)
The principles of aerodynamics govern snow transport in open terrain and also the transport of snow within and just above the forest canopy. Only in the last forty years or so, have theories been developed and field tested for wind-driven snow transport above forest canopies. This report presents a seamless transition between the two phenomena.
Keywords: Colorado; forest canopy; snow transport; subalpine

Projected Changes in Snowfall Extremes and Interannual Snowfall Variability in the Western United States - A. C. Lute; J. T. Abatzoglou (82nd Annual Western Snow Conference, 2014)
Projected warming and more variable precipitation will impact snowfall accumulation and melt, with implications for water availability and management in snow-dominated regions. Projected changes in extreme snowfall events, which constitute 20-38% of annual snowfall water equivalent (SFE) in the western U.S., are confounded by projections of more extreme precipitation and the differential temperature sensitivities of snowfall events. Data from 20 global climate models downscaled and bias corrected to western U.S. Snowpack Telemetry stations are used to assess projected changes in extreme snowfall events and annual SFE. Annual SFE is projected to decrease at all stations. In the coldest regions, changes in the distribution of snowfall and precipitation events are similar, with substantial increases in the most extreme events and smaller changes in small and moderate events. In warmer regions, reductions are projected for all snowfall events, however large events will be far more resilient than small and moderate events due to differential temperature sensitivities and changes in precipitation. Variability in annual SFE is projected to increase, particularly in warmer regions, due to fewer snowfall days and the increasing importance of heavy snowfall events. In the coming century, water management will be challenged by reduced and significantly more variable snowpack.
Keywords: climate change; extreme; snowfall variability; temperature

Understanding Trends in Snow Accumulation and Streamflow Using Snow Telemetry and Streamgage Observations in the Missouri River Headwaters - Thomas Matthews; Jordy Hendrikx (82nd Annual Western Snow Conference, 2014)
The Missouri River headwaters are located in the mountains of southwestern Montana and drain the eastern side of the continental divide. These headwaters serve as a water source for the Missouri River basin, which covers 10 states with an approximate population of 12 million people. A key component of the annual water budget in the headwaters is from snowfall, accounting for around 70% of the total annual flow in this region. The Western U.S. is generally comprised of semi-arid to arid regions that exhibit a high degree of inter-annual to multi-decadal variability. Changing trends in water availability due to climate change and yearly variations must be understood and quantified for proper allocation and forecasting of water resources. Here we use snow, temperature and precipitation records from the Natural Resource Conservation Service (NRCS) and streamflow records from the U.S. Geological Survey (USGS) in a coupled analysis designed to assess recent changes in these temperature sensitive high alpine headwaters over the last 40 years of record. Snow water equivalence, streamflow and temperature are key metrics that are indicative of changes in these headwater regions and are useful in determining the amount, timing and duration of hydrologically important snow-driven events. These data are being examined to determine what role inter annual and decadal drivers such as the El Niño Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), and the Pacific/North American Pattern (PNA) play in controlling the amount and timing of water availability in this catchment. Metadata from the weather stations used in this study are being analyzed to determine how changes in station characteristics, such as vegetation growth or equipment updates, can help explain variances in trends or relationships seen in the data beyond large-scale climate variations.
Keywords: ENSO; precipitation; runoff; snow; temperature; water availability

Airborne Snow Observatory: Hetch Hetchy Basin Snow Water Equivalent Time Series, 2013 - Bruce J. McGurk; Thomas H. Painter (82nd Annual Western Snow Conference, 2014)
The Airborne Snow Observatory (ASO) 2013 demonstration mission collected detailed basin-wide snow information for portions of the Tuolumne Basin in California and the Uncompahgre Basin in Colorado. The ASO uses an imaging spectrometer and LiDAR systemmounted in an aircraft for collecting snow depth and snow albedo. Snow depth is combined with a calculated density field to produce distributed snow water equivalent. Weekly flights over the Tuolumne produced both basin-wide and sub-basin SWE estimates that were used in the USGS Precipitation Runoff Model to provide runoff forecasts for Hetch Hetchy Reservoir, the source of 85% of the water supply for 2.5 million people on the San Francisco Peninsula. Information produced by the ASO data collection and PRMS modeling is designed to improve the ability of reservoir operators to more efficiently allocate the last half of the recession limb of snowmelt inflow and be more assured of meeting operational mandates.
Keywords: Hetch Hetchy; LiDAR; PRMS; runoff forecasting; Snow water equivalent; Tuolumne

Opportunities and Limitations For Assessing Ski Area Vulnerability and Potential Low-Snow Adaptation Strategies in the Changing Climate - Lisa S. Nichols; Tim G. Frazier (82nd Annual Western Snow Conference, 2014)
The ski industry in the United States is being threatened by climate change due to rising snowlines, earlier spring melt, and more winter precipitation falling as rain. Snow depth, duration, and timing all are critical factors in the number of skier visit days. The ski industry, worth over $10 billion nationally, is important for the economic vitality of mountain communities in thirty-seven states, but profits decline in warm, dry winters. There are limited climate change mitigation and adaptation strategies available to the industry. Artificial snowmaking is utilized to ameliorate the experience of limited snowfall but is energy-intensive, water-demanding, and has high upfront costs. In addition, artificial snowmaking may be limited by warming winter temperatures and, in certain basins, access to water in the next few decades. In order to better plan future investments in snowmaking equipment and other adaptations, climate projections are needed at a sub-regional scale. However, uncertainty and assumptions increase when downscaling from global climate models. Downscaling with Multivariate Adaptive Constructed Analogues couples climate variables and is capable of accounting for complex terrain, and therefore offers the best projections for natural snow coverage and snowmaking viability by mid-century.
Keywords: adaptation; climate change; customer perception; ski industry; snowmaking

Modeling of Interannual Snow Storage for Long-Term Simulation - Noriaka Ohara; Ryan Johnson; Jacob Heward (82nd Annual Western Snow Conference, 2014)
Snow models in hydrologic engineering field have barely incorporated the long-term effect of the interannual snow storage such as glaciers because the time scale of glacier dynamics is much longer than those of river flow and seasonal snowmelt. It will be shown in the presentation that general energy and mass balance models for snow process may fail without consideration of the interannual snow storage effect. This study proposes an appropriate treatment for inland glaciers as systems in dynamic equilibrium that stay constant under a static climate condition. It is supposed that the snow/ice vertical movement from high elevation areas to valleys (lower elevation areas) by means of wind re-distribution, avalanches, and glaciation, may be considered as an equilibrator of the glacier system because it stimulates snow/ice ablation. The simplest implicit modeling of such a dynamic equilibrium snow system is introduced and discussed for the long-term snow simulation, and its demonstrative model application in Wyoming will be presented.
Keywords: Energy balance; equilibrium; glaciers; glaciology; mass balance models; snow storage

Niveograph Interpolation To Estimate Peak Accumulation of Snow Water Equivalent in Rocky Mountain National Park - Glenn G. Patterson; Steven R. Fassnacht (82nd Annual Western Snow Conference, 2014)
Since the late 1970s the US Department of Agriculture’s Natural Resources Conservation Service has used snow pillows at snowpack telemetry (SNOTEL) stations to measure the pressure of the overlying snowpack to provide a real-time daily record of snow water equivalent (SWE). Manual snow-course SWE measurements have been taken on or around the 1st of February, March, April and May for up to 75 years of record, with the April 1st SWE value typically used to represent peak SWE. However these have been shown to be in the order of 12% less than the actual peak, based on the SNOTEL record. In this paper, daily SNOTEL SWE data were used to improve the estimation of peak SWE from the monthly measurements at snow courses. First of the month SWE values were used to adjust the median time series to produce estimates of peak SWE for each year of record. Average annual niveographs (graphs of SWE versus time) were created from SNOTEL data collected near the snow course. Five SNOTEL stations in and near Rocky Mountain National Park, with at least 30 years of record, are being used to characterize the snowpack in the park. Average annual peak SWE values ranged from 143 to 720 mm. This method produced good estimates of peak SWE for the two sites tested. The estimates were improved when the trend of snow accumulation on May 1 was considered.
Keywords: niveograph; Rocky Mountain National Park; SNOTEL; snow course; Snow water equivalent; SWE

Are Temperature-Index Models Appropriate for Assessing Climate Change Impacts On Snowmelt - Mark S. Raleigh; Martyn P. Clark (82nd Annual Western Snow Conference, 2014)
Robust projections of climate change impacts are critical for natural resource planning in snow-dominated watersheds. Numerous studies have applied temperature-index (TI) snow models using calibrated parameter sets from the historic period, and estimate climate change impacts by forcing TI snow models with different climate scenarios. However, this methodology is questionable because (1) it assumes stationarity in model parameters, (2) it assumes the climate change signal is embedded in temperature alone, and (3) it does not account for changes in the snowmelt energy balance in a warmer climate. Here we explore the relationships between TI melt factors and changes in climate to understand the reliability of TI models for quantifying climate change impacts on snow hydrology. We examine historic relationships between temperature and melt factors (derived from observations) at 510 SNOTEL sites across diverse hydroclimates. Results show that melt factors decrease with increasing mean annual temperature at 98.6% of the sites (76% with statistical significance), and decrease with declining peak SWE and earlier peak SWE timing at over 90% of the sites. The results imply that historically calibrated TI models will overestimate snowmelt rates when applied in a warmer climate, and therefore their usage in climate change studies is problematic.
Keywords: climate change; Energy balance; physically-based model; temperature-index model

Climate Change Risks To Our Snowmelt Water Supply and Possible Adaptation Responses in the Southwest U.S. - Albert Rango; Emile Elias; Caiti Steele (82nd Annual Western Snow Conference, 2014)
USDA Regional Climate Hubs were established in 2014 to assist stakeholders in maintaining high agricultural productivity under conditions of climate change. The Southwest Regional Climate Hub is characterized by extreme climate variability and physical diversity. In the Southwest, as climate changes, water scarcity will become the most important issue.
Keywords: adaptation; climate change; regional climate hub; variability

Will the 2014 Drought in California Set A Record? - Maury Roos (82nd Annual Western Snow Conference, 2014)
Once again, severe drought is affecting California snowpack and water supply. Water year 2013 in California ended on a dry note with depleted reservoir storage. The new water year got off to a record poor start in many places with extremely low precipitation and snowpack. At the end of January, it looked like 2014 could become the driest water year of record. February arrived with above normal precipitation to avert a dire situation. However, 2014 is still one of our driest water years, probably to rank 4 in over 100 years. This paper will examine precipitation, snowpack, runoff, and reservoir storage in this third year of drought in California.
Keywords: California; drought; extreme; precipitation; reservoir storage

Simulating Streamflow Under a Warming Climate: Implications for Acequia Communities in the Upper Rio Grande - Caitriana Steele; Emile Elias; Albert Rango; John Mejia; A. Fernald (82nd Annual Western Snow Conference, 2014)
Over the next century, it is predicted that warmer temperatures and altered precipitation patterns in the Upper Rio Grande (URG) basin will have a deleterious effect on the seasonal accumulation of snowpack and the timing and duration of snowmelt. In Northern New Mexico, acequia communities situated at the outlet of snowmelt basins are particularly exposed to climate-induced changes in snowmelt runoff. In this paper, we assess the variability in climate-affected streamflow of four tributaries of the Rio Grande. Each tributary is an important source of surface water for acequia communities. We used the Snowmelt Runoff Model (SRM) to simulate runoff from 4 sub-basins for years when the annual volume of water produced was above the median annual value (1984-2013). This exercise yielded basin-specific model parameters that could be then applied in SRM simulations of snowmelt runoff under altered climate conditions. For 60 CMIP-3 and CMIP-5 general circulation models we determined central tendency and spread of projected changes in precipitation and temperature at two locations, comparing the period 1980-1999 with 2040-2069 and 2080-2099. For simulations of streamflow under a changed climate, we used data from those models which best represented hotter-dryer (HD), warmer-dryer (WD), hotter-wetter (HW) and warmer-wetter (WW) conditions. Our results suggest that in agreement with other studies, annual volume of runoff is closely tied to changes in precipitation amount, while peak flow timing is affected by warming temperatures. If there is sufficient snow accumulation, increasing temperatures result in earlier occurrence of peak springtime flows. With insufficient snow accumulation, the characteristic snowmelt hydrograph is lost entirely. In a warmer climate with wetter conditions, springtime peak flows occur earlier in the year, are of shorter duration and are of greater volume than historic flows.
Keywords: climate change; irrigation; New Mexico; Streamflow simulation

Soil Moisture Dynamics During Snowmelt - Kent Sutcliffe (82nd Annual Western Snow Conference, 2014)
Little research exists examining soil moisture characteristics under a snowpack, especially during the active meltout period. Unlike snow water equivalent (SWE) and snow depth, which has been measured by the Snow Survey Program for 80 years, soil moisture changes during meltout have been difficult to monitor and analyze. Advances in sensor technology, increased deployment of instrumentation, and longer period of records present new opportunities for analysis and a better understanding of soil moisture dynamics under snowmelt. Three characteristic annual soil moisture patterns are discussed. Analysis of hourly soil moisture, SWE, and precipitation data have resulted in the observation of new relationships between daily snowmelt and soil moisture. At most SNOTEL sites, snowpack melt results in diurnal soil moisture fluctuations. At well-drained sites, during periods of rapid melt, fluctuations of up to 10 percent soil moisture by volume are observed. Typically, fluctuations are expressed by all three sensors through the 50 cm measurement zone during the entire meltout period, or until saturation is reached. Diurnal fluctuations in soil moisture scale in magnitude with the SWE loss during the same period. At sites with well-drained soils and no run-in from adjacent areas, the volume of water transmitted through the entire 50 cm zone correlates well with the volume of SWE loss on a daily basis. Four select sites with different soil properties and geographic areas within Utah and California are examined and the correlation between SWE and soil water flux is quantified and found to range from an R2 of 0.50 to 0.76. Analysis of diurnal soil moisture fluctuation provides a valuable window into the significant water flux occurring during the melt cycle and may assist in making soil moisture a quantitative input in statistical-based streamflow forecasting.
Keywords: active melt; diurnal fluctuation; snow; snowmelt; soil moisture

Winter in New France: A Constant Battle (1535 - 1763) - Jerry Toupin (82nd Annual Western Snow Conference, 2014)
On behalf of King of France, François I, explorer, sailor and geographer Jacques Cartier and about 60 men sailed to North America from St. Malo, France in April-May 1534. They reached and explored parts of the St. Lawrence River banks (until August 1534) which would become the cradle of New France (for more than 2 centuries from about 1534 to 1763). Winter was brutal and merciless for the first settlers used to a milder climate in France. At the very beginning of the colony and thereafter, several people died from cold, famine and diseases, including scurvy. This article looks at how people, notably from about 20 settlers in 1608 in Québec City to approximately 65,000 in the new world in 1763 fought, managed and over time adapted to the harsh environment in what later became known as Canada.
Keywords: adaptation; Canada; New France; survival; winter

Understanding the Spatial Distribution of Snow Water Equivalent and Subsequent Snowmelt Runoff Patterns of Paired Basins in Southwest Montana - Jason Welz; Jordy Hendrikx; Stuart Challender; Paul Stoy (82nd Annual Western Snow Conference, 2014)
This paper presents the initial results of a research project with the primary goal of investigating the hydrologic role of avalanche activity alongside the physiographic variables (i.e. elevation, slope, aspect, wind shelter/exposure, landcover, and solar radiation) that the snow hydrology community widely consider to be the dominant controls on the spatial distribution of snow water equivalent (SWE) and subsequent snowmelt runoff in alpine basins. An extensive field campaign was conducted in two adjacent alpine basins in southwest Montana from January 31 to August 21, 2013, consisting of three survey periods to capture snowpack metrics during the phases of (1) accumulation; (2) peak SWE, and (3) ablation/snowmelt runoff. During each period, the same stratified random sampling methods were used to measure snow depth and SWE at transects along elevation contours. Transects were spatially distributed with the goal of acquiring a representative sample of the aforementioned physiographic variables as well as the components of avalanche paths. After quantifying the contribution of each of these variables to the distribution of SWE, we will also consider their impact on the timing and magnitude of snowmelt runoff. This will be determined by correlation to stream discharge measurements that were collected throughout the 2012- 2013 water year. The initial results are discussed as are the future steps.
Keywords: avalanche; mountain hydrology; runoff; Snow water equivalent; snowmelt

Using Hydrochemistry Data to Constrain the Role of Snow and Ice Meltwater in the Langtang Valley, Nepal - Alāna M. Wilson; Mark W. Williams; Rijan B. Kayastha (82nd Annual Western Snow Conference, 2014)
The Langtang River Basin of central Nepal is one of the most well-studied valleys of the Himalaya. With an elevation range of 1460m to 7246m and with the Upper Langtang Basin (above 3642m) approximately 40% glacierized, snow and ice melt play a dominant role in the hydrology. Presented here is a synoptic survey of hydrochemistry data from a pre-monsoon field campaign in May 2012. Major chemistry and isotopes are used to conduct hydrograph separations of the Langtang River to quantify the role of meltwater in river discharge. Results using End Member Mixing Analysis (EMMA) showa decline in the contribution of groundwater with increasing elevation - estimated at 24% at 1479m, down to 9% at 3642m. This work isolated contributions of 'high-elevation' water but EMMA did not identify distinct snow and ice contributions. Two versions of EMMA are compared – one including δ18O in the input tracer set and the second excluding it. EMMA results are compared to a two-component mixing model using δ18O as the sole tracer to separate groundwater from melt water. Ourobjective is to distinguish potential source waters through hydrograph separation. We show that using hydrochemistry data for EMMA can be an appropriate tool for this.
Keywords: EMMA; glacier and snow melt; hydrochemistry; Hydrologic mixing models

2013 Title, Contents, and Minutes (81st Annual Western Snow Conference, 2013)
Information includes Table of Contents SNOW NOTES Minutes of the Western Snow Confer ence Executive Committee Meeting Minutes of the Western Snow Conference Business Meeting 81st Annual Meeting of the Western Snow Conference – Attendees

Increasing Climate Variability and the Clues to Understanding What Makes Your Basin Flow - Abramovich, R. (81st Annual Western Snow Conference, 2013)
An increase in climate variability magnifies the challenges for water users, water managers and water supply forecasters. As the demand for water in the west increases, due to competing uses for this natural resource, so has climatic variability. Presented here is a review and reinforcement of past research on long-term streamflow forecast skill levels, examples of recent climate variability in Idaho, key indicators to monitor, and their relationship to historic snowmelt-streamflow relationships. Understanding these key climatic indicators and the amount of remaining snow in the basin results in a better understanding of your watershed and events that generate an increase in streamflow. Past climatic events are discussed to provide a better context for the relationship between melting snow and how a basin may react when extreme weather occurs. With an increase in climatic variability, our predictive power using historic tools has decreased, forcing us to look deeper at the underlying physical properties to understand snowmelt-streamflow relationships. Each basin is different and the sequence of events that produce rapid runoff is becoming required knowledge for water managers and users to understand what makes your basin flow.
Keywords: Climate variability; extreme weather; snow; snowmelt-streamflow relationship; streamflow

New Quality Assurance Technique for Meteorological Stations Based on A Physically-Based Hydrological Model - Bellingham, Bryant Keith (81st Annual Western Snow Conference, 2013)
Many groups depend on climate data from federal and state supported weather station networks such as the NRCS’s SNOTEL, and NOAA’s Climate Reference Network. While data from these stations are typically of high quality, there is no statistical parameter available to the public that quantifies the bias and the magnitude of errors in a time series. A time series error analyses could possibly detect subtle data anomalies, and problems with sensors, while providing a general level of confidence in the data for the user. HYDRUS-1D was used to construct a physically-based flow model for water and thermal fluxes for a SNOTEL site in Oregon from June 1, 2008 0:00 to October 31, 2011 23:00. Soil moisture and temperature values were predicted using the model and then compared to soil data measured with Hydra Probe soil sensors placed at 5, 10, 20, 50 and 100 cm. Simulations on hourly data sets typically yield RMSE from about 0.01 to 0.05 and 1 to 3 degrees C for soil moisture and temperature respectively. Model efficiencies decrease and RMSE increase for soil moisture with the presence of the winter snow pack when using degree day based model for snow water equivalent.
Keywords: cloud computing; meteorological station; physically-based model; quality assurance; time series

Estimating Snow Water Equivalent at NWS Climatological Stations - Farnes, Phillip (81st Annual Western Snow Conference, 2013)
Typically, National Weather Service (NWS) Climatological Stations measure snow depth but not snow water equivalent (SWE). However, SWE is generally more important than depth when used in hydrologic and wildlife studies. Typically, there are higher elevation stations that measure SWE but lower elevations stations are predominately Climatological stations that do not measure SWE. New snowfall densities are generally between 6 and 10 percent while snow packs can reach densities into the 25 to 35 percent range just prior to and during melt. As part of developing the climatic database for the core area of the Greater Yellowstone Area (GYA), daily SWE was computed for all Climatological Stations. Some of these stations have snow courses at or near the station. Also, snow measurements were made at some of these stations in conjunction with the Snow Sinking Studies on the Northern Range of Yellowstone National Park. Methods for computing daily SWE using snow depth, precipitation and temperature will be presented as well as comparisons between estimated SWE and measured SWE at ten stations. The lengths of records where both measured and estimated SWE exist vary from about 17 years up to about 75 years. Long range trends of SWE will be shown for stations with longer records.
Keywords: density; precipitation; Snow water equivalent; snowmelt; temperature

Modeling of Snowpack Accumulation and Losses in Mountainous Terrain for Both Snowpack Storage Mapping and Watershed Storage Estimates - Froyland, Hugo; Stackhouse, Josh; Schiefer, Erik; Decker, Rand (81st Annual Western Snow Conference, 2013)
A heuristic watershed-scale snowpack model that has been under development and verification at the University of Utah and now at Northern Arizona University since 1998 is now implemented on an articulate Geographic Information System (GIS) platform. Simple heuristic rules are established for the preferential accumulation and loss of snowpack in mountainous terrain. These rules include elevation and solar wattage, each at the pixel scale. The capacity for modern GIS to provide solar wattage explicitly from the root Digital Elevation Model (DEM), means that indexing this ablative potential with slope aspect and angle is no longer required. Each model run must be initialized with two snowpack Snow Water Equivalent (SWE) observations at different elevation within the watershed. One observation can be snowline. This means the model can be initialized for a water year start date, or an annual snowpack SWE maximum when it occurs, or forensic queries of historic events/years, and virtual events such as a “unit” storm or winter. Additionally, the efficiency with which a given watershed commutes water from snowpack storage to surface runoff is indexed with two different ratios; length of surface water channel in the watershed to area of the watershed, and length of watershed channel to watershed circumference. The test watersheds of Stackhouse (Rohde et al., 2012) are repeated with this model, and include four highland tributary watersheds in different physiographical provinces of the Rocky Mountains; Doyle Peak, San Francisco Peaks, Arizona; Kings Peak, Uintas, Utah; and Mt. Elbert and Jones Peak, Eastern San Juan Mountains, Colorado. These tributary sub-basins ranged in size from 88 to 210 million square meters. Snowpack accumulation and/or loss is modeled to the DEM pixel scale, in all of these cases, 30m by 30m. Snowpack SWE in storage, per pixel, is then integrated for an estimate of watershed aggregate snowpack SWE storage. As an aid in identifying watersheds that are particularly effective at snowpack SWE storage, this model allows for the comparison of SWE volumes in a given watershed to the area of the watershed; a measure of the watershed’s snow water volume to area efficiency. Another valuable data product of the model is a detailed mapping of snowpack SWE storage within the watershed at the pixel scale. This information can be used in a variety of ways. As examples of the decision support capabilities of the model, three water resource decision space challenges are investigated in an effort to demonstrate the utility of the model and include the following: Watershed target identification and ground based cloud-seeding generator siting for snowpack augmentation, including estimates of snowpack storage volume increases to be realized. Forest reclamation (thinning) target areas, at fine scales within a given watershed, that have the highest potential to increase net ground snow accumulation. Point locations within a watershed where the accumulation of snowpack storage properties at the pixel scale are indicative of the watershed averages. i.e. for the purpose of establishing ground-based observation stations to extrapolate the basin’s aggregate snowpack SWE from one or only a few observation sites.
Keywords: ablation; accumulation; modeling; Snow water equivalent; snowpack; SWE; watershed

Data Analysis of the Snow Pack Analyzing System Tested by UCAR - Heggli, Anne (81st Annual Western Snow Conference, 2013)
Snow pack measurements can be costly to perform and generally provide only snow water equivalent (SWE) and snow depth from which density can be calculated and the onset of snow melt can be estimated. A new automatic snow pack analyzing system designed by Sommer Systemtechnik in Koblach, Austria has developed new technology to measure snow pack characteristics. The instrument is an automatic in-situ measurement system that determines the percentage of liquid water and ice by measuring the “complex” impedance from which SWE is determined. However, the liquid water content as a percentage is a value that has never been able to be measured before. This Snow Pack Analyzing system or SPA system, as it is referred to, was installed at the (University Corporation for Atmospheric Research (UCAR) Test Field site in March of 2012 where it could be collocated and compared to conventional snow tube and snow pillow measurements. This manuscript will describe the measurement principal of the SPA system as well as the parameters that can be derived, including indicators to help improve the prediction of snow melt. Preliminary results from the UCAR Test Field site installation comparing the SPA system to both the snow tube and snow pillow measurement will also be presented. It is reasonable to conclude the SPA system can be a valuable addition to existing snow melt forecasting schemes.
Keywords: liquid water; snow pack; Snow water equivalent; SWE

Analysis of Future Snow Conditions for the National Climate Assessment - Kunkel, Kenneth E. (81st Annual Western Snow Conference, 2013)
The Third National Climate Assessment Report is under development. To support this effort, regional analyses of climate conditions were conducted, focusing on both historical trends deduced from observations and future projections derived from climate model simulations. A recent project on snowfall trends generally found declining total snowfall in the western U.S. at cooperative observer sites. Since the 1990s, the area with extreme high seasonal snowfall has been well below the long-term mean. Climate model simulations show substantial future warming throughout the west. Precipitation is simulated to decrease in the Southwest and increase in the Northwest and Alaska. These results suggest future declining snowpack in the southwest.
Keywords: climate assessment; projections; snowfall

Characteristics and Interannual Variability of Extreme Snowfall Events - Lute, Abby; Hegewisch, Katherine; Abatzoglou, John (81st Annual Western Snow Conference, 2013)
Extreme snowfall events provide significant contributions to total snowpack and the characteristics and variability of these events are important for interannual variability in water supply. This study assesses the characteristics of the heaviest snowfall event each winter including average amount, percent of annual snowfall accumulation, coincident mean daily temperature and relationship to ENSO using long-term records from both SNOTEL and National Weather Service Cooperative Network stations across the western United States. Results indicate that the biggest snowfall event of the year can contribute more than a quarter of total annual snowfall water equivalent (SFE) at SNOTEL stations. The size of the biggest snowfall event is strongly positively correlated with annual SFE across the West. ENSO is shown to have a northwest-southwest dipole pattern of correlation with the annual SFE, the size of the biggest event, and the percent of annual SFE contributed by the biggest event. Collectively, this analysis provides a basis for understanding the relative contribution of extreme snowfall events to water resources and provides information on the sensitivity of extreme snowfall events to interannual variability.
Keywords: event; interannual variability; snowfall extremes; SWE

Understanding Trends in Snow Accumulation, Water Availability, and Climate Changes Using Snow Telemetry and Streamflow Observations in the Missouri River Headwaters - Matthews, Tom (81st Annual Western Snow Conference, 2013)
The Missouri River headwaters are located in the mountains of southwestern Montana, and serve as a water source for 10 states and approximately 10 million people. A key component of the annual water budget in this headwater region is from snowfall, accounting for around 70% of the total annual flow. The Western U.S. is comprised of semi-arid to arid regions that exhibit a high degree of inter-annual to multi-decadal variability. Changing trends in water availability due to climate change and yearly variations must be understood and quantified for proper allocation and forecasting of water resources. Here we use snow, temperature and precipitation records from the Natural Resource Conservation Service (NRCS) and streamflow records from the U.S. Geological Survey (USGS) in a coupled analysis designed to assess recent changes in these temperature sensitive high alpine headwaters over the last 40 years of record. Snow water equivalence, snow depth, temperature and streamflow are key metrics that are indicative of changes in these headwater regions and are useful in determining the amount, timing and duration of hydrologically important snow-driven events. These data are being examined to determine what role inter annual and decadal drivers such as the El Niño Southern Oscillation (ENSO), the Pacific North American Pattern (PNA), and the Pacific Decadal Oscillation (PDO) play in controlling the amount and timing of water availability in this catchment. Metadata from the weather stations used in this study are being analyzed to determine how changes to the station, such as vegetation growth or equipment updates, could help explain any trends or relationships seen in the data beyond the natural climate variations.
Keywords: climate; Missouri; SNOTEL; snow hydrology; temporal trends

Airborne Snow Observatory: Next Generation of Basin Snow Measurement, Modeling, and Forecasting - McGurk, Bruce J.; Painter, Thomas H. (81st Annual Western Snow Conference, 2013)
The Airborne Snow Observatory (ASO) demonstration mission will collect detailed basin-wide snow information for portions of the Tuolumne Basin in California and the Uncompahgre Basin in Colorado in spring of 2013. The ASO uses an imaging spectrometer and LiDAR system mounted in an aircraft for collecting data allowing determination of snow water equivalent, snow depth, and snow albedo. Weekly flights over the Tuolumne will produce both basin-wide and detailed sub-basin SWE estimates that will be used in a hydrologic simulation model to improve the accuracy and timing of runoff forecasting tools used to manage Hetch Hetchy Reservoir, the source of 85% of the water supply for 2.5 million people on the San Francisco Peninsula. The USGS PRMS simulation model will be calibrated to the 459 square mile basin and will be updated at weekly time steps with both weather forecast data and distributed snow information from ASO flights to inform the reservoir operators of predicted inflow volumes and timing. Information produced by the ASO data collection and PRMS modeling is expected to improve the ability of reservoir operators to more efficiently allocate the last half of the recession limb of snowmelt inflow and be more assured of meeting operational mandates. This presentation will provide preliminary results from the project as it begins its first year.
Keywords: Hetch Hetchy; LiDAR; PRMS; runoff forecasting; Snow water equivalent; Tuolumne

What Makes Rain-on-Snow Events Hazardous: Field Study at Ward Valley, Lake Tahoe Basin - Ohara, N.; Kavvas, M.L.; Easton, D.; Dogrul, E.C.; Yoon, J.Y.; Chen, Z.Q. (81st Annual Western Snow Conference, 2013)
Rain-on-snow events tend to be more hazardous than snow-free-rainfall-runoff or snowmelt events in Western States. The field observations in Ward Creek watershed, Tahoe Basin, showed that the snowmelt induced by energy flux from raindrops scarcely contributes to the hillslope runoff during the major rain-on-snow event of May 7, 2000, due to the cold weather. Spring high flows in the Sierra Nevada may be mainly due to the high soilwater content in the top soil kept by continuous snowmelt water supply. It was also found that the overland flow or longitudinal flow within the snowpack may still happen even over unfrozen and unsaturated topsoil on a relatively mild hillslope (16 %). The overland/in-snow flow may be due to the difference in hydraulic conductivities of the snow and the top-soil. This overland flow within the snowpack may form up to 10 percent of the peak flood discharge at the field hillslope scale. It may be hypothesized that the overland/in-snow flow on the unsaturated top soil may be a common phenomenon. The high flood peak of the rain-on-snow events may be magnified by this insnow fast runoff mechanism as well as the snowmelt by raindrop energy transfer. To test this observation-based hypothesis, further studies on the runoff process within the snowpack are desirable.
Keywords: field measurement; overland flow; rain-on-snow event; snowmelt; spring flood

Lateral Free Water Flow and Snowmelt Lysimeters - Osterhuber, Randall (81st Annual Western Snow Conference, 2013)
Five winters of snowpack free water outflow data from two 18 m2 snowmelt lysimeters at the UC Berkeley Central Sierra Snow Laboratory are analyzed against coincident measurements of precipitation, snow water equivalent accumulation and ablation, and snow depth. Challenges in using outflow data as a water balance tool are revealed by the sometime greatly differing amounts of outflow recorded by the side-by-side lysimeters, and the ratio of outflow to precipitation. The data here give insight to subsurface lateral free water flow. Also described is an attempt to inhibit lateral flow beyond the lysimeter’s borders by cutting the full profile of the melting spring snowpack.
Keywords: free water; lateral flow; lysimeter; snowmelt

Variability of Snow Sublimation in the Upper Colorado River Basin - Phillips, Morgan (81st Annual Western Snow Conference, 2013)
Snowpack water stored in mountain environments is the primary source of water for the population of much of the western United States, and the loss of water through direct evaporation (sublimation) is a significant factor in the amount of runoff realized from snow melt. A land surface modeling study was carried out in order to quantify the temporal and spatial variability of sublimation over the Upper Colorado River basin through the use of a spatially distributed snow-evolution model known as SnowModel. Simulations relied on forcing from high resolution atmospheric analysis data from the North American Land Data Assimilation System (NLDAS). These data were used to simulate snow sublimation for several years over a 400 by 400 km domain in the Upper Colorado River Basin at a horizontal resolution of 250 m and hourly time-steps. Results show that total volume of sublimated water from snow varies 68% or between 0.95 x 107 acre feet in WY 2002 to the maximum of 1.37 x 107 acre feet in WY 2005 within the ten years of the study period. On daily timescales sublimation was found to be episodic in nature, with short periods of enhanced sublimation followed by several days of relatively low snowpack water loss. The greatest sublimation rates of approximately 3 mm/day were found to occur in high elevation regions generally above tree line in conjunction with frequent windblown snow, while considerable contributions from canopy sublimation occurred at mid-elevations. Additional sensitivity runs accounting for reduced canopy leaf area index as a result of western pine beetle induced tree mortality were also carried out to test the models sensitivity to land surface characteristics. Results from this comparison show a near linear decrease in domain total sublimation with reduced LAI. Model performance was somewhat satisfactory, with simulations underestimating precipitation and accumulated SWE, most likely due to biases in the precipitation forcing and errors in determining precipitation phase.
Keywords: snow; snow modeling; Sublimation; Upper Colorado River Basin

Synthetic Year-Independent Spatio-Temporal Patterns of Snow Depletion - Qualls, Russell J.; Arogundade, Ayodeji B. (81st Annual Western Snow Conference, 2013)
Snow cover extent is a key variable which is critically important for climate and hydrologic studies. In recent years, the MODerate Resolution Imaging Spectroradiometer (MODIS) satellite sensor has been used in a number of studies and gained widespread acceptance for estimation of snow cover extent due to its high spatial and temporal resolution. Several researchers have observed that snow accumulation and ablation occur in reasonably regular patterns from one year to the next. Thus, information from satellite imagery across different years ought to be able to inform the spatial distribution of snow in one year based on information in another year. This is a vital piece of information which has not yet been fully recognized or exploited. We have developed a method to synthesize the regular, year-independent, spatio-temporal pattern of snow depletion from the beginning to the end of melt seasons, using a series of snow cover maps produced from MODIS data across multiple years (2001 to 2011) coupled with the melt-out dates of a collection of SNOwpack TELemetry (SNOTEL) stations. The synthesized spatial time series have the capability of extrapolating snow covered area in space (e.g., during cloud obscuration) and time (e.g., for forecasting snow cover ablation). The accuracy of this method has been evaluated over the headwaters of the Upper Snake River in Western Wyoming with very good results. This method has many applications including cloud removal, within-season snow cover ablation forecasting, climate change impacts on snow and runoff, and modeling climatology of snow. These applications can be extended for use in water management and water supply forecasting.
Keywords: MODIS; SNOTEL; Snow ablation; snow accumulation; snow cover extent

An Algorithm to Estimate Traditional Snowfall Measurements from Ultrasonic Snow Depth Sensors at U.S. Observing Sites - Ryan, Wendy A.; Doesken, Nolan J. (81st Annual Western Snow Conference, 2013)
The measurement of snowfall is a climatologically important variable measured at U.S. observing sites dating back to the late 1800’s. Snowfall is inherently difficult to measure due to wind redistribution, compaction and melting that can occur prior to a snowfall measurement taking place. With automation of many U.S. observing sites in the 1990’s, snowfall measurements were abandoned due to lack of technology to continue the measurements at many locations. This study aims to test the feasibility of restoring traditional snowfall measurements at automated stations using changes in snow depth from ultrasonic sensors. The ultrasonic sensors were installed in a triplicate configuration along with a Geonor precipitation gage and a wetness sensor for verification. Results show fairly good agreement between manual measurements and automated snowfall estimates. Differences are mainly due to low density snow that is not measured by the ultrasonic sensors and also does not register measureable precipitation in the Geonor gage. Wind driven events also cause problems for the algorithm, but overall these events were mainly less than 2.5 cm (1 inch) as manually measured but not estimated by the algorithm at all.
Keywords: precipitation gauge; snowboard; snowfall; ultrasonic snow depth sensor

Using the Utah Energy Balance Snow Melt Model to Quantify Snow and Glacier Melt in the Himalayan Region - Avirup Sen Gupta; Tarboton, David G. (81st Annual Western Snow Conference, 2013)
Quantification of the melting of glaciers in the Hindu-Kush Himalayan (HKH) region is important for decision making in water sensitive sectors, and for water resources management and flood protection. Access to and monitoring of the glaciers and their melt outflow is challenging, thus modeling based on remote sensing offers the potential for providing information to improve water resources decision making and management. In this paper we report on a distributed version of the Utah Energy Balance (UEB) snowmelt model, referred to as UEBGrid, which was adapted to quantify the melting of glaciers taking advantage of NASA remote sensing and earth science data products such as, satellite data, reanalysis data and climate model outputs. The representations of surface energy balance fluxes in the UEB snowmelt model have been extended to include the capability to quantify glacier melt. To account for clean and debris covered glaciers, substrate albedo determined from remote sensing, and glacier mapping is taken as an input. Representation of glaciers within the model involves inclusion of glacier ice as a substrate and generation of melt from the ice substrate when seasonal snow has melted. In UEBGrid, a watershed is divided into a mesh of grid cells and the model runs individually for each grid cell. Users have control to provide separate inputs for each grid cell, or spatially constant inputs for the entire domain. Therefore, regional variability in snow and glacier melting is computed. Outflow can be aggregated over subwatersheds defined, for example, from a digital elevation model, and input into other hydrologic models. UEBGrid was tested using weather, climate and hydrologic data at Langtang Khola Watershed, Nepal. UEBGrid is being included into the EPA BASINS software to facilitate linking to other models and to take advantage of BASINS’s capability to manage input data and visualize results. This capability for using gridded NASA Earth Science data, and the associated data model and workflow for storage and processing of data into and out of models linked in BASINS advances hydrologic information science. The capability for estimating the melt from glaciers and snow in a data sparse region will help water managers in decision making and management of water resources in areas impacted by glacier and snow melt.
Keywords: Energy balance; glacier and snow melt; model; remote sensing

Comparison of Snowfall Between A Standard Precipitation Gauge and Snow Board Measurements - Starr, Banning; Elder, Kelly; Baggett, L. Scott (81st Annual Western Snow Conference, 2013)
The measurement of snowfall precipitation is important for ecosystem and watershed research, and avalanche forecasting. Obtaining accurate measurements of solid precipitation, or snow, remains challenging. Literature values suggest that measurement errors can range from 20% to 80% due to undercatch resulting from wind and other such variables. Some sources report overcatch. In 2007 a site was established by the Rocky Mountain Research Station on the Fraser Experimental Forest in the north central rocky mountain region of Colorado to compare snowfall between an unshielded standard Belfort Universal Gauge and snow board snow core measurements. The period of record for this study was within the winter months, defined by the accumulation of measurable snow typically between November and May, and including the water years of 2008 through 2012. Catch comparisons were made for 24 hour event periods. In addition, comparisons were made for annual accumulation of snow water equivalence between the gauge and the snow board. The null hypothesis was that catch deficiency in the unshielded Belfort Universal Gauge is statistically insignificant compared to snow board measurements for individual events, as well as the annual cumulative total for the winter months. The relationship between the event catch of the rain gauge and the snow board measurements was nearly one to one, and an R2 close to 0.94. Seasonal differences of 4% on average were statistically significant with the rain gauge undermeasuring solid precipitation.
Keywords: Colorado; Fraser Experimental Forest; rain gauge; snow board; solid precipitation

Observing the Elusive Intermittent Snow Using Traffic Camera Images - Wayand, Nicholas; Lundquist, Jessica (81st Annual Western Snow Conference, 2013)
Intermittent snow covers a majority of the western U.S. and is known to have contributed to rain-on-snow type floods. Quantifying the elevational contributions of melt water during such events is hampered from a critical lack of observations of the lowest snow extent. The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua offers the best available compromise of sampling and resolution to capture intermittent snow’s spatio-temporal snow cover variations over mid-latitudes. However, twice daily images from MODIS are significantly limited by cloud cover that may obscure rapidly melting snowcover; a critical model initialization state for flood forecasting models. In this study, we approach the question of quantifying the snowmelt contribution through an idealized simulation, followed by a comparison of the current available observations of intermittent snowcover.
Keywords: intermittent snow; rain-on-snow; remote sensing; traffic cameras

The Effect of Physiographic Parameters on the Spatial Distribution of Snow Water Equivalent in A Large Mountainous Basin - Wetlaufer, Karl; Hendrikx, Jordy; Challender, Stuart; Marshall, Lucy (81st Annual Western Snow Conference, 2013)
Water accumulated and stored is the winter snowpack throughout the mountainous regions of the Western United States is a critical, yet poorly understood resource. An improved understanding of the correlations between basin physiography (e.g. elevation, land cover, incoming solar radiation, etc.) and snow water equivalence (SWE) in large and diverse landscapes could lead to better estimates of the total volume of water stored in the winter snowpack. This study quantifies the effect of the physiography of a large (207 km2) and complex mountainous basin (West Fork of the Gallatin River basin in SW Montana) on the spatial distribution of SWE and snow density. Sampling took place near the time of peak SWE accumulation (~April 1st 2012).

2012 Title, Contents, and Minutes (80th Annual Western Snow Conference, 2012)
Includes Table of Contents SNOW NOTES Minutes of the Western Snow Conference Executive Committee Meeting Minutes of the Western Snow Conference Business Meeting 80th Annual Meeting of the Western Snow Conference – Attendees

Relationship of Field and LiDAR Estimates of Forest Canopy Cover with Snow Accumulation and Melt - Dobre, Mariana; Elliot, William J.; Wu, Joan Q.; Link, Timothy E.; Glaza, Brandon; Jain, Theresa B.; Hudak, Andrew T. (80th Annual Western Snow Conference, 2012)

Value Added Products - Farnes, Phillip E. (80th Annual Western Snow Conference, 2012)

Gauge Conversion Effects on Long-Term Precipitation Comparison and Records - Fisher, Daniel B. (80th Annual Western Snow Conference, 2012)
Climate sites measure precipitation using a variety of methods and sensors. Each individual sensor has its own catch efficiency which varies with solid and liquid precipitation. A climate site’s precipitation record may contain data from two or more types of precipitation gauges. Using parallel data from the accumulation gauges at four SNOTEL sites in Alaska, comparisons were made of the effects gauge transitions have had on the long term record. The records of each site indicate that significant change in gauge catch can occur with gauge transitions, though the variations cannot be tied to gauge type alone. These transitions should be taken into consideration when developing long-term assessments and while comparing recent data with earlier years. (KEYWORDS: precipitation gauge, SNOTEL, long-term precipitation records)
Keywords: long-term precipitation records; precipitation gauge; SNOTEL

Analyzing the Impact of Climate Change on Monthly River Flows in California's Sierra Nevada and Southern Cascade Mountain Ranges - Gary J Freeman (80th Annual Western Snow Conference, 2012)
The impact of climate change on monthly river flows in California's Sierra Nevada and southern Cascade Mountain Ranges and its potential to impact hydroelectric production was analyzed to determine changes that have taken place in two successive 35-year periods during the past 70 years. Unimpaired monthly flows from both California's Department of Water Resources' (CDWR) Data Exchange Center's (CDEC) files and from Pacific Gas and Electric Company's (PG&E) operational subbasin runoff forecasting files for the Feather River were analyzed for comparison of the two periods. A notable change was the shift of snowmelt runoff from the April through July period into the month of March. March flows were larger for the more recent 35-year period for all of the flow points analyzed in the Sierra and southern Cascades including two subbasins on the upper North Fork Feather River where rain shadowed climate change impact has significantly reduced both snowmelt and water year runoff in the more recent 35-year period. The increase in March runoff appears to be a combination of mostly earlier snowmelt due to warming temperatures and from an increase in proportion of March precipitation that now occurs as rainfall. In northern California both the shift of snowmelt into March and the reduction of snowpack overall has resulted in reduced late spring and summer flows during the months of April through June. Subbasins south of the Yuba River have for the most part increased overall snowmelt runoff for the March 1 through July 31 period, while subbasins from the Yuba River north have remained either equal or declined in snowmelt runoff in recent years. Both increased elevation and orographic cooling seem to be critical for delaying the impacts of climate change on affecting spring and early summer runoff. For a rain-shadowed subbasin such as Lake Almanor, the recent 35-year period shows a 22% decline in the April through July runoff caused primarily from a combination of: 1) earlier snowmelt, 2) increased proportion of precipitation occurring as rainfall in recent years with less snowfall overall, and 3) reduced aquifer outflow from springs. (KEYWORDS: climate change, subbasin, unimpaired flow, orographic, hydroelectric)
Keywords: climate change; hydroelectric; orographic; subbasin; unimpaired flow

Impact of Forest Canopy Density on Snow Accumulation and SWE Preservation Over Time - Hagberg, Daniel; Palmer, Dane; Decker, Rand (80th Annual Western Snow Conference, 2012)
This study analyzes how four differing forest canopy densities affect the rate of snow ablation in the ponderosa pine type forest of Northern Arizona, and develops visual correlations between the rate of snow sublimation and temperature, wind, relative humidity and exposed snow surface area. Reported here are the results gathered during the 2011-2012 winter season, from four different forest states: Alpine Meadow (0% canopy density) ~Meadow Recently thinned (15-30% canopy density) ~ Light Mature thinned (30-45% canopy density) ~ Medium Untreated (45-60% canopy density) ~ Dense
Keywords: and meteorological factors; canopy intercept; Ponderosa pine; Sublimation; SWE retention

Water Availability Index - Julander, Randall P. (80th Annual Western Snow Conference, 2012)

Effects of Temperature on the Propylene Glycol/Ethanol (PGE) Solutions Used in Mountain Precipitation Gauges with the Polysorbate Emulsifier Additive - Lea, Rowyn; Lea, Jon; Lea, Jolyne (80th Annual Western Snow Conference, 2012)
The object of this study was to verify the earlier test to determine the temperatures at which various dilutions of equal proportions of propylene glycol and ethanol (PGE) with the addition of an emulsifier Polysorbate 20 (brand name Tween 20) would freeze. Earlier tests were conducted with straight mixture of 50 percent by volume of propylene glycol and 50 percent ethanol by volume without an emulsifier. This repeat study was to determine if the Tween 20 emulsifier had an effect on the freezing properties and specific gravity as tested in the earlier experiment. This experiment was also to observe if the 3 percent by volume Tween 20 would keep the 48.5 percent by volume propylene glycol and 48.5 percent by volume ethanol solution from separating at high temperatures which could occur at the remote site locations.
Keywords: NRCS; precipitation gauge; propylene glycol/ ethanol (PGE); SNOTEL

Improved Estimates of Snow Water Equivalent at NRCS Aerial Markers Using New Statistical Methodology - Lea, Jon; Sturm, Matthew; Lea, Jolyne (80th Annual Western Snow Conference, 2012)
Natural Resources Conservation Service (NRCS) Aerial Markers snow depth data have been measured since the late 1940s and are located in remote areas of the West. These stations would typically take hours or days of ground travel to visit, so are measured by aircraft over-flights to get a monthly depth reading. This depth reading and an estimate of the snowpack density are used to estimate snow water equivalent (SWE) for use in water supply forecasting. The NRCS historically has used an empirical method described in the agency National Engineering Handbook (Davis, R. T., et al.) to calculate densities. Using Bayesian analysis technique, Sturm et al. developed densification parameters from worldwide snow pack data. With these parameters, the accuracy of the estimates of density can be improved using only the snow depth, day of the year, and climate class of the snowpack. These parameters were applied to a subset of data from February 1, 2012, NRCS Cooperative snow surveys where measurements of SWE and depth were measured. The density of the snow pack using the observed data was compared to the modeled density. Differences between the modeled and the measured densities were about 1%. With additional refinement, this method can be applied to depth readings throughout the NRCS Aerial Marker network to calculate SWE values in a consistent and repeatable fashion.
Keywords: aerial markers; Bayesian analysis; bulk density; climate (snow) class; NRCS; Snow water equivalent; SWE

The Nature of Snow and Rain Along the Northern Gulf of Alaska During the Winter Months - Papineau, John (80th Annual Western Snow Conference, 2012)

Contrasting Snowpack Trends in the Sierra Nevada of California - Roos, Maurice; Sahota, Sunny (80th Annual Western Snow Conference, 2012)

Initial Evaluation of National Weather Service Ensemble Post Adjustment Procedure on Monthly Flow Forecasts at Three Forecast Points in the Western U.S. - Streubel, David (80th Annual Western Snow Conference, 2012)

Pioneers Through Winter in North America: Paleo-Indians and Paleo-Eskimos - Toupin, Jerry (80th Annual Western Snow Conference, 2012)
We may never find out exactly how humankind first reacted towards cold, snow and winter. Yet in North America, this first contact following the post-glacial era (20,000 years ago) can be partly traced back through archaeological evidence. Traces from first settlers possibly coming from Siberia can be found in Alaska and in the Yukon as far back as 14,000 years ago. Excavations done farther south (near San Bernardino, California, and in Mexico) strongly suggest that toolmaking people were even there 50,000 years ago (Simpson, 1980). Scientists named these first migrants as Paleo-Indians (47,000 to 14,000 years ago) and Paleo-Eskimos farther north (±6000 years ago). They possibly crossed the Bering Strait located between Asia and Alaska and later settled in vast parts of North America. Others might have sailed along the North American West Coast (Mochanov, 1980). More specifically, we will examine how people coped with winter in the Canadian Arctic, West Coast and Prairies, Southern Ontario and Michigan, Québec and the Maritimes/Maine, USA. It appears as though winter created a dual life for all of the new residents.
Keywords: cold; North America; Paleo-Eskimos; Paleo-Indians; snow; winter

Methods for Quantifying the Effect of Physiographic Parameters on the Spatial Distribution of Snow Water Equivalent in Mountainous Basins - Wetlaufer, Karl; Hendrikx, Jordy; Challender, Stuart; Marshall, Lucy (80th Annual Western Snow Conference, 2012)

2011 Title, Contents, and Minutes (79th Annual Western Snow Conference, 2011)
Content includes Table of Contents SNOW NOTES Minutes of the Western Snow Conference Executive Committee Meeting Minutes of the Western Snow Conference Business Meeting 79th Annual Meeting of the Western Snow Conference – Attendees

The Potential of Landscape Scale Treatments to Reduce Sublimation Losses of Critical Water Supply Snowpack in the Western United States - Bringhurst, A.; Williamson, K.; Werbylo, K.; Decker, R. (79th Annual Western Snow Conference, 2011)
A variety of treatments were tested for their effectiveness at limiting sublimation losses from snowpack. Treatments tested included vertical compaction, spraying the snowpack with a coating of vegetable oil, and applying a layer of chipped Ponderosa Pines slash biomass over the top of the snowpack. In meadow areas, untreated snowpack ablated at a rate of 0.66 centimeters of snow water equivalent (SWE) per day, while snowpack covered with a thick blanket of biomass ablated at a rate of 0.10 centimeters of SWE per day. Further, at the end of the data collection period, the control had lost 100% of its original SWE, while the biomass treated snowpack only lost 22% of its original SWE. In areas with a dense forest canopy, untreated snowpack ablated at a rate of 0.53 centimeters of SWE per day, and the snowpack treated with a thick biomass blanket averaged a loss of 0.20 centimeters of SWE per day. It was determined that a thick layer of biomass (about seven to ten centimeters in depth) would help reduce sublimation losses of snowpack in both meadow and canopied areas. A cost analysis was performed to determine the price of application of the thick biomass blanket, and it was determined that one application would cost roughly $365 per 4,047 square meters (1 acre). This high cost of application poses a real challenge to the feasibility of implementing this treatment to reduce sublimation losses at landscape scales.
Keywords: Arizona, snowpack, sublimation, water supply, snow preservation treatment, biomass blanket

Montana Electronic Precipitation Map - Farnes, P.E.; Huddleston, J.; Flynn, K. (79th Annual Western Snow Conference, 2011)
An accurate estimate of average annual precipitation (AAP) is a necessity for completing hydrologic analysis, developing stream flow statistics, or doing other related water resource planning. Tools to develop and complete such analysis are required, capable of very quickly updating AAP information as it become available, and available for widespread use without proprietary requirements. To meet such a mandate, we developed a free-ware UNIX based tool called PMAP, which allows rapid AAP estimates through universal Kriging. A case study was implemented for the state of Montana using the 1981-2010 water-year averages and a 400 m elevation grid. While there are many geo-statistical techniques to choose from in completing such analysis, the strength in our work is not necessarily the method that we selected, but rather the data supporting it. We compiled AAP estimates for over 1,400 stations across the region including 1,100 stations in Montana, and 300 adjacent to the state. We evaluated the data using a number of geostatistical analysis techniques. Isohyetal lines were set at 50 mm (2 inch) increments under 500 mm (20 inches) and 250 mm (10 inch) increments above 500 mm (20 inches). The1981-2010 AAP map (isohyets and grids) will be available through the Montana Natural Resource Information System (NRIS) web site electronically, and software will be made available from the Montana Department of Environmental Quality upon request
Keywords: Montana, annual precipitation, Kriging, climatological stations, isohyetal, multivariate interpolation, annual precipitation

Climate Change and the Changing Water Balance for California's North Fork Feather River - Freeman, G.J. (79th Annual Western Snow Conference, 2011)
Climate change has likely had a large role the changing water balance on northern California's North Fork Feather River (NFFR) in recent years. In addition to changes in both snowpack quantity and timing of the spring snowmelt, some of its subbasins are also revealing a declining trend in water year runoff, while others do not. NFFR's complex terrain geometry includes a combination of both windward facing slopes and rain-shadowed leeward slopes that result in a mix of climatic gradients. The combined effect of having relatively low elevation and topographic barriers in the form of mountain ridges provide opportunity for both orographic cooling to take place on the windward slopes and compressional warming to take place on the leeward slopes as the airflow of frontal systems pass through the NFFR Basin. On the leeward, rain-shadowed slopes, air descends and warms quickly through compressional heating. Precipitation amounts quickly diminish as the descending air warms and increases its capacity to hold moisture. Both the Lake Almanor and East Branch of the North Fork Feather (EBNFFR) subbasins are two rain-shadowed subbasins that exhibit a declining trend in water year runoff. Trend declines that approach 308 hm3 (250,000 AF)/year collectively from the two subbasins since the early 1960's were analyzed using a water balance approach to help understand the declining runoff trend in terms of changes taking place at the watershed level. The decrease in both the low elevation snowpack and the water year runoff has resulted in a decline in hydroelectric output and less outflow of the NFFR into Lake Oroville.
Keywords: Precipitation, climate change, Feather River, orographic, water balance, rain shadow, northern California

A Preliminary Field Investigation on the Impacts of Forest Thinning on Snowpack Accumulation in Ponderosa Pine Type Forests of Northern Arizona - Heffelfinger, S.; Decker, R.; Sesnie, S.; Lopez, S.M. (79th Annual Western Snow Conference, 2011)
This study compared snowpack accumulation for three anthropogenic forest treatment (mechanized thinning) types with different levels of residual canopy cover representing dense to recently thinned forest conditions in Ponderosa pine forests of the Mogollon Rim country of northern Arizona. Reported here are results for the 2011 winter season's storm and peak snowpack accumulation time history from moderate elevation (300 m) snow courses that traverse three proto-typical ponderosa forest states: 1. Untreated: 45 to 60% canopy cover (Untreated - Dense canopy cover); 2. Thinned about 10 years prior: 30 to 45% canopy cover (Medium Thinning - Medium canopy cover) and 3. Recently thinned: 15 to 30% canopy cover. (Heavily Thinned - Sparse canopy cover )
Keywords: Mogollon Rim, canopy interception, canopy cover, Ponderosa pine, snowpack accumulation, sublimation, Ponderosa pine

The Mill Flat Fire Hydrologic and Flood Potential Evaluation - Julander, R.; Vaughn, K.S.; Bricco, M.; Uriona, B.; Nault, B. (79th Annual Western Snow Conference, 2011)
The Mill Flat Fire near New Harmony in southern Utah in 2009 posed a substantial risk of flooding and possibly mud/debris flow from the steep terrain and nearly 200% of average snowpack in the area. This hydrologic evaluation and aerial photographic survey by NRCS Snow Survey quantified in general terms what that risk was based on the snowpack inside the fire area and on the contributing watershed versus outside the area where NRCS has a SNOTEL monitoring station. The assessment included the area's ability to infiltrate both snowmelt and a potential rain-on-snow event based on current soil moisture characteristics as well as measured infiltration rates. We were able to define at each sample location the current snowpack, soil moisture content, and an estimate of infiltration rates and to relate this information to the same information at the SNOTEL site. Large portions of the steep south facing aspects throughout the watershed, up to as high as 2590 meters in Dam Canyon, were bare of snow cover at the time of the survey even though snowpacks were much above average. However, areas that had even moderate slopes as low as 2255 meters on south east, east, north or northwest facing aspects still had substantial snowpacks. Data and analyses from the fire area indicated that the watershed could easily infiltrate much if not all of the snowpack and that the greatest danger of flooding would be a large rain-on-snow event.
Keywords: SNOTEL, NRCS, Utah, fire, flood, watershed evaluation, infiltration, soil moisture

Developing NRCS SNOTEL and SCAN Soil Moisture Parameters for Water Supply Forecasting Applications - Lea, J.; Harms, D. (79th Annual Western Snow Conference, 2011)
Soil moisture is an important component in determining watershed hydrologic condition, and as a contribution to streamflow. Most hydrologic models use precipitation and soil climate information as surrogates for soil water holding capacity and water flow through the soil. The Natural Resources Conservation Service (NRCS) Snow Survey and Water Supply Forecasting Program has a network of installed soil moisture and soil temperature sensors in their Soil Climate Analysis Network (SCAN) and at some SNOwpack TELemetry (SNOTEL) stations throughout the U.S. The data is collected hourly at 4 to 5 soil depths at each location. Some sites have now more than 10 years of data. Soil moisture data is statistically analyzed in conjunction with other parameters in water supply forecasting. An index has been developed and tested that calculates soil moisture for a pedon using specific detailed soil and site characteristics. This method may prove to be a more comprehensive measure of soil moisture that would be applicable to a soil specific geographic area.
Keywords: NRCS, soil moisture, SNOTEL, SCAN, water supply, forecasting

Comparisons of Spatially Distributed Hydrologic Model Outputs for the Dungeness Watershed to Field-Based Measures of Snow Water Equivalent - Massey, G.B.; Barry, D.; McDonald, S.; DeSisto, C. (79th Annual Western Snow Conference, 2011)
Many spatially distributed estimates of snow water equivalent (SWE) rely on modeling based in part on remotely sensed data. The Hybrid model is a spatially distributed streamflow forecasting model developed recently for the Dungeness Watershed of western Washington State that incorporates estimates of snow cover using NASA's MODIS. Prior to generating streamflow estimates, the Hybrid model estimates SWE across the watershed in 500m grid cells. Another NASA product, SNODAS, also estimates SWE through a combination of remote sensing and modeling. Over three winters, we monitored SWE on the ground at 12 field sites, and compared field results with those estimated by both the Hybrid and SNODAS models at two different scales (25 ha and 225 ha). Taking into account the size of the confidence intervals, only one snow course had a reasonable correlation of ground SWE with the model outputs at either scale. Both models consistently and slightly overestimated actual SWE for sites below 1400 m. Above1400 m, SNODAS consistently overestimated ground SWE, and the Hybrid model usually underestimated ground SWE, though to a lesser extent. Although the current Hybrid model performs reasonably well, more accurate point (cell) estimates of SWE within the Dungeness Watershed could provide more precise estimates of watershed-scale SWE, and, as a result, subsequent estimates of streamflow in the Dungeness River.
Keywords: Washington, snow water equivalent, SNODAS, HYBRID model, elevation effect, Dungeness Watershed

Effect of Snow Covered Area and Delayed Snowmelt on Water Quality and Reservoir Management: 2010 Turbidity Event in Hetch Hetchy Reservoir - Mazurkiewicz, A.B.; McGurk, B.J.; Tsang, M. (79th Annual Western Snow Conference, 2011)
The hydrodynamic processes in reservoirs located in snowmelt-dominated watersheds are poorly understood during snowmelt runoff. Very large storm events or unusually large spring inflows can threaten the operational and regulatory water quality goals. Turbidity levels in Hetch Hetchy are typically between 0.1 and 0.3 NTU, but storm events or unusual spring inflow events can produce inflow turbidity of over 15 NTU. This study collected turbidity and temperature data over a two-week period that included the peak inflow during an unusually large inflow event that carried a significant volume of sediment and organic debris-laden water, causing localized reservoir turbidities in excess of 10 NTU. The field data provided the information needed for operational responses and averted exceeding turbidity thresholds. An operator can adjust the elevation of the inlet used to release excess water as well as adjust the inlet elevation of water supplied to the customers. The operator can also manage reservoir storage to maintain a storage volume to dilute turbid inflow, and the timing of the release of excess water can be adjusted to control the location of mixing and control the approach of plumes of turbid water toward the water supply inlet. By combining inflow forecasts with real-time water quality data collection and dam operations, most snowmelt inflow turbidity events can be managed so that interruptions in supply due to water quality issues can be avoided.
Keywords: Tuolumne River, turbidity, reservoir operation, hydrodynamic mixing, Hetch Hetchy Reservoir

Using Quantile Regression to Model Elevation/SWE Relationships in the Olympics and Central Washington Cascades - McDonald, S.; Barry, D. (79th Annual Western Snow Conference, 2011)
Although ordinary least squares (OLS) regression is often used to develop initial models for elevation/snow water equivalent (SWE) relationships in watersheds, such an approach cannot account for the heterogeneous variability in SWE over elevation bands common in many coastal Pacific Northwest watersheds. This is particularly problematic in attempting to model middle-elevation SWE in watersheds affected by winter rain-on-snow events. Scatterplots of this relationship often show a distinctive fan-shaped pattern that widens as elevation increases, implying that there is not a single rate of change in SWE by elevation. Thus, the use of an OLS regression in models or trend assessment could provide severely misleading estimates of SWE in middle elevation areas where no field data are collected. We compare OLS and quantile regression-based models of SWE by elevation based on four snow seasons of field assessment for the Dungeness Watershed of western Washington State, as well as for snow courses and SNOTEL sites in the Olympic Mountains and central Washington Cascades. In both cases, quantile regression better accounts for the observed data than does the typical OLS approach.
Keywords: Washington Cascades, snow water equivalent, quartile regression, watershed elevation, least squares regression, Dungeness Watershed

Application of a Wireless Sensor Network for Distributed Snow Water Equivalence Estimation - Moeser, C.D.; Walker, M.J.; Skalka, C.; Frolik, J. (79th Annual Western Snow Conference, 2011)
Snow accumulated in mountainous areas is the source of water supply for much of the western United States. Estimates of the expected amounts of annual discharge in rivers are based on snow water equivalence (SWE) measurements and regression models that have climate stability as an underlying assumption. The current data collection network for SWE provides sparse areal coverage. Inexpensive wireless sensor networks and simple estimation techniques could be used to extend the areal coverage of snow data to improve spatial resolution. We report results of deployment of a prototype wireless sensor network, Snowcloud, at the Sagehen Creek, CA experimental field station. The network reported snow depth and temperature from January-May, 2010. A simple estimate of SWE at each node was based on the assumption of stability of the ratio SWE/SD and predicted SWE with reasonable accuracy (average difference of +1.0 cm (0.4 in), standard deviation = 3.0 cm (1.2 in)). Regression analysis indicated significant associations (P<.05) between SWE and % canopy closure to the north, weekly total incoming solar radiation and monthly average temperature. These results indicate that wireless sensor networks measuring SD can be used to extend information from snow measurement sites accurately to give estimates of water availability in snowpack.
Keywords: Sagehen Creek, wireless network, snow water equivalent, snow sensor, snow, snow depth, areal estimation

What Lies Beneath? Comparing MODIS Fractional Snow Covered Area Against Ground-Based Observations Under Forest Canopies and in Meadows of the Sierra Nevada - Mark S. Raleigh; Karl Rittger; Jessica D. Lundquist (Western Snow Conference, 2011)
Field observations are required to understand the potential errors in remotely sensed snow cover in forested areas . . .

Topographic Distribution of Snow Water Equivalent in the Sierra Nevada - Rittger, K.; Kahl, A.; Dozier, J. (79th Annual Western Snow Conference, 2011)
Water supply forecasts in the Sierra Nevada using ground-based measurements of snow water equivalent (SWE) are uncertain because neither point measurements nor transects adequately explain spatial or temporal variability in mountainous terrain. To address this problem, we combine satellite-based retrievals of fractional snow cover in 2006 with energy balance calculations to reconstruct the SWE values throughout the melt season. Model estimates when compared to snow pillows at maximum accumulation are unbiased and have an RMS error of 297 to 417 mm. We compare this retrospective calculation of distributed SWE with two real-time models: (i) interpolation from pillows, courses, and satellite snow cover, and (ii) the Snow Data Assimilation System (SNODAS). The interpolation and SNODAS models show complete melt out more than a month earlier than reconstruction, and their total SWE volumes are 68% and 87% of the reconstructed volume. At elevations below 1500 m, the reconstruction model has less total SWE because of early season melt. Above 3000 m, the reconstruction shows more SWE than the real time models, which depend on surface measurements that do not sample the higher elevations. The results indicate that spatial patterns from the reconstruction could improve estimates of snow accumulation and duration.
Keywords: SNODAS, snow-covered area, snow water equivalent, energy balance, MODIS

Exploring the Potential for a Fused Landsat-MODIS Snow Covered Area Product - Selkowitz, D. (79th Annual Western Snow Conference, 2011)
Results from nine 3 x 3 km study areas in the Rocky Mountains of Colorado, USA demonstrate there is potential for using sporadically acquired Landsat images in combination with daily coarse resolution fractional snow covered area (SCA) images to produce daily high resolution binary SCA images. The results also highlight several challenges to implementing this type of approach. The approach described here consistently yields accurate results in locations with persistent winter and spring snow cover where ten or more partially snow covered images are available to populate the image database, but is less successful in areas with shallower or more ephemeral snow covers or when fewer images are available to populate the image database. This work represents a first step towards developing an algorithm to combine Landsat and MODIS data to produce daily 30 m resolution binary SCA images. Further research should focus on testing the accuracy of this approach across a range of landscape types and snow cover regimes, developing methods to improve prediction accuracy when snow cover is nearly complete or nearly absent, and developing methods to compensate for the effects of canopy cover on SCA retrievals.
Keywords: Rocky Mountains, Colorado, Landsat, MODIS, snow covered area, remote sensing

Use of Radar for Spatial Snow Mapping: Implications for Water Supply Forecasts - Valsiloff, S.; Busto, J.; Arthur, A. (79th Annual Western Snow Conference, 2011)
Water supply forecasts in the West rely largely on data from over 700 SNOw TELemetry (SNOTEL) sites in the Western United States. Forecast methodology is based on 30-yr regression periods using SNOTEL and measured run-off. However, SNOTEL data represent point values and are rarely sufficiently clustered to depict the true 3-dimensional spatial distribution of snowfall. Furthermore, many headwaters basins do not have SNOTEL sites. Thus the lack of observations can result in large uncertainties in the forecasts. This paper presents a case study from a gap-filling radar project that targeted the San Juan Mountains in Southwest Colorado. For the Animas River Basin the additional radar observed a 10-fold increase in the snow water equivalent compared to surrounding NEXRAD radars. In addition the radar depicted the spatial distribution of precipitation. While the location of the radar was not optimal, radar quantitative precipitation estimates were very similar to SNOTEL precipitation amounts at most SNOTEL locations.
Keywords: Radar, SNOTEL, snowpack assessment, runoff forecasting, San Juan Mountains

Supplementing Sparse Observations of Temperature and Precipitation with a High-Resolution Atmospheric Model - Wayand, N.; Lundquist, J.; Hughes, M.; Hamlet, A. (79th Annual Western Snow Conference, 2011)
The spatial scarcity of meteorological observations represents a significant challenge for distributed hydrological modelers. Mesoscale models can provide a physically-based approach to supplement surface observations over high-elevation terrain. The heavily instrumented North Fork American River basin in California offers an optimal study location to verify mesoscale model output. Gridded 6km surface temperature and precipitation were obtained from the Weather and Research Forecasting (WRF) model, which uses lateral boundary conditions from the North American Regional Reanalysis. Results indicate that during the wet season, the WRF model was shown to well represent the inter-annual variability of the large scale temperature lapse rate and the orographic gradient of precipitation. Errors in the WRF model's temperature and precipitation were of a similar magnitude to those errors using a low-elevations station coupled to a standard lapse rate and Precipitation Regression on Independent Slopes Method (PRISM). A distributed hydrological study to evaluate if the WRF based forcing improves simulated snowpack and streamflow remains as future work.
Keywords: Mesoscale, distributed, hydrology, lapse rate, orographic precipitation gradient, PRISM, American River

Performance Analysis of GMON3 Snow Water Equivalency Sensor - Wright, M.; Kavanaugh, J.; Labine, C. (79th Annual Western Snow Conference, 2011)
This report evaluates the performance of the GMON3 Snow Water Equivalency (SWE) sensor developed by Hydro Québec in collaboration with Campbell Scientific Canada Corporation. The GMON3 determines SWE by measuring the attenuation by the snowpack of naturally emitted terrestrial gamma radiation from the soil. This provides a non-contact technique for determining SWE that is effective with any type of snow or ice cover and whose performance is not affected by adverse weather conditions. Field testing of the GMON3 was carried out at Sunshine Village, Alberta from 2008-2011 and at the SNOTEL Tony Grove Ranger Station, Utah from 2009-2010. The GMON3 values were compared to other sensors, which produce SWE either directly or indirectly: snow pillow, precipitation gauge, snow depth sensor, and manual SWE values from snow course measurements. Strong agreement is shown both qualitatively and quantitatively between all automated methods of SWE: GMON3, snow pillow, and precipitation gauge. Statistically, all automated methods show correlations of 0.99 over the entire season and up to peak periods. Monthly snow course measurements were found to be the least reliable method for measuring SWE. Analysis of the GMON3 suggests that it provides comparable, if not better, SWE accuracy to the snow pillow and precipitation gauge, while eliminating the disadvantages associated with both of these techniques.
Keywords: Alberta, snow water equivalent, SWE, GMON3, snow pillow, precipitation gauge, snow course, SNOTEL