We introduce a quality controlled observational atmospheric, snow, and soil data set from Snoqualmie Pass, Washington, USA, to enable testing of hydrometeorological and snow process representations within a rain-snow transitional climate where existing observations are sparse and limited. Continuous meteorological forcing (including air temperature, total precipitation, wind speed, specific humidity, air pressure, and short and longwave irradiance) are provided at hourly intervals for a 24 year historical period (water years 1989-2012) and at half-hourly intervals for a more recent period (water years 2013-2015), separated based on the availability of observations. The majority of missing data were filled with biasedcorrected reanalysis model values (using NLDAS). Additional observations include 40 years of snow board new snow accumulation, multiple measurements of total snow depth, and manual snow pits, while more recent years include subdaily surface temperature, snowpack drainage, soil moisture and temperature profiles, and eddy covariance-derived turbulent heat flux. This data set is ideal for testing hypotheses about energy balance, soil, and snow processes in the rain-snow transition zone. Key Points:A comprehensive atmospheric, snow, and soil data set is introduced Historical and intensive recent observations are included This data set is ideal for vetting model representation of snow processes Supporting Information:Supporting Information S1 Movie S1

Rain-on-snow events trigger immediate and delayed avalanches as liquid water penetrates the snowpack. We present results from an extreme rain-on-snow event that triggered a glide avalanche near Snoqualmie Pass, Washington, USA. Snoqualmie Pass recorded 463 cm of snowfall from 13 December 2008 to 6 January 2009. This period of snowfall was followed by a strong southwesterly tropical flow that resulted in an extreme rain-on-snow event. Sensors at Snoqualmie Pass recorded 285 mm of precipitation over a 52 hour period. Flooding, slush flows, landslides and avalanches resulted from the influx of precipitation. Snow heights decreased rapidly over the period, with settlement rates approaching 80 mm h -1 . Liquid water infiltrated and flowed through the snowpack within a few hours of the arrival of rain, yet many of the major avalanches occurred 12-30 or more hours after the onset of rain and water outflow. A glide avalanche occurred 30 hours after the onset of rain and the establishment of drainage through the snowpack. Increasing glide rates correlate with periods of rapid snow settlement. Here glide rates approached 670 mm h -1 . Although glide and settlement rates increased during periods of intense precipitation, glide failure occurred 8 hours after peak precipitation and outflow.

Low‐level cold air from eastern Washington often flows westward through mountain passes in the Washington Cascades, creating localized inversions and locally reducing climatological temperatures. The persistence of this inversion during a frontal passage can result in complex patterns of snow and rain that are difficult to predict. Yet these predictions are critical to support highway avalanche control, ski resort operations, and modeling of headwater snowpack storage. In this study we used observations of precipitation phase from a disdrometer and snow depth sensors across Snoqualmie Pass, WA, to evaluate surface‐air‐temperature‐based and mesoscale‐model‐based predictions of precipitation phase during the anomalously warm 2014–2015 winter. Correlations of phase between surface‐based methods and observations were greatly improved (r2 from 0.45 to 0.66) and frozen precipitation biases reduced (+36% to −6% of accumulated snow water equivalent) by using air temperature from a nearby higher‐elevation station, which was less impacted by low‐level inversions. Alternatively, we found a hybrid method that combines surface‐based predictions with output from the Weather Research and Forecasting mesoscale model to have improved skill (r2 = 0.61) over both parent models (r2 = 0.42 and 0.55). These results suggest that prediction of precipitation phase in mountain passes can be improved by incorporating observations or models from above the surface layer.

The Washington State Department of Transportation's (DOT) snow avalanche control program reduces winter roadway closure times and hazards to motorists. The University of Washington and the Washington State DOT evaluated small unmanned aircraft systems (UASs) as a tool to enhance this program. Because of military investment, UAS technology has dropped in cost as it has become increasingly capable and easier to operate. Commercially available UASs, which fly autonomously, can be operated off a roadway and can collect low-cost, real-time aerial imagery while also carrying payloads. This project conducted a series of test flights involving both fixed- and rotary-wing (helicopter) UASs over a roadway in mountainous terrain. The flights demonstrated that UASs can conduct snowpack and terrain surveillance and can accurately drop explosive charges such as those used to trigger controlled avalanches. The rotary-wing UAS was particularly usable because of its ability to hover, which provided a stable camera platform, and because it required minimal area to land. The reliability of UASs is a concern, and their capabilities may be challenged by mountainous terrain and weather. This problem may be reduced as UASs become either less expensive and more expendable or more reliable and all-weather capable. A major barrier to use of UASs is the need to obtain approval to fly from FAA, a process that can be time-consuming and restrictive. FAA is currently updating its plans to integrate UASs into the national airspace, and a number of technology-based solutions are being considered.