The seasonal snowpack and liquid water equivalent contained in it (SWE) is of vital concern to water managers, because it is a primary source of water for use throughout the dry portions of the year in the mountainous West. Thus it is essential that both snow level and SWE can be characterized accurately on a storm-by-storm basis in order to address issues of uncertainty inherent in hydrometeorological forecasting, water management, and flood control. All of this work points to a better diagnosis/understanding of precipitation characteristics associated with winter storms and can serve as a baseline by which to measure climate change. Shifts in average snow level and SWE in response to climate change can severely alter runoff and flood patterns and impact water availability throughout the year.
For hydrometeorological prediction in regions containing mountainous watersheds, the snow level is an important variable because it determines the amount of area in a basin that will receive rain versus snow during a particular storm, which controls the amount of water that is available for runoff and the potential for flooding. Observations of the melting layer are critical to hydrologic forecasting as areas with rain or snow will have different runoff responses. The altitude of the snow level during a particular event is determined by the storm characteristics and the interaction of the atmosphere with complex terrain (White et al. 2002). HMT has developed and implemented a technique to use profiling radars to automatically detect the altitude of the snow level during precipitation, and seeks to validate these radar snow level estimates through intensive field monitoring of storm events. This validation work will eventually lead to better integration of radar snow level estimates into operational forecasting.
Determination of the storm total precipitation presents another challenge to hydrometeorology forecasts in mountainous regions. Radar-based quantitative precipitation estimates (QPE) below the snow level are comparatively well understood, however QPE of snowfall are not. HMT seeks to quantify and validate QPE of snowfall through intensive monitoring of snow rate and storm totals using various techniques before, during, and after storm events. Knowing storm total snow water equivalents (SWE) can greatly enhance estimates of total seasonal snowpack.
Major sub-themes in this activity presently include:
- Snow Depth and Snow Information
- Snow Level and Freezing Level Observations