Department of Civil and Environmental Engineering
University of Washington
Research

Forests and Snow

Intermittent Snow and Process Dynamics

Snow Surface Temperature and Snow Depth in the Tuolumne Watershed

OLYMPEX


Orographic Precipitation

Mapping temperature in complex terrain

Spatial patterns of snow-fed streamflow

Rain vs. Snow

How meadow ecology relates to snow and climate

Intercomparison of Meteorological Forcing Data from Empirical and Mesoscale Model Sources

Silvicliture to maximize snow retention

Remote sensing of radiation to improve snow modeling

Wildflowers and Snow

Wildflowers on Mt. Rainier:

The timing of key life events like reproduction (i.e. phenology) is tightly linked to climate. For example, alpine wildflowers emerge and flower within a few weeks of snow disappearance, and complete their life-cycles before the onset of the first snow in fall. Because annual variability in snow disappearance is large, the timing of seasonal wildflower displays also varies annually, influencing visitation and staffing needs within parks. Additionally, as climate change causes earlier snow disappearance, wildflowers need to shift their phenology to match this earlier climate window. Thus, resource managers and conservation biologists need the ability to seasonally forecast snow disappearance and wildflower phenology as well as monitor their annual trends in the long-term to better manage diverse wildflower meadows of the high mountains.

To address these issues, we are currently working with Dr. Janneke Hille Ris Lambers in the Biology Department at the University of Washington on a NASA-sponsored project to combine MODIS-based maps of snow covered area (SCA), citizen science observations and models to develop decision-making tools at Mt. Rainier National Park (Washington). Specifically, we are developing and validating snow models driven by MODIS SCA and daily observations of temperature, precipitation and snow (from SNOTEL climate station) that generate spatially explicit forecasts of snow duration months prior to snow disappearance. Next, we are using pictures of blooming wildflowers from photo-sharing websites to develop phenological forecasts driven by snow disappearance forecasts. Phenological models are compared to data from an existing citizen science program, Meadowatch. Operationally, these estimates will 1) help managers plan where and when trail maintenance, conservation/restoration activities, and monitoring can occur, 2) allow visitors to better plan trips to view and photograph wildflowers, and eventually, 3) help resource managers identify the earliest climatic and biological signals of climate change.

Our current forecast is available here.

You can help update our forecast with your own observations by participating in Meadowatch anywhere near Mt. Rainier National Park.