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