Data Spotlight: Projecting Alaska Snowpack Response to Climate Change

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Snow: More than just a Weather Phenomena

Snow Telemetry and snowcourse sites used in this study, 13 Alaska climate divisions

Figure 1. Snow Telemetry (SNOTEL, 21 total) and snowcourse sites (170 total) used in this study, 13 Alaska climate divisions (black boundaries), and 1970–1999 historical snowfall equivalent (SFE).

(Public domain.)

Snow is an iconic and integral part of the Alaskan landscape, serving many functions to both the people and wildlife that live there. Snow provides crucial habitat for species such as the native Alaskan snowshoe hare, wolverine, and lynx, and plant life is affected by the timing of the onset and end of the snow season. Glaciers, which are the result of centuries of snow accumulation and compaction, harbor snowfields that melt later than other snow and contribute to streamflow important to resident and migratory fish. Local hydroelectric power systems, recreation-seekers, and transportation infrastructure all rely on accurate predictions of snowfall.

Yet, warmer temperatures are affecting snowpack (snow on the ground that persists until it melts in spring) even in places where precipitation appears to be increasing. Therefore, better understanding the response of snowpack to climate change is critical for Alaskan communities and managers of wildlife in the state. The need for statewide and fine scale snowpack projections was addressed by the Alaska CASC-funded project “Alaska Snowpack Response to Climate Change: Statewide Snowfall Equivalent and Snowpack Water Scenarios”. Led by Alaska CASC research ecologist Jeremy Littell and co-investigators Stephanie McAfee (University of Nevada, Reno) and Gregory Hayward (U.S. Forest Service), the research teamsought to develop snowpack projections for the coming century to inform Alaska’s resource managers of the potential changes to ecosystem services ranging from winter sports to freshwater salmon habitat.

About the Data

Term Directory:

  • CMIP5: Coupled Model Intercomparison Project Phase 5
  • CRU: Climate Research Unit
  • GCM: Global Climate Model
  • PRISM: Parameter-elevation Regressions on Independent Slopes Model
  • PSF: projected snow day fraction; the projected fraction of days with precipitation falling as snow
  • RCP: representative concentration pathway; greenhouse gas concentration trajectory adopted by the Intergovernmental Panel on Climate Change
  • SF: snow day fractions, the fraction of total precipitation that falls as snow
  • SFE: snowfall equivalent; the liquid water equivalent of newly fallen snow
  • SFE:P: snowfall equivalent to precipitation
  • SNOTEL: Snow Telemetry : a remote backcountry weather station that measures snow and transmits the data wirelessly. These sites are primarily focused on measuring snow depth and the amount of water contained in the snow
  • SWE: snow water equivalent; the amount of liquid that would be present if you melted a column of snow
  • TS: Time Series

 Methods Summary

Researchers analyzed historical downscaled decadal average monthly SFE and downscaled estimates of decadal average monthly SF for each month of the snow season (October-March) from 1900 to 2009. The resulting decadally averaged monthly values were based on high resolution gridded datasets downscaled to the PRISM 1971-2000 climatology model. The downscaled historical and future snow products were summarized for Alaska’s 13 climate divisions, each containing hundreds to a thousand watersheds (figure 1). Assumptions for the modeled SWE approximations and historical decadal average SWE observations were validated using snowcourse and SNOTEL sites. These data were primarily made available by the Scenarios Network for Alaska and Arctic Planning (SNAP) program.

The historical downscaled data were then compared to downscaled projections of decadal monthly SFE and decadal average monthly SF from 2010 through 2099. Projected PSF, SFE, and SFE:P were based on bias-corrected statistically downscaled projections of CMIP5 GCM temperature and precipitation data. To provide a range of future snow scenarios for Alaska, the researchers calculated changes in projected SF, SFE, and SFE:P for 2040–2069 and 2070–2099, relative to a historical period of 1970–1999 CRU TS 3.1 for the 5 GCMs under pathways consistent with intermediate and high representative concentration pathways for greenhouse gases. The projected change in SFE for all 5 GCMs under the RCP 4.5 and 8.5 scenario can be found in figure 2. The USGS repository houses several datasets related to the fraction of precipitation days that are snowy (vs. rainy) and the amount of precipitation that likely falls as snow across Alaska. Both historical and projected downscaled data are available at 771 x 771 m spatial resolution. 

Access the Data

  • Download the data and learn more about the project here.
  • Read a quick snapshot of the data here.

Potential Data Applications

Using these scenarios, Little et al. (2018) showed that the area of Alaska considered snow dominant is projected to decrease under all scenarios, while transitional and rain-dominated watersheds are projected to increase. Projected changes during the months of October – March for projected snow fraction, snowfall equivalent, and snowfall equivalent to precipitation fractions (SFE:P) for Alaska indicate a universal decrease in the length of the snow season. However, the April 1 SFE:P and snowfall equivalent projected indicate a large decrease in the snow season in southern Alaska and at lower elevations and some coastal regions, but slight increases at higher elevations in the high latitudes, where precipitation is projected to still fall as snow.  

Published results using this model can be found here.

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