Explore projected changes in monthly Snow Water Equivalent, a common measurement of snowpack, for California.
- This chart shows monthly averages of projected Snow Water Equivalent values for the selected area on map under the RCP 4.5 scenario. The colored lines (2006 – 2100) are projections from 10 LOCA downscaled climate models selected for California.
- * These models have been selected by California state agencies as priority models for research contributing to California’s Fourth Climate Change Assessment.
- Use year sliders to get means for different time periods. The projected mean is calculated for all visible models in the chart. Use slider below the chart to zoom and pan within the chart.
If heat-trapping emissions continue unabated, more precipitation will fall as rain instead of snow, and the snow that does fall will melt earlier, reducing the Sierra Nevada spring snowpack by as much as 70 to 90 percent. How much snowpack will be lost depends in part on future precipitation patterns, the projections for which remain uncertain. However, even under wetter climate projections, the loss of snowpack would pose challenges to water managers, hamper hydropower generation, and nearly eliminate skiing and other snow-related recreational activities.
Snow Water Equivalent output from Variable Infiltration Capacity model forced by LOCA Downscaled Data
Snow Water Equivalent (SWE) projections are produced by using a land surface/hydrology model known as the Variable Infiltration Capacity (VIC) model. The VIC model uses high resolution LOCA precipitation and temperature data from Scripps Institution Of Oceanography as input to calculate SWE and a suite of additional parameters. Details are described in Pierce et al., 2016 and Pierce et al., 2014.
Snow Water Equivalent output from Variable Infiltration Capacity model forced by Gridded Historical Observed Data
Snow Water Equivalent (SWE) data are produced by using a land surface/hydrology model known as the Variable Infiltration Capacity (VIC) model forced by Livneh observed gridded data. Details are described in Livneh et al., 2015.
In order to create data layers used in this tool, we calculated monthly averages of daily values of Snow Water Equivalent for each year (1950–2100). This process was done for each of the 10 LOCA downscaled climate models selected for California, for historical and future scenarios - RCP 4.5 and RCP 8.5.