Historic Average Spring Snowpack, Northern Sierra Nevada California,1971-2000

May 9, 2013 (Last modified Jun 10, 2013)
Description:
This dataset is a historic average Spring (March, April, May) snowpack, in northern Sierra Nevada California, for 1971-2000, from the California Basin Characterization Model (BCM)

Snowpack: Amount of snow accumulated per month summed annually, or if divided by 12 average monthly snowpack. This is calculated as prior month's snowpack plus snowfall minus sublimation and snow melt.

The California Basin Characterization Model (BCM) climate dataset provides historical and projected climate surfaces for the state at a 270 meter resolution. The historical data is based on 4 kilometer PRISM data, and the projected climate surfaces are based on the A2 and B1 scenarios of the PCM and GFDL GCMs. The BCM approach uses a regional water balance model based on high resolution downscaled precipitation and temperature as well as elevation, geology, and soils to produce surfaces for a wide range of variables. These variables include maximum temperature, minimum temperature, precipitation, potential evapotranspiration, runoff, recharge, climatic water deficit, actual evapotranspiration, sublimation, soil water storage, snowfall, snowpack, snowmelt, and excess water. Data is distributed as 30-year monthly summaries and 30-year water year summaries, with month-by-month data for each year available by special request.

Creator: Flint, Lorraine E. and Flint, Alan L.
Contributor: Thorne, James, and Boynton, Ryan
Publisher:  Public Interest Energy Research Program (PIER), California Energy Commission
Data Provided By:
Flint, Lorraine E. and Flint, Alan L.
Content date:
not specified
Citation:
Flint, L.E. and Flint, A.L. 2012. Downscaling future climate scenarios to fine scales for hydrologic and ecological modeling and analysis.  Ecological Processes 1:2 doi: 10.1186/2192-1709-1-2
Spatial Resolution:
270 (meter)
Contact Organization:
not specified
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Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 3.0 License.
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