CITRIS Research Exchange - Snowcover Patterns in the Sierra Nevada from Blended Satellite & Ground-Based Networks

• September 5, 2007: 11:00am - 12:00pm
• Location: 290 Hearst Memorial Mining Building, the Maria & Dado Banatao Conference Room, UC Berkeley

Please join us for a talk on "Snowcover Patterns in the Sierra Nevada from Blended Satellite & Ground-Based Networks" by Roger Bales, Professor of Engineering, UC Merced on Sept. 5 at noon in 290 Hearst Memorial Mining Building, UC Berkeley.

 

Watch talk here.

 

Part of the CITRIS Research Exchange at UC Berkeley. The complete schedule for the fall semester is online at RE-Fall2007. As always, these talks are free, open to the public. Sponsored by Infineon Technologies.

 

Abstract:

Accurate, frequent satellite-derived snow covered area (SCA) products provide the opportunity to explore the spatial patterns of snow, as well as the impact of snow accumulation and ablation on snow distribution along elevation gradients. Blending a MODIS fractional snow cover product with interpolated point snow water equivalent (SWE) measurements and energy balance calculations yields composite maps of the spatial distribution of SWE. The transitional rain/snow zone is at about 1,500 m in the Merced and Tuolumne basins of the central Sierra Nevada, with 40% of the elevation between 2,100-2,700 m. Spatial maps of SWE highlight elevation bands that contribute significantly to snowmelt across the basin, as well as those elevation bands that are susceptible to warming and thus rapid depletion of the snowcover. Using a season-long energy-balance approach it is apparent that higher elevations, up to 4,000 m and above the highest snow measurement site (about 2,700 m) contribute a disproportional share of the basin snowmelt relative to elevations from 2,700 m down to the snowline. These results also underscore deficiencies in the current measurement network and provide the impetus for designing of an adequate measurement network along elevational gradients. Ongoing deployment of snow and water-balance instrument clusters in the Sierra Nevada are designed to overcome these deficiencies, and provide low-cost, near-real-time information on spatial snow depths.

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