C32A-04:
The NASA Airborne Snow Observatory: Demonstration Mission 2

Wednesday, 17 December 2014: 11:05 AM
Thomas H Painter1, Daniel F Berisford2, Joseph W Boardman3, Kat Bormann2, Jeffrey S Deems4, Frank Gehrke5, Jason Horn1, Danny G Marks6, Chris A Mattmann2, Bruce J McGurk7, Paul Ramirez1, Megan Richardson1, McKenzie Skiles8, Adam H Winstral9 and Paul Zimdars2, (1)Jet Propulsion Laboratory, Pasadena, CA, United States, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (3)Analytical Imaging and Geophysics, Boulder, CO, United States, (4)University of Colorado, Boulder, CO, United States, (5)State of California, Sacramento, CA, United States, (6)USDA Agriculture Research Serv, Boise, ID, United States, (7)Self Employed, McGurk Hydrologic, Washington, DC, United States, (8)University of California Los Angeles, Los Angeles, CA, United States, (9)USDA-ARS, Boise, ID, United States
Abstract:
The NASA Jet Propulsion Laboratory developed the Airborne Snow Observatory (ASO), an imaging spectrometer and imaging LiDAR system, to quantify snow water equivalent and snow albedo, provide unprecedented knowledge of snow properties, and provide complete, robust inputs to snowmelt runoff models, water management models, and systems of the future. This talk presents results from the second Demonstration Mission that occurred during the intense California drought of spring 2014.

With the acquisition of the new cutting edge lidar system, ASO was able to fly higher and as such acquire complete basin coverage for the Tuolumne, Merced, Lakes, and South Fork of Kings River Basins in the California Sierra Nevada. Despite the intensity of the California drought, several snowfalls occurred during the Demonstration Mission and we were able to uniquely map snowfall distribution, providing unprecedented capability to test our understanding of orographics and redistribution of snowfall.

A new snow density model and analysis were integrated into the ASO data system. Despite a > 4-fold increase in data volume from the new lidar, the landing-to-data delivery remained at < 24 hrs. ASO SWE and albedo data are assimilated into models of varying complexity and results presented here. We use the ASO data in the Sierra Nevada to evaluate SWE simulations from the NWS SNODAS and SWE reconstruction models. Finally, the ASO data were watched carefully during the drought, suggesting that the Hetch Hetchy reservoir original infrastructure’s forecast of falling well short of fill would be biased low and that the reservoir would come close to filling.