2012 AGU Chapman Conference on Remote Sensing of the ...

Painter, Thomas H.The JPL Airborne Snow Observatory: Cutting edgetechnology for snow hydrology and watermanagementPainter, Thomas H. 1 ; Deems, Jeffrey 2 ; McGurk, Bruce 3 ;Dooley, Jennifer 1 ; Green, Robert O. 11. Jet Propulsion Laboratory, Pasadena, CA, USA2. Western Water Assessment/NSIDC, University ofColorado, Boulder, CO, USA3. McGurk Hydrologic, Orinda, CA, USASnowmelt in the western US dominates the freshwatersupply for tens of millions of people. In particular, theColorado River supplies freshwater to 27 million people inseven states and Mexico, and without the import ofsnowmelt-dominated aqueducts, the metropolitan LosAngeles area could sustain only 400 thousand of its current15 million people. In 2010, Lake Mead faced a drop to a lakelevel of 1075’, which would have triggered action underShortage Sharing agreement with interstate andinternational legal implications. The two most criticalproperties for understanding snowmelt totals and timing arethe spatial distributions of snow water equivalent (SWE) andsnow albedo. Despite their importance, these snowpackproperties are poorly quantified in the US and not at all inmost of the globe, leaving runoff models poorly constrained.Recognizing this void, we are building the Airborne SnowObservatory (ASO), an integrated imaging spectrometer andscanning lidar system, to quantify spatially coincident snowwater equivalent and snow albedo in headwaters throughoutthe Western US. The ASO will provide unprecedentedknowledge of snow properties and complete, robust inputsto water management models and decision-support systemsof the future. The ASO couples a visible through shortwaveinfrared imaging spectrometer (the Airborne Visible/InfraredImaging Spectrometer-NextGeneration, AVIRISng) with ahigh-altitude, scanning LiDAR system (Optech Gemini) on aTwin Otter aircraft. The AVIRISng will measure reflectedsolar radiance from ~5 m pixels in ~220 spectral bands from350 to 2500 nm. The LiDAR will image at 1064 nmwavelength with 4 range measurements and continuousmultipulse technology to provide highly accurate surfaceelevation maps, allowing mapping of snow depth at ~5 m aswell. The snow depth maps will then be combined with fieldand automated measurements of snow density to produceSWE maps. The first ASO Demonstration Mission (ASO-DM1) will cover the Upper Tuolumne River Basin, SierraNevada, California (City of San Francisco water supply) andthe Uncompahgre River Basin, San Juan Mountains,Colorado (Upper Colorado River Basin). The ASO willacquire snow-free data in late summer to provide thebaseline topography against which snow depth may bedetermined. The ASO will then image target basins on aweekly basis from mid winter through complete snowmelt toprovide coincident spatial distributions of snow albedo,snow depth, snow water equivalent, and dust/black carbonradiative forcing in snow. The data will be processed on thenew JPL Snow Server cluster (192 cores) and delivered to115water managers in near real time, lagged by < 24 hours. Inturn, in both basins, we will compare forecast total volumesand timing driven by current, limited data sources withthose forecasts driven by the comprehensive products fromthe ASO. The ASO-DM1 data will then be processed torefined products and delivered to the broader communityfor scientific discovery.Parajka, JurajMODIS Snow Cover Mapping Accuracy in SmallAlpine CatchmentParajka, Juraj 1 ; Holko, Ladislav 21. Institute of Hydraulic Engineering and Water ResourcesManagement, Vienna University of Technology, Vienna,Austria2. Institute of Hydrology, Slovak Academy of Sciences,Liptovsky Mikulas, SlovakiaIn the last decade, a range of MODIS snow coverproducts have been used for regional mapping of snow coverchanges. MODIS images are particularly appealing due totheir high temporal (daily) and spatial resolution. Numerousvalidation studies examined and confirmed their accuracyand consistency against other remote-sensing products andin situ climate station data. The snow cover mappingefficiency in alpine and forested regions is, however, still notwell understood. The main research questions addressed inthis contribution are: How accurate is MODIS snow covermapping in alpine forested environment? Does MODISconsistently identify snow cover beneath forest particularlyat the end of snow melt period? MODIS snow cover changesin small experimental catchment (Jalovecky creek, WesternTatra Mountains, Slovakia) will be compared against theextensive snow course measurements at open and forestedsites. It is anticipated that a decade of snow observations inwell documented experimental catchment may give moregeneral insight into the efficiency and accuracy of MODISsnow cover dataset in forested alpine regions.www.hydro.tuwien.ac.atParinussa, RobertGlobal quality assessment of active and passivemicrowave based soil moisture anomalies forimproved blendingParinussa, Robert 1, 2 ; Holmes, Thomas 2 ; Crow, Wade 2 ;Dorigo, Wouter 3 ; de Jeu, Richard 11. Hydrology and Geo-environmental sciences, VUUniversity Amsterdam, Amsterdam, Netherlands2. Hydrology and Remote Sensing Laboratory, USDA-ARS,Beltsville, MD, USA3. Institute for Photogrammetry and Remote Sensing,Vienna University of Technology, Vienna, AustriaRecently, a methodology that takes advantages of theretrieval characteristics of passive (AMSR-E) and active(ASCAT) microwave satellite soil moisture estimates wasdeveloped. Combining surface soil moisture estimates fromboth microwave sensors offers an improved product at a