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

cloud cover and darkness at a resolution better than 10 m,which can resolve the hill-slope scale accounting for theNyquist requirement (~25 m), DESDynI could provideobservations crucial for an array of hydrological scienceresearch and applications. [1] National Research Council.2007. Earth Science and Applications from Space: NationalImperatives for the Next Decade and Beyond. The NationalAcademies Press, Washington, D.C.Rudiger, ChristophSMOS Soil Moisture Validation in AustraliaRudiger, Christoph 1 ; Monerris, Alessandra 1 ; Mialon,Arnaud 2 ; Olivier, Merlin 2 ; Walker, Jeffrey P. 1 ; Kerr, Yann H. 2 ;Kim, Edward J. 31. Dept. of Civil Engineering, Monash University, Clayton,VIC, Australia2. Biospheric Processes, Centre d’Etudes Spatiales de laBiosphère (Cesbio), Toulouse, France3. Hydrospheric and Biospheric Sciences Laboratory, NASAGoddard Space Flight Center, Greenbelt, MD, USAFor the validation of the European Space Agency-ledSoil Moisture and Ocean Salinity (SMOS) Level 2 soilmoisture product two extensive field campaigns wereconducted in the Australian summer (18 January to 21February) and winter (8-23 September) periods of 2010.Such extensive field campaigns including detailed in-situand airborne observations are required due to the newdesign of the SMOS satellite being a 2-dimensionalinterferometric radiometer and its use of a previouslyunderutilized microwave frequency band (L-band at1.4GHz). The Australian Airborne Cal/val Experiments forSMOS (AACES) were undertaken in south-eastern Australia,across the catchment of the Murrumbidgee River, a tributaryof the Murray-Darling basin. The climatological andhydrological conditions throughout the catchment rangefrom flat, semi-arid regions in the west to alpine andtemperate in the central and eastern reaches. This varietymakes the Murrumbidgee River catchment particularly wellsuited for such large scale studies. The study area covered atotal area of 50,000km2 with 20 focus farms distributedacross the catchment in which high-resolution in-situmeasurements were taken. Furthermore, the OzNetmonitoring network consisting of over 60 stations, includingsoil temperature and soil moisture sensors, is located withinthe catchment, complementing the data collection efforts byproviding long-term observations. During the campaignsextensive brightness temperature data sets were collectedusing an airborne L-band radiometer, while ground teamswere deployed to the focus farms to collect in-situ data.Those data sets are used in the present study to producelarge scale soil moisture maps, using the standardparameterization of the L-band Microwave Emission of theBiosphere (L-MEB) model, which forms part of theoperational soil moisture retrieval processor of SMOS. Thesubsequent comparison of those large scale maps, as well asthe station time series show a systematic dry bias in theSMOS retrieval. The magnitude of this bias varies betweenthe regions and is likely related to the varying surface128conditions. As the spatial resolution of SMOS is too low forthe agricultural purposes, SMOS soil moisture data werealso disaggregated, applying an approach based on the asemi-empirical soil evaporative efficiency model, and a firstorder Taylor series expansion around the field-mean soilmoisture. While the bias is well preserved, promising resultsare obtained when comparing the disaggregated productwith aggregated in-situ measurements of the focus farms,with retrieval errors from 0.02 to 0.1 m3 m-3, which issimilar to the errors found in the large scale products. Thetwo studies performed highlight the value SMOS can have invarious applications. In particular, a further expectedimprovement of the retrieval algorithm should allow a soilmoisture product close to the design accuracy of SMOS of0.04 m3 m-3.Rui, HualanNLDAS Views of North American 2011 ExtremeEventsRui, Hualan 1, 3 ; Teng, William 1, 4 ; Vollmer, Bruce 1 ; Mocko,David 2, 5 ; Lei, Guang-Dih 1, 31. GES DISC, GSFC NASA, Greenbelt, MD, USA2. Hydrological Sciences Laboratory, GSFC NASA,Greenbelt, MD, USA3. ADNET Systems, Inc., Rockville, MD, USA4. Wyle Information Systems, Inc., McLean, VA, USA5. SAIC, Beltsville, MD, USA2011 was marked as one of the most extreme years inrecent history. Over the course of the year, weather-relatedextreme events, such as floods, heat waves, blizzards,tornadoes, and wildfires, caused tremendous loss of humanlife and property. Many research projects have focused onacquiring observational and modeling data and revealinglinkages between the intensity and frequency of extremeevents, global water and energy cycle, and global climatechange. However, drawing definite conclusions is still achallenge. The North American Land Data AssimilationSystem (NLDAS, http://ldas.gsfc.nasa.gov/nldas/) data, withhigh spatial and temporal resolutions (0.125° x 0.125°,hourly) and various water- and energy-related variables(precipitation, soil moisture, evapotranspiration, latent heat,etc.) is an excellent data source for supporting water andenergy cycle investigations. NLDAS can also provide data forcase studies of extreme events. This presentation illustratessome extreme events from 2011 in North America, includingHurricane Irene, Tropical Storm Lee, the July heat wave, andthe February blizzard, all utilizing NLDAS data.Precipitation and soil moisture fields will be shown for thetwo East Coast tropical storm events, temperatures will beshown for the heat wave event, and snow cover and snowdepth will be shown for the winter blizzard event. Theseevents are presented in the context of the 30-plus yearclimatology of NLDAS. NLDAS is a collaboration projectamong several groups (NOAA/NCEP/EMC, NASA/GSFC,Princeton University, University of Washington,NOAA/OHD, and NOAA/NCEP/CPC) and is a core projectof NOAA/MAPP. To date, NLDAS, with satellite- and