HR: 1400h
AN: H53B-03    [Abstracts]
TI: Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.
AU: * Garcia, M
EM: mgarcia@hsb.gsfc.nasa.gov
AF: UMBC-GEST and NASA-GSFC Hydrological Sciences Branch, Goddard Space Flight Center Code 614.3, Greenbelt, MD 20771, United States
AU: Peters-Lidard, C D
EM: christa.peters@nasa.gov
AF: NASA-GSFC Hydrological Sciences Branch, Goddard Space Flight Center Code 614.3, Greenbelt, MD 20771, United States
AU: Eylander, J B
EM: john.eylander@afwa.af.mil
AF: HQ Air Force Weather Agency Air & Space Model Integration Branch, 106 Peacekeeper Dr. Suite 2N3, Offutt AFB, NE 68113, United States
AU: Daly, C
EM: daly@coas.oregonstate.edu
AF: PRISM Group Oregon State University, Department of Geosciences, Corvallis, OR 97330, United States
AU: Tian, Y
EM: yudong@hsb.gsfc.nasa.gov
AF: UMBC-GEST and NASA-GSFC Hydrological Sciences Branch, Goddard Space Flight Center Code 614.3, Greenbelt, MD 20771, United States
AU: Zeng, J
EM: jzeng@hsb.gsfc.nasa.gov
AF: SAIC and NASA-GSFC Hydrological Sciences Branch, Goddard Space Flight Center Code 614.3, Greenbelt, MD 20771, United States
AB: The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.
DE: 1805 Computational hydrology
DE: 1833 Hydroclimatology
DE: 1840 Hydrometeorology
DE: 1854 Precipitation (3354)
DE: 1855 Remote sensing (1640)
SC: Hydrology [H]
MN: 2007 Joint Assembly