HR: 0800h
AN: IN21A-0075    [Abstracts]
TI: A Novel Hydro-information System for Improving NOAA AWIPS DSS for Disaster Management
AU: Liang, Y
EM: yliang@cs.iupui.edu
AF: Department of Computer and Information Science, Purdue University School of Science, IUPUI, 723 West Michigan Street, SL 280L, Indianapolis, IN 46202, United States
AU: Adams, T
EM: Thomas.Adams@noaa.gov
AF: NOAA National Weather Service, Ohio River Forecast Center, 1901 South State Route 134, Wilmington, OH 45177, United States
AU: Liang, X
EM: xuliang@engr.pitt.edu
AF: Department of Civil and Environmental Engineering, University of Pittsburgh, 941 Benedum Hall, 3700 O'Hara St., Pittsburgh, PA 15261, United States
AU: * Teng, W
EM: william.l.teng@nasa.gov
AF: NASA Goddard Earth Sciences Data and Information Services Center, NASA Goddard Space Flight Center, Code 610.2, Greenbelt, MD 20771, United States
AU: Chiu, L
EM: lchiu@gmu.edu
AF: Center for Earth Sciences and Space Research, George Mason University, Fairfax, VA 22030, United States
AB: The U.S. National Weather Service (NWS) carries out its mission of protecting life and property from water-related disasters through improving forecast skills. The Advanced Weather Interactive Processing System (AWIPS), implemented by NWS in the 1990s, is employed to support its decision making in issuing forecasts, watches, and warnings for water-related disasters. A sub-Decision Support System (DSS) of the AWIPS is the NWS River Forecast System (NWSRFS), which is used to provide forecasts of floods and droughts. In this study, we focus on developing a novel hydro-information system to improve the forecast accuracy of the NWSRFS. In particular, our system will allow the automated flow of surface soil moisture satellite data from the Goddard Earth Sciences Data Information and Services Center (GES DISC) into NWSRFS through an extension of the Hydrological Integrated Data Environment (HIDE) system. A spatial data assimilation framework, together with the NOAH model, will then be employed to assimilate improved evapotranspiration data to be inputted into the NWSRFS to thus improve the behavior of the NWSRFS in its forecasting skills, especially for droughts, and for disaster management. Initial framework and investigations from this study will be presented and discussed.
DE: 0525 Data management
DE: 1640 Remote sensing (1855)
DE: 1818 Evapotranspiration
DE: 1866 Soil moisture
DE: 2447 Modeling and forecasting
SC: Earth and Space Science Informatics [IN]
MN: 2007 Fall Meeting