HR: 17:15h
AN: GC44A-06 INVITED     [Abstracts]
TI: Application of a Satellite Precipitation Product for Snow Modeling and Hydrologic Forecasting
AU: * Franz, K J
EM: franzk@uci.edu
AF: University of California, Irvine, Civil and Environmental Engineering, E/4130 Engieering Gateway, Irvine, CA 92697 United States
AU: Hogue, T S
EM: thogue@seas.ucla.edu
AF: University of California, Los Angeles, 5732C Boelter Hall, Civil and Environmental Engineering, Los Angeles, CA 90095 United States
AU: Sorooshian, S
EM: soroosh@uci.edu
AF: University of California, Irvine, Civil and Environmental Engineering, E/4130 Engieering Gateway, Irvine, CA 92697 United States
AB: Satellite-based observations of hydroclimatological variables have been evolving but have yet to see any widespread use in operational hydrology. Reasons for this may be because acquisition and processing time hinders the efficient use of the data, many operational models have not been developed to take advantage of remotely sensed observations, or the value in using these products for hydrologic prediction is not yet fully understood. Satellites can provide observations in areas where ground-based collection is impossible or too expensive and makes them a potentially vital source of information for hydrologic modeling. Model states at the beginning of a forecast period dominate the quality of springtime forecasts for snow-dominated regions because of the influence of snowpack on future streamflow. In basins where snowpack observations are unavailable or inadequate for use in state adjustments, proper model input data is important for maintaining accurate model states. This study explores the potential uses for the PERSIANN (Precipitation Estimation from Remotely Sensed Information Using Neural Networks) product in operational environments. The data is used to drive two snow models of varying complexity during the spring streamflow forecasting season on a basin in the Western US. Resulting snow model states and streamflow are evaluated and the likely benefits of using the satellite-based precipitation products are assessed. This study is a continuation of a project investigating the use of physically-based models and new observational products in hydrologic forecasting. The long-term objective of the project is to bring new science and technology into operations with the goal of improving hydrologic predictions.
DE: 0798 Modeling
DE: 1816 Estimation and forecasting
DE: 1847 Modeling
DE: 1855 Remote sensing (1640)
SC: Global Climate Change [GC]
MN: Fall Meeting 2005