HR: 11:05h
AN: H22A-04    [Abstracts]
TI: OPERATIONAL STREAMFLOW FORECASTS DEVELOPMENT USING GCM PREDICTED PRECIPITATION FIELDS
AU: * Arumugam, S
EM: sankar@iri.columbia.edu
AF: Sankar Arumugam, International Research Institute for Climate Prediction, Columbia University, Palisades, NY 10964-8000 United States
AU: Lall, U
EM: ula2@columbia.edu
AF: Upmanu Lall, Department of Earth and Environmental Engineering, Columbia University, New York, NY 10027 United States
AB: Monthly updates of streamflow forecasts are required for deriving reservoir operation strategies as well as for quantifying surplus and shortfall for the allocated water contracts. In this study, an operational streamflow forecasts are developed using Atmospheric General Circulation Models (AGCM) predicted precipitation for managing the Angat Reservoir System, Philippines. The methodology employs principal components regression (PCR) for downscaling the AGCM predicted precipitation fields to monthly streamflow forecasts. The performance of this downscaling approach is analyzed with AGCM being forced using the observed sea surface temperature (SST) conditions as well under persisted SST conditions. The ability of downscaled streamflow forecasts in explaining the intraseasonal variability is also explored. Conditional distribution of streamflows obtained from the PCR downscaling approach is also compared with a simple, semi-parametric resampling algorithm that obtains ensembles of streamflow forecasts by identifying similar conditions in that season's climatic predictors state space.
DE: 3354 Precipitation (1854)
DE: 1833 Hydroclimatology
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting