HR: 0800h
AN: H21F-1098    [Abstracts]
TI: Impact Of Initial Soil Wetness On Seasonal Climate Prediction
AU: * Sun, L
EM: sun@iri.columbia.edu
AF: International Research Institute for Climate Prediction, Columbia University, 61 Route 9W, PO Box 1000 231 Monell Building, Palisades, NY 10964 United States
AU: Li, H
EM: lhl@iri.columbia.edu
AF: International Research Institute for Climate Prediction, Columbia University, 61 Route 9W, PO Box 1000 231 Monell Building, Palisades, NY 10964 United States
AB: This study investigates the importance of initial soil wetness in seasonal climate predictions with ECHAM4.5 AGCM (T42). Three experiments are performed, each consisting of five ensembles of AGCM integrations from February to May 1979-1998. In the first experiment, all ensembles are initialized with NCEP reanalysis-2 soil wetness data set, and use monthly varying climatological SSTs. In the second experiment, all ensembles are initialized with model climatological soil wetness, and use observed SSTs. In the third experiment, all ensembles are initialized with NCEP reanalysis-2 soil wetness data set, and use observed SSTs. After initialization, the AGCM predicts the evolution of the soil wetness fields in all experiments. The contribution of both SSTs and initial soil wetness to the climate variability over East Africa during March-April-May season (i.e., long rains) is examined. Both SST forcing and initial soil wetness anomalies exert some influence over East Africa. But each forcing alone is not strong enough to capture the observed climate variability. With both forcings in the AGCM, the model can reproduce the observed atmospheric circulation. The results suggest that seasonal atmospheric prediction over East Africa could be enhanced by using a realistic initial state of soil wetness.
DE: 3322 Land/atmosphere interactions
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting