HR: 13:45h
AN: A33B-02    [Abstracts]
TI: Prediction of Tropical Atlantic SST Using a Markov Model Trained Upon NCEP's Global Ocean Data Assimilation System
AU: * Xue, Y
EM: yan.xue@noaa.gov
AF: Yan Xue, Climate Prediction Center, NCEP/NOAA 5200 Auth Road, Room 605, Camp Springs, MD 20746 United States
AB: Both statistical and numerical models have been used to predict the Tropical Atlantic SST. However, the forecast skill of the Tropical Atlantic SST is quite poor, partially due to weak signal and complexity of the underling physical processes. Diagnostic studies on Tropical Atlantic Variability largely relate atmospheric circulation patterns and precipitation anomalies with SST anomalies in the Tropical Atlantic. The multivariate EOF analysis by Ruiz-Barradas et al. (2000) suggests that the Tropical Atlantic SST is not only associated to precipitation and surface wind stress but also to subsurface ocean temperature. We will use the ocean reanalysis for 1997-2004 produced with the NCEP's global ocean data assimilation system (GODAS) to search for coupled modes of atmosphere-ocean interaction in the tropical Atlantic and to study impacts from remote forcings such as ENSO and NAO. A prediction system will be developed with the coupled modes using the Markov model approach (Xue et al. 2000). The hindcast skill will be cross-validated and compared with that of the NCEP's new Climate Forecast System (CFS). The goal is to extract oceanic predictors within GODAS and to use them to improve the prediction skill of SST and precipitation in the tropical Atlantic where the forecast skill of numerical models is still poor.
DE: 3339 Ocean/atmosphere interactions (0312, 4504)
DE: 4231 Equatorial oceanography
DE: 9325 Atlantic Ocean
SC: Atmospheric Sciences [A]
MN: 2005 Joint Assembly