11:00 AM - 11:15 AM
[ACG32-07] Improved seasonal prediction for tropical and subtropical interannual variability using an atmospheric nudging scheme
Keywords:seasonal prediction, interannual variability, atmospheric initialization
Improvements in a seasonal prediction system due to an atmospheric initialization by an atmospheric nudging scheme were evaluated using hindcast experiments. The seasonal prediction system originally employed only sea surface temperature (SST) nudging scheme. 9 climate indices were chosen and the prediction skills were evaluated. The results show that the atmospheric initialization slightly deteriorated El Niño Southern Oscillation (ENSO) prediction, but improved the prediction skill for almost all other climate indices, locating in tropics and subtropics. Further analyses revealed that the prediction skill improvements were related to improvements in the sea level pressure (SLP) prediction. When the SLP prediction was improved, coastal upwelling (downwelling) or radiative warming (cooling) was also improved through the atmospheric variability, resulting in a better ocean forcing. It was also found that the improvements due to the atmospheric initialization (atmospheric nudging) strongly appeared in the midlatitude including subtropical regions, and the regions were found to be atmospheric-feedback-dominant regions. In the regions, SST was dominated by atmospheric feedback, thus the atmospheric initialization by the nudging scheme worked well and improved the prediction skill there. However, in the tropics, the atmospheric variability was dominated by SST (SST-feedback-dominant), so the atmospheric initialization resulted in worse atmospheric variability since SST feedback was partly neglected, and it deteriorated the prediction skill. Since the influence of dominance of atmosphere or SST on prediction skill is considered general, the results of this study suggest that the present finding can be applicable for other seasonal prediction systems.