Abstract

A dynamical downscaling system for seasonal forecast has been constructed based on a regional climate model, and its predictability was investigated for 10 years' wintertime (December-January-February; DJF) climatology in East Asia. Initial and lateral boundary conditions were obtained from the operational seasonal forecasting data, which are realtime output of the Global Data Assimilation and Prediction System (GDAPS) at Korea Meteorological Administration (KMA). Sea surface temperature was also obtained from the operational forecasts, i.e., KMA El-Nino and Global Sea Surface Temperature Forecast System. In order to determine the better configuration of the regional climate model for East Asian regions, two sensitivity experiments were carried out for one winter season (97/98 DJF): One is for the topography blending and the other is for the cumulus parameterization scheme. After determining the proper configuration, the predictability of the regional forecasting system was validated with respect to 850 hPa temperature and precipitation. The results showed that mean fields error and other verification statistics were generally decreased compared to GDAPS, most evident in 500 hPa geopotential heights. These improved simulation affected season prediction, and then HSS was better 36% and 11% about 850 hPa temperature and precipitation, respectively.

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