This study investigates the potential to improve regional seasonal forecast for the east asia during cold season using the Global/Regional Integrated Model system(GRIMs). The GRIMs is forced by the climate Forecast system (cFs) seasonal prediction data for 25 years from 1983 to 2007.

This dynamically downscaled forecast is compared with the cFs produced by global forecast model. Results of the comparison suggest that the RcM add value in seasonal prediction application, but the improvements largely depend on location, forecast lead time, variables, and skill metrics used for evaluation. Generally, more improvements are found over the oceans for the shorter lead time. This results allow us to be cautiously optimistic about the model ability in the forecast of important climatological features as well as extreme event of precipitation and temperature in east Asia.

1. 서론

2. 연구 방법

2.1 Global/Regional Integrated Model System (GRIMs)

2.2 실험 설계

2.3 Scale-Selective Bias Correction (SSBC)

3. 연구 결과

3.1 전구 예측 자료의 검증

3.2 고해상도 예측 자료의 예측성

3.3 Spectral nudging이 계절예측에 미치는 영향

4. 요약 및 논의