Extraseasonal ensemble numerical predictions of winter climate over China

Using the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM) under the Chinese Academy of Sciences, 30-year extraseasonal short-term ensemble hincast of winter climate is performed, with integrations starting from annual autumn during 1969—1998. Winter climate predictability over China is then evaluated for the first time. It follows that the predictability is higher in tropics than in extratropics. Also, it is higher over ocean compared with land, especially for surface air temperature. With height increasing in troposphere, the predictability of geopotential height slightly changes zonally, but for weakening of band-ship distribution and dropping near the date line. Of all analyzed variables, the prediction skill of air temperature and geopotential height (precipitation) is the highest (smallest). In addition, the predictability of winter climate over China and even East Asia enhances obviously during ENSO cycle, especially during La Nia phase. Simulation comparison against verifying analysis for surface temperature anomaly exhibits the model抯 skill in predicting surface temperature抯 interannual variation trend in winter.

Extraseasonal ensemble numerical predictions of winter climate over China

Using the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM) under the Chinese Academy of Sciences, 30-year extraseasonal short-term ensemble hincast of winter climate is performed, with integrations starting from annual autumn during 1969-1998. Winter climate predictability over China is then evaluated for the first time. It follows that the predictability is higher in tropics than in extratropics. Also, it is higher over ocean compared with land,especially for surface air temperature. With height increasing in troposphere, the predictability of geopotential height slightly changes zonally, but for weakening of band-ship distribution and dropping near the date line. Of all analyzed variables, the prediction skill of air temperature and geopotential height (precipitation) is the highest (smallest). In addition, the predictability of winter climate over China and even East Asia enhances obviously during ENSO cycle, especially during La Nina phase. Simulation comparison against verifying analysis for surface temperature anomaly exhibits the model's skill in predicting surface temperature's interannual variation trend in winter.