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Recent Advances in Dynamical Extra-Seasonal to Annual Climate Prediction at IAP/CAS
Recent Advances in Dynamical Extra-Seasonal to Annual Climate Prediction at IAP/CAS

Keywords: seasonal prediction,ensemble technique,ENSO prediction,soil moisture,correction method
季节预报
,土壤潮湿性,气候变化,中国,东亚季风地区

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Abstract:

Recent advances in dynamical climate prediction at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS) during the last five years have been briefly described in this paper. Firstly,the second generation of the IAP dynamical climate prediction system (IAP DCP-Ⅱ) has been described,and two sets of hindcast experiments of the summer rainfall anomalies over China for the periods of 1980-1994 with different versions of the IAP AGCM have been conducted. The comparison results show that the predictive skill of summer rainfall anomalies over China is improved with the improved IAP AGCM in which the surface albedo parameterization is modified. Furthermore, IAP DCP-Ⅱ has been applied to the real-time prediction of summer rainfall anomalies over China since 1998, and the verification results show that IAP DCP-Ⅱ can quite well capture the large scale patterns of the summer flood/drought situations over China during the last five years (1998-2002). Meanwhile, an investigation has demonstrated the importance of the atmospheric initial conditions on the seasonal climate prediction, along with studies on the influences from surface boundary conditions (e.g., land surface characteristics, sea surface temperature).Certain conclusions have been reached, such as, the initial atmospheric anomalies in spring may play an important role in the summer climate anomalies, and soil moisture anomalies in spring can also have a significant impact on the summer climate anomalies over East Asia. Finally, several practical techniques (e.g., ensemble technique, correction method, etc.), which lead to the increase of the prediction skill for summer rainfall anomalies over China, have also been illustrated. The paper concludes with a list of critical requirements needed for the further improvement of dynamical seasonal climate prediction.

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