Predictability of winter rainfall in South China as demonstrated by the coupled models of ENSEMBLES
Predictability of winter rainfall in South China as demonstrated by the coupled models of ENSEMBLES
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ENSEMBLES耦合模型对华南冬季降水的可预测性
DOI：
10.1007/s00376-013-3172-2
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发表时间：
2014-05
影响因子：
5.8
通讯作者：
Lu Riyu
中科院分区：
文献类型：
--
作者：
Yang, Se-Hwan;Li Chaofan;Lu Riyu
华南冬季降水表现出较强的年际变化，约占华南冬季降水总量的一半。本研究利用1961-2006年中国南方冬季（12月- 1月- 2月；DJF）降水的五个最先进耦合模式的回顾性预报，探讨了华南冬季（12月- 1月- 2月；DJF）降水的可预测性。结果表明，ENSEMBLES模型较好地预测了华南地区降水的年际变化，观测/台站平均降水与预测/地区平均降水的相关系数为0.46。特别是华南地区的降水预报较好，冬季降水预报与观测的相关系数为0.64。此外，模式较好地捕捉了与华南降水变化相关的海温和大气环流异常的主要特征。进一步发现，根据预测DJF Niño3.4指数和ENSO-South China降水关系预测华南降水，其预测能力几乎与直接预测的预测能力相当，说明ENSO是华南降水的可预测性来源。
Winter rainfall over South China shows strong interannual variability, which accounts for about half of the total winter rainfall over South China. This study investigated the predictability of winter (December-January-February; DJF) rainfall over South China using the retrospective forecasts of five state-of-the-art coupled models included in the ENSEMBLES project for the period 1961–2006. It was found that the ENSEMBLES models predicted the interannual variation of rainfall over South China well, with the correlation coefficient between the observed/station-averaged rainfall and predicted/areaaveraged rainfall being 0.46. In particular, above-normal South China rainfall was better predicted, and the correlation coefficient between the predicted and observed anomalies was 0.64 for these wetter winters. In addition, the models captured well the main features of SST and atmospheric circulation anomalies related to South China rainfall variation in the observation. It was further found that South China rainfall, when predicted according to predicted DJF Niño3.4 index and the ENSO-South China rainfall relationship, shows a prediction skill almost as high as that directly predicted, indicating that ENSO is the source for the predictability of South China rainfall.
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影响因子：
--
作者：
Wang Lin
通讯作者：
Wang Lin
ENSO与中国东南部冬季降水的关系及其年代际变化
DOI：
10.1007/s00376-012-1248-z
发表时间：
2012-10
期刊：
Adv. Atmos. Sci.
影响因子：
--
作者：
Li Chun;Ma Hao
通讯作者：
Ma Hao
影响因子：
4.4
作者：
Chen, W;Yang, S;Huang, RH
通讯作者：
Huang, RH
影响因子：
8.9
作者：
F. Doblas-Reyes;A. Weisheimer;M. Déqué;N. Keenlyside;M. McVean;J. Murphy;P. Rogel;Doug M. Smith;T. Palmer
通讯作者：
F. Doblas-Reyes;A. Weisheimer;M. Déqué;N. Keenlyside;M. McVean;J. Murphy;P. Rogel;Doug M. Smith;T. Palmer
影响因子：
5.8
作者：
Renhe Zhang;A. Sumi;M. Kimoto
通讯作者：
Renhe Zhang;A. Sumi;M. Kimoto