Skillful seasonal predictions of winter precipitation over southern China
Skillful seasonal predictions of winter precipitation over southern China
复制标题
巧妙预测华南冬季降水季节
DOI：
10.1088/1748-9326/aa739a
复制
发表时间：
2017-07
影响因子：
6.7
通讯作者：
Eade Rosie
中科院分区：
文献类型：
--
作者：
Lu Bo;Scaife Adam A;Dunstone Nick;Smith Doug;Ren Hong Li;Liu Ying;Eade Rosie
中国南方的冬季降水量每年都有很大的变化，这可能导致严重的社会和经济影响。利用全球季节预报业务系统第5版（GloSea 5）、NCEP气候预报系统（CFSv 2）和北京气候中心气候系统模式（BCC-CSM 1. 1 m）3种业务模式对华南冬季降水进行了预报。GloSea 5和CFSv 2的相关系数分别达到0.76和0.67，集合平均预报信号的幅度与观测变化相当。GloSea 5和CFSv 2的预报主要得益于对ENSO遥相关的成功再现。厄尔尼诺使步行者环流减弱，导致西北太平洋副热带高压加强。该反气旋在南海上空引起异常偏北气流，并将水汽带到华南地区，导致降水增多。这种遥相关型在BCC-CSM 1.1m中太弱，这解释了它的低技能（0.13）。而最熟练的预报系统也能通过孟加拉湾西南风的变化模拟印度洋对华南降水的影响。最后，我们检查了2015/16年冬季的实时预报，当时强烈的厄尔尼诺事件导致了中国南方近几十年来最高的降雨量。我们发现，GloSea 5系统给出了很好的建议，因为它产生了第三个最潮湿的中国南方在后报，但低估了观测到的振幅。这可能是由于低估了2015/2016年冬季西伯利亚高压的强度，从而导致了中国南方的强烈辐合。我们的结论是，目前的一些季节性预报系统可以提供有用的警告即将发生的极端事件。然而，仍然需要进一步改进模型，以充分反映该区域的复杂动态。
Southern China experiences large year-to-year variability in the amount of winter precipitation, which can result in severe social and economic impacts. In this study, we demonstrate prediction skill of southern China winter precipitation by three operational seasonal prediction models: the operational Global seasonal forecasting system version 5 (GloSea5), the NCEP Climate Forecast System (CFSv2) and the Beijing Climate Center Climate System Model (BCC-CSM1.1m). The correlation scores reach 0.76 and 0.67 in GloSea5 and CFSv2, respectively; and the amplitude of the ensemble mean forecast signal is comparable to the observed variations. The skilful predictions in GloSea5 and CFSv2 mainly benefit from the successful representation of the observed ENSO teleconnection. El Niño weakens the Walker circulation and leads to the strengthening of the subtropical high over the northwestern Pacific. The anti-cyclone then induces anomalous northward flow over the South China Sea and brings water vapor to southern China, resulting in more precipitation. This teleconnection pattern is too weak in BCC-CSM1.1m, which explains its low skill (0.13). Whereas the most skilful forecast system is also able to simulate the influence of the Indian Ocean on southern China precipitation via changes in southwesterly winds over the Bay of Bengal. Finally, we examine the real-time forecast for 2015/16 winter when a strong El Niño event led to the highest rainfall over southern China in recent decades. We find that the GloSea5 system gave good advice as it produced the third wettest southern China in the hindcast, but underestimated the observed amplitude. This is likely due to the underestimation of the Siberian High strength in 2015/2016 winter, which has driven strong convergence over southern China. We conclude that some current seasonal forecast systems can give useful warning of impending extremes. However, there is still need for further model improvement to fully represent the complex dynamics of the region.
登录
查看更多内容
影响因子：
--
作者：
Xu Xiangde
通讯作者：
Xu Xiangde
影响因子：
3.1
作者：
Tongwen Wu;R. Yu;Fang Zhang
通讯作者：
Tongwen Wu;R. Yu;Fang Zhang
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
DOI：
--
发表时间：
2005
期刊：
Langmuir : the ACS journal of surfaces and colloids
影响因子：
--
作者：
Liu;Yimin;Zhang;Renhe;Yin;Yonghong;Niu;Tao
通讯作者：
Liu;Yimin;Zhang;Renhe;Yin;Yonghong;Niu;Tao
DOI：
10.1007/s11430-008-0039-y
发表时间：
2008-06-01
期刊：
SCIENCE IN CHINA SERIES D-EARTH SCIENCES
影响因子：
--
作者：
Ji JinJun;Huang Mei;Li KeRang
通讯作者：
Li KeRang