| 2015/2016年超强El Nio事件背景下我国月预测技巧差异分析 |
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| 引用本文： | 陈丽娟,李想,李维京,李景鑫.2015/2016年超强El Nio事件背景下我国月预测技巧差异分析[J].大气科学学报,2016,39(6):756-765. |
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| 作者姓名： | 陈丽娟 李想 李维京 李景鑫 |
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| 作者单位： | 中国气象局 国家气候中心/气候研究开放试验室, 北京 100081;南京信息工程大学 气象灾害预报预警与评估协同创新中心, 江苏 南京 210044;中国气象局 国家气候中心/气候研究开放试验室, 北京 100081;中国气象局 国家气候中心/气候研究开放试验室, 北京 100081;南京信息工程大学 气象灾害预报预警与评估协同创新中心, 江苏 南京 210044;中国气象局 国家气候中心/气候研究开放试验室, 北京 100081;中国气象科学研究院, 北京 100081 |
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| 基金项目： | 国家重点基础研究发展计划（973计划）资助项目（2015CB453203；2013CB430203）；国家自然科学基金资助项目（41275073）；公益性行业（气象）科研专项（GYHY201306032） |
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| 摘 要： | 利用中国站点观测降水资料、国家气候中心第2代月动力延伸预报模式(BCC_DERF2.0)的回报和预报数据、NCEP/NACR再分析资料和国家气候中心实时发布的月尺度降水预测评分数据,通过评估和诊断分析发现,在2015/2016年超强El Nio事件背景下,这两年内业务发布的月降水预报能力有明显不同,BCC_DERF2.0对月环流的预测技巧也存在差异:在2015年(El Nio发展位相),降水预报和环流预测技巧较高且稳定,而在2016年(El Nio衰减位相)的预报技巧总体偏低。进一步的研究显示,亚洲—太平洋涛动(Asia-Pacific Oscillation,APO)可能是导致2015年和2016年夏季预测技巧高低的重要影响因素。2015(2016)年夏季为APO低(高)指数年,且2016年具有高指数年的典型环流特征。而APO高指数对应的环流特征与El Nio衰减位相对西北太平洋环流的影响不同,在El Nio和APO的物理影响途径不一致时,将直接影响东亚环流可预报性的高低及动力气候模式的预报技巧,即El Nio在发展和衰减位相与APO型不同组合的影响是2015和2016年月预测技巧有差异的重要原因。
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| 关 键 词： | El Niño事件 月预测技巧 可预报性 APO指数 |
| 收稿时间： | 2016/10/7 0:00:00 |
| 修稿时间： | 2016/11/9 0:00:00 |
Analysis of different monthly prediction skills over China during the 2015/2016 super El Niño event |
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| CHEN Lijuan,LI Xiang,LI Weijing and LI Jingxin.Analysis of different monthly prediction skills over China during the 2015/2016 super El Niño event[J].大气科学学报,2016,39(6):756-765. |
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| Authors: | CHEN Lijuan LI Xiang LI Weijing and LI Jingxin |
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| Institution: | National Climate Center/Laboratory for Climate Studies, CMA, Beijing 100081, China;Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China;National Climate Center/Laboratory for Climate Studies, CMA, Beijing 100081, China;National Climate Center/Laboratory for Climate Studies, CMA, Beijing 100081, China;Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China;National Climate Center/Laboratory for Climate Studies, CMA, Beijing 100081, China;Chinese Academy of Meteorological Sciences, Beijing 100081, China |
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| Abstract: | The ENSO cycle is a strong signal in atmosphere-ocean interaction,and plays a significant role in the global climate,including the East Asia monsoon region.Typically,in the developing phase of El Niño,the convection is strong in the east-central tropical Pacific,and weak in the west tropical Pacific and Maritime continent.In the following summer,the northwest subtropical high is weaker than normal,and is located southward from its normal position.As a result,the southwest jet stream from the Bay of Bengal is weaker than normal,and carries less moisture to mainland China.In the decaying phase of El Niño,the Philippines anti-cyclone can persist until summer,and the northwest subtropical high is strong and located westward from its normal position.The southwest jet stream from the Bay of Bengal is much stronger than normal and carries more moisture to mainland China.In addition,the Yangtze River typically experiences flood events.Aside from the ENSO cycle,the vertical averaged eddy temperature difference between the Asian and Pacific may have less influence on the East Asia summer monsoon.The Asian-Pacific Oscillation(APO) and its associated indexes can be used to identify this difference.With higher APO index years,in the upper troposphere the summer South Asian high and North Pacific trough are stronger,while the westerly jet stream over Asia and easterly jet stream over South Asia are strengthened.Further more,in the lower troposphere the Asian low and North Pacific subtropical high are stronger.The anomalous westerly prevails over South Asia,and the Meiyu front is located northward from its normal position.Such a circulation pattern may lead to greater rainfall in northern China,southern China and South Asia.Further analysis shows that the combined impact of the ENSO phase and APO index has different predictability for the East Asia climate.This paper will study the 2015/2016 monthly prediction skill differences under the background of super strong El Niño events and different APO index conditions.The data used in the paper include station precipitation data,BCC_DERF2.0 hindcast and forecast data,NCEP/NCAR reanalysis data,and the scores of NCC issued monthly precipitation forecast.Some of the results are obtained through verification methods and diagnostic techniques,as follows:(1) During the super El Niño event occurring from 2015 to 2016,the skills of the issued monthly precipitation prediction are high/stable in 2015(El Niño developing phase),and low/unstable in 2016(El Niño decaying phase).The skills of the key circulation predicted by BCC_DERF2.0 show results similar to the precipitation.Further analysis indicates that Asia-Pacific Oscillation(APO) may play another important role in the predictability of monthly scale prediction in 2015 and 2016.(2) The APO index is low in summer 2015 and high in summer 2016.The effect of low APO on East Asia circulation is consistent with that of the El Niño developing phase in 2015,while that of the high APO on East Asia circulation is not consistent with that of the El Niño decaying phase in 2016.That is to say,the eddy temperature difference between the Asian and Pacific in 2016 is favorable for strong Asia summer monsoons,while the El Niño decaying phase leads to weak summer monsoons.(3) The circulations in 2016 show some typical features of higher APO index conditions,and BCC_DERF2.0 can predict most of the features of the high APO index conditions in 2016.The summer rainfall anomaly in 2016 shows that both the Yangtze River and northern China experienced flood disasters.These facts imply that the climate features in 2016 are multi-factor results.(4) The combined effect of the APO index and El Niño phase may have different predictabilities on the monthly East Asian circulation.The skill of BCC_DERF2.0 depends on these two factors,as does the monthly precipitation in 2015 and 2016. |
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| Keywords: | El Niño event monthly prediction skills predictability APO index |
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