doi:  10.3878/j.issn.1006-9895.1906.18244
夏季亚洲对流层中上层温度年际变率的预测水平评估及其在我国东部降水预测中的应用

Evaluation on the Prediction Skill of the Interannual Variability of Summer Asian Upper Tropospheric Temperature and Its Application to Prediction of Precipitation in Eastern China
摘要点击 286  全文点击 141  投稿时间:2018-10-30  
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基金:  国家自然科学基金项目 41675076 国家自然科学基金项目41675076
中文关键词:  季节预测  可预报性  动力—统计降尺度预测模型  对流层温度
英文关键词:  Seasonal forecasting  Predictability  Dynamical-statistical forecast model  Tropospheric temperature
     
作者中文名作者英文名单位
张丽霞ZHANG Lixia中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室(LASG)
周天军ZHOU Tianjun中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室(LASG)
引用:张丽霞,周天军.2020.夏季亚洲对流层中上层温度年际变率的预测水平评估及其在我国东部降水预测中的应用[J].大气科学,44(1):150-167,doi:10.3878/j.issn.1006-9895.1906.18244.
Citation:ZHANG Lixia,ZHOU Tianjun.2020.Evaluation on the Prediction Skill of the Interannual Variability of Summer Asian Upper Tropospheric Temperature and Its Application to Prediction of Precipitation in Eastern China[J].Chinese Journal of Atmospheric Sciences (in Chinese),44(1):150-167,doi:10.3878/j.issn.1006-9895.1906.18244.
中文摘要:
      夏季亚洲对流层温度异常与中国东部夏季降水紧密相关并可能作为降水的有效预报因子。基于欧盟ENSEMBLES计划的季节预测试验耦合模式每年5月1日开始的回报试验,分析了其对1960~2005年夏季亚洲对流层中上层温度(以200~500 hPa厚度替代,简称对流层温度)年际变率的预测结果,发现模式集合平均对夏季亚洲对流层温度年际变率具有较高的预报技巧,可以合理回报其前两个EOF(Empirical Orthogonal Function)主导模态(EOF1、EOF2),只是未能回报出EOF2高纬度的温度异常,模式集合平均预测的第一模态主成分(PC1)和第二模态主成分(PC2)与再分析资料的时间相关系数分别达到0.63和0.77。再分析资料中前两个EOF模态分别由ENSO(El Niño–Southern Oscillation)发展年印度夏季降水异常所激发的丝绸之路遥相关波列和ENSO衰减年西北太平洋夏季降水异常对应的太平洋—日本遥相关波列导致。ENSEMBLES计划可以合理预测出相应的海温异常及遥相关波列,进而合理预测出前两个EOF模态。对流层温度PC1和PC2分别表征了欧亚大陆与周围海洋之间的纬向和经向热力对比异常,模式对由PC1的预报技巧远高于前人定义的纬向热力对比的东亚夏季风指数,对前人定义的经向热力对比指数的预测技巧与PC2相当。将PC1和前人定义的经向热力对比指数作为预报因子,建立了中国夏季降水的动力—统计降尺度预测模型,交叉检验的结果表明该预报模型显著提高了东北和长江流域上游夏季降水的预报技巧。本文提出的亚洲对流层温度年际变率的EOF1及PC1,既能较好表征纬向热力对比与中国东部夏季降水显著相关,又能被模式合理预测,可以作为我国中高纬度地区,特别是东北地区降水的重要预测因子之一。
Abstract:
      Variations in Asian upper tropospheric temperature during summer is closely related to, and may, indeed, serve as a useful predictor of East Asian precipitation. The predictability of these interannual variations in summer UTT (upper tropospheric temperature, represented by 500-200 hPa thickness) for the period 1960-2005 in the ENSEMBLES multi-model seasonal forecast, initiated 1 May every year, was examined in this study. Results showed that the interannual variability of Asian UTT in summer was skillfully predicted by ENSEMBLES, as measured by the good prediction of its standard deviation centers in the mid-latitude and high correlation coefficient of its first two leading interannual variability modes compared with observations. The main deficiency of the multimodel ensemble mean (MME) was that the temperature at high-latitudes could not be captured. The correlation coefficients of the first (PC1) and second (PC2) principle components in the MME with those from NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis were 0.63 and 0.77, respectively. The first two leading models of Asian UTT in summer in observation were dominated by (1) the silk-road teleconnection at the upper troposphere forced by Indian monsoon precipitation anomalies in an ENSO-developing summer, and (2) the Pacific-Japan teleconnection forced by northwestern Pacific Ocean rainfall anomalies in an ENSO-decaying summer, respectively. These processes were well-predicted by ENSEMBLES; thus, a high prediction skill for Asian summer UTT was shown in ENSEMBLES. The first two leading modes of Asian summer UTT well-represented the zonal and meridional thermal contract variation. A comparison with two previous widely-used East Asian Summer Monsoon (EASM) indices was performed; results showed a much better predictive outcome for PC1 than for the traditional zonal thermal contrast. Using PC1 of Asian summer UTT and the traditional meridional EASM index as two predictors of summer precipitation over eastern China, a dynamical-statistical forecast model was established. The cross-validation results showed that the new forecast model significantly improved the predictive skill of summer precipitation over Northeast China and the upper stream of the Yangtze River. The first leading mode of Asian summer UTT and corresponding PC could well represent the zonal thermal contrast, which has a correlative relationship with summer precipitation over eastern China, and can be well-predicted by climate models. It can effectively serve as one predictor of summer precipitation over mid-latitude China, particularly northeastern China.
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