| 长江中下游6—7月降水的降尺度模型 |
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| 引用本文： | 宋进波,陆尔,屠菊青,丁滢,刘思源.长江中下游6—7月降水的降尺度模型[J].大气科学学报,2018,41(1):85-92. |
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| 作者姓名： | 宋进波 陆尔 屠菊青 丁滢 刘思源 |
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| 作者单位： | 南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心;江西省气候中心; |
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| 基金项目： | 公益性行业（气象）科研专项（GYHY201506001） |
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| 摘 要： | 基于偏相关的强迫因子选取方法,以长江中下游6—7月降水为例,进行了降水变率的归因分析,并建立了相应的统计降尺度模型。结果表明,影响长江中下游6—7月降水的强迫因子主要有两个:西太平洋850 h Pa的位势高度(W_(PH8))和黑潮延伸区的海表温度(K_(SST))。W_(PH8)反映的是西太平洋副热带高压对长江中下游降水的影响;K_(SST)反映了黑潮延伸区的变率。基于这两个因子的线性降尺度模型能较好地拟合长江中下游6—7月的降水,在独立检验和模式检验阶段,模型体现出了可靠性,因而可用于长江中下游降水的季节预测。
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| 关 键 词： | 统计降尺度 偏相关 位势高度 海表温度 |
| 收稿时间： | 2016/3/2 0:00:00 |
| 修稿时间： | 2016/5/28 0:00:00 |
A statistical downscaling model for the summer rainfall over the middle and lower reaches of the Yangtze River Basin |
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| SONG Jinbo,LU Er,TU Juqing,DING Ying and LIU Siyuan.A statistical downscaling model for the summer rainfall over the middle and lower reaches of the Yangtze River Basin[J].大气科学学报,2018,41(1):85-92. |
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| Authors: | SONG Jinbo LU Er TU Juqing DING Ying and LIU Siyuan |
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| Institution: | Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China;Climate Center of Jiangxi Province, Nanchang 330046, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China |
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| Abstract: | As one of the means for bridging the gap between low resolution data obtained from weather models and those required in the basin scale,statistical downscaling has become an important field of study,due to its relative simplicity and practicability,along with its many flexible methods.More accurate forecast results can be obtained by the statistical downscaling method of establishing the function between the low-resolution raw model output and high-resolution prediction variables.With the partial correlation-based method,forcing factors are sought for the precipitation over the middle and lower reaches of the Yangtze River Basin in June and July,and a statistical downscaling model is established for the precipitation.The major forcing factors for the precipitation over the region include the 850 hPa geopotential height over the western Pacific(WPH8) and the sea surface temperature in the Kuroshio extension(KSST).The WPH8 may indicate the influence of the western Pacific subtropical high on the rainfall,while the KSST may reflect the variability of the Kuroshio extension.A regression statistical downscaling model based on WPH8 and KSST shows good performance in fitting the variability of early summer rainfall in the middle and lower reaches of the Yangtze River Basin,and the model also shows strong robustness in the independent validation.In the future the statistical downscaling model can be used for downscaling output from seasonal forecast numerical,and improving the middle and lower reaches of the Yangtze River Basin early summer rainfall prediction. |
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| Keywords: | statistical downscaling partial correlation geopotential height sea surface temperature |
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