熊开国,封国林,黄建平,丑纪范. 2012. 最优多因子动态配置的东北汛期降水相似动力预报试验[J]. 气象学报, 70(2):213-221, doi:10.11676/qxxb2012.021
最优多因子动态配置的东北汛期降水相似动力预报试验
Analogue-dynamical prediction of monsoon precipitation in Northeast China based on dynamic and optimal configuration of multiple predictors
投稿时间:2010-05-15  修订日期:2011-02-10
DOI:10.11676/qxxb2012.021
中文关键词:  相似-动力预报, 汛期降水, 误差订正, 动态最优配置
英文关键词:Analogue-dynamical prediction, Monsoon precipitation, Correction of errors, Dynamic and optimal configuration
基金项目:公益性行业科研专项(GYHY200806005)、国家自然科学基金(40930952和41075058)和国家科技支撑计划(2007BAC29B01和2009BAC51B04)
作者单位
熊开国 半干旱气候变化教育部重点实验室兰州大学大气科学学院兰州730000 
封国林 国家气候中心气候研究开放实验室北京100081
中国科学院大气物理研究所东亚区域气候-环境重点实验室北京100029 
黄建平 半干旱气候变化教育部重点实验室兰州大学大气科学学院兰州730000 
丑纪范 半干旱气候变化教育部重点实验室兰州大学大气科学学院兰州730000 
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中文摘要:
      基于中国气象局国家气候中心季节预报业务模式27 a(1983—2009年)预报结果和同期美国气候预报中心组合降水分析(CMAP)资料及国家气候中心气候系统诊断预报室74项环流指数和NOAA 40个气候指数(1951—2009年),提出了客观定量化的最优多因子动态配置汛期降水相似 动力预测新技术,并对中国东北地区汛期降水进行了预报试验。利用历史资料有用信息估算模式预报误差原理,选取4个历史相似年对应模式误差来估算当前模式预报误差。通过单因子交叉检验距平相关系数确定主导因子及演化相似因子,结合当前及前期优化多因子组合配置确定预报因子集,最后利用历史相似年对应模式误差来估算当前模式预报误差并订正国家气候中心季节预报业务模式的预报结果,得到预报的汛期降水。对2005—2009年进行独立样本检验的结果表明,此技术对中国东北地区汛期降水有一定预报技巧。证实了利用历史资料估计业务模式预报误差的另类途径是可行的,显示了在业务预报应用中的潜在能力。
英文摘要:
      Based on the National Climate Center (NCC) of China operational seasonal prediction model results for the period 1983-2009 and the US National Weather Service Climate Prediction Center merged analysis of precipitation in the same period, together with the 74 circulation indices of NCC Climate System Diagnostic Division and 40 climate indices of NOAA of US during 1951-2009, an analogue-dynamical technique for objective and quantitative prediction of monsoon precipitation in Northeast China is proposed and implemented. Useful information is extracted from the historical data to estimate the model forecast errors. Dominant predictors and the predictors that exhibit evolving analogues are identified through cross validating the anomaly correlation coefficients (ACC) among single predictors, meanwhile with reference of the results from the dynamic analogue bias correction using four analogue samples. Next, an optimal configuration of multiple predictors is set up and compared with historical optimal multi-predictor configurations and then dynamically adjusted. Finally, the model errors are evaluated and utilized to correct the NCC operational seasonal prediction model results, and the forecast of monsoon precipitation is obtained at last. The independent sample validation shows that this technique has effectively improved the monsoon precipitation prediction skill during 2005-2009. This study demonstrates that the analogue-dynamical approach is feasible in operational prediction of monsoon precipitation.
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