| 基于PC-CCA方法的气象场资料插补试验 |
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| 引用本文： | 江志红,丁裕国,屠其璞.基于PC-CCA方法的气象场资料插补试验[J].南京气象学院学报,1999,22(2):141-148. |
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| 作者姓名： | 江志红 丁裕国 屠其璞 |
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| 作者单位： | 南京气象学院环境科学系,南京,210044 |
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| 基金项目： | 国家“九五”攻关项目资助 |
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| 摘 要： | 引入主成分典型相关分析（ＰＣ－ＣＣＡ）方法建立缺测气象要素场序列的插补模式，对区域性气象场序列（以长江流域月气温距平场为例）各种时空缺测分布型态作插补试验。结果表明，当插补场站网分布型取包含子场在内的混合站网时，建模样本量达２５年就可有最优插补精度，且性能稳定，效果优良。尤其当距平符号单一且大尺度分量占优势时，插补精度随缺测场变化很小
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| 关 键 词： | 典型相关分析(CCA) 气温距平场 资料序列插补 |
INTERPOLATION EXPERIMENT OF METEOROLOGICAL FIELDS BASED ON PC-CCA |
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| Jiang Zhihong,Ding Yuguo,Tu Qipu.INTERPOLATION EXPERIMENT OF METEOROLOGICAL FIELDS BASED ON PC-CCA[J].Journal of Nanjing Institute of Meteorology,1999,22(2):141-148. |
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| Authors: | Jiang Zhihong Ding Yuguo Tu Qipu |
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| Abstract: | A missing data field interpolation model is presented in terms of the method of principal component canonical correlation analysis (PC CCA). Experiments of regional meteorological fields series ( in the Yangtze basins) for different data missing distribution structures exhibit a stable highest precision can be obtained for mixed fields containing subfields when 25 year sample size is used, especially when a large scale component is dominant in the fields with single sign deviation from average. |
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| Keywords: | canonical correlation analysis(CCA) temperature anomaly fields data series interpolation |
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