|
|||||
|
|
| 近53a中国气温异常分布的非线性特征 | |
| 引用本文： | 郭品文,徐同,居丽丽.近53a中国气温异常分布的非线性特征[J].南京气象学院学报,2009,32(1):11-16. |
| 作者姓名： | 郭品文 徐同 居丽丽 |
| 作者单位： | 1. 南京信息工程大学,气象灾害省部共建教育部重点实验室,江苏,南京,210044 2. 中国气象局,上海台风研究所,上海,200030 3. 南汇区气象局,上海,201300 |
| 基金项目： | 江苏省"六大人才高峰"项目 |
| 摘 要： | 运用一种基于神经网络的非线性主成分分析法（nonlinear principal component analysis,NLP-CA）对中国1951—2003年53 a四季气温距平场（surface air temperature anomaly,SATA）进行分析,NLPCA第一模态结果显示中国四季气温异常具有一定的非线性特征,并且具有显著的季节性差异,即春、夏两季的非线性较强,秋、冬两季较弱。一维NLPCA对原始气温距平场的近似比一维PCA（principal component analysis）更好地反映了气温场的实际分布情况。 |
| 关 键 词： | 气温 非线性 主成分分析 非线性主成分分析 |
Nonlinear Characteristics of Surface Air Temperature Anomalies over China in Recent 53 Years |
|
| GUO Pin-wen,XU Tong,JU Li-li.Nonlinear Characteristics of Surface Air Temperature Anomalies over China in Recent 53 Years[J].Journal of Nanjing Institute of Meteorology,2009,32(1):11-16. | |
| Authors: | GUO Pin-wen XU Tong JU Li-li |
| Institution: | 1.Key Laboratory of Meteorological Disaster of Ministry of Education;NUIST;Nanjing 210044;China;2.Shanghai Typhoon Institute;China Meteorological Administration;Shanghai 200030;3.Nanhui Meteorogical Bureau;Shanghai 201300;China |
| Abstract: | Seasonal surface air temperature(SAT) anomalies over China from 1951 to 2003 is investigated by applying a neural-network-based nonlinear principal component analysis(NLPCA) method.The results of the first NLPCA mode show that the seasonal SAT anomalies have some nonlinear characters;its nonlinearity is stronger in spring(MAM) and summer(JJA),and weaker in autumn(SON) and winter(DJF).The SAT approximation by 1-D NLPCA is closer to the observations than that by 1-D PCA. |
| Keywords: | temperature nonlinearity principal component analysis NLPCA |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |