主办单位：中国气象局沈阳大气环境研究所
国际刊号：ISSN 1673-503X
国内刊号：CN 21-1531/P
气象与环境学报

气象与环境学报 ›› 2012, Vol. 28 ›› Issue (6): 50-57.doi:

• 论文 • 上一篇    下一篇

辽宁地区夏季高温极值预测模型

李娇1,2,3  任国玉2  任玉玉2  沈志超1,2  孙秀宝1,2   

  1. 1. 南京信息工程大学大气科学学院，江苏 南京 210044 ；2. 中国气象局气候研究开放实验室，国家气候中心，北京 100081；3. 铁岭市气象局，辽宁 铁岭 112000
  • 出版日期:2012-12-28 发布日期:2012-12-28

Prediction models of summer extreme high temperature in Liaoning province

LI Jiao1,2,3  REN Guo-yu2  REN Yu-yu2  SHEN Zhi-chao1,2  SUN Xiu-bao1,2   

  1. 1.College of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China; 2. The Laboratory for Climate Studies of China Meteorological Administration, National Climate Center, Beijing 100081, China; 3.Tieling Meteorological Service, Tieling 112000, China
  • Online:2012-12-28 Published:2012-12-28

PDF (PC)

591

被引次数

3

摘要： 利用1957—2006年辽宁地区夏季23站极端最高气温资料和国家气候中心气候监测室的74项环流特征量资料，应用EOF方法对高温极值样本进行分解，研究辽宁极端高温的时空分布规律。结果表明：第一特征向量表现为区域整体一致的特征，中心区位于辽西北、辽北，第二、三特征向量空间分布表现为东西部反位相和南北反位相的特征。普查了前3个时间系数与前期环流指数的相关关系，认为前3个时间系数的显著影响因子是不同的。采用CSC准则确定最优预测因子，分别建立各时间系数的回归统计模型，并对高温极值历史拟合序列进行回报检验和预测检验。回报结果表明，各站的历史拟合率都保持在一定水平，但拟合率在辽西地区较差。各年的历史拟合率极不均衡，多数年份较为稳定，但个别年份拟合率较低。未来3 a试验性预测效果逐年下降，模型对未来1 a预测能力较好，可以作为业务预测的参考。

关键词: 高温极值, EOF, 环流指数, 最优子集回归, 统计模型, 气候预测, 辽宁

Abstract: Based on the summer extreme high temperature data in 23 weather stations in Liaoning province and 74 circulation indices information from the climate monitoring department of the National Climate Center (NCC), China Meteorological Administration (CMA), the temporal and spatial distribution features of summer extreme high temperature in Liaoning province were analyzed by a Empirical Orthogonal Function (EOF) decomposition method. The results show that the first EOF vector is characterized by a uniform anomaly over the whole area and the centers are in the northern and northwestern Liaoning province, while the second and third EOF vectors are the reversed phase patterns in the east and west areas and in the south and north areas, respectively. The correlation coefficient between first three time coefficient series and preceding circulation indices are calculated. It is found that the influencing factors are different for the three time coefficients. The optimum subset regressions are chosen as prediction equations using the CSC evaluation method and the fitting rate of past records in the 23 weather stations and each year are tested. It shows that the fitting rate of past records in the 23 weather stations is generally stable, except for in the western Liaoning province. In addition, the fitting rate is unbalanced each year, and it is stable in most years, while it is low in few individual years. While the prediction effect is good for the first year in the future it declines yearly in the following two years. The results can be used as reference in climatic prediction.

Key words: Extreme high temperature, EOF, Circulation index, Optimum subset regression, Statistic models, Climate prediction, Liaoning province