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

Journal of Meteorology and Environment ›› 2012, Vol. 28 ›› Issue (6): 50-57.doi:

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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

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