Resources Science ›› 2018, Vol. 40 ›› Issue (8): 1672-1683.

• Orginal Article •

Analysis of temporal and spatial variation of extreme temperature in Guizhou Province

Dayun ZHU1,2(), Kangning XIONG1,2(), Hua XIAO1,2

1. 1. School of Karst Science, Guizhou Normal University, Guiyang 550001, China
2. State Engineering Technology Institute for Karst Desertfication Control, Guiyang 550001, China
• Received:2017-09-24 Revised:2018-04-03 Online:2018-08-25 Published:2018-08-10

Abstract:

With global warming, the extreme weather events in southwest China have become more frequent and the damage is also deepening, posing a serious threat to national economic development and ecological environment protection. Based on daily temperature data sets of 33 stations in Guizhou Province, spatial and temporal changes of extreme temperature and its influence factors were analyzed during the period of 1960-2016, by using the methods of linear regression, Inverse Distance Weighted (IDW) and Mann-Kendall(M-K) test. The results showed that in the last 57 years the climate of Guizhou is getting warmer and accelerating the trend in the 21st century. The extreme high temperature indices, i. e. summer day, the percentile value of warm day, the duration of warmness and the frequency of the duration of warmness have all increased, with the velocity of 0.6d/10a、2.7d/10a、0.02d/10a、and 0.2times/10a, respectively. And the extreme low temperature indices, i. e. frost day, the percentile value of cold day, the duration of coldness and the frequency of the duration of coldness have decreased, with the velocity of -1.6d/10a、-8.0d/10a、 -0.5d/10a、and -1.0times/10a, respectively. In addition, the extreme temperatures show asymmetry pattern. For example, the change range of extreme low temperature indices is greater than that of extreme high temperature indices, the tropical days and cold days have the largest variation. There is a close relationship between the extreme temperature indices and altitude. Moreover, most abrupt change of climate occurred in the late 19th and early 2000s. El Niño has a significant impact on the extreme warm series index, and La Nina has a greater influence on the extreme cold series index. The impact of La Nina on the extreme cold series index reached its highest level in the following year.