RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2017, Vol. 26 >> Issue (01): 110-117.doi: 10.11870/cjlyzyyhj201701013

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INTERACTION OF TEMPERATURE AND RAINFALL IN ANHUI PROVINCE BASED ON COPULA FUNCTION

YE Ming-hua1, WANG Rong-ming1, DING Yue1, SHU Jiong2   

  1. 1. School of Statistics, East China Normal University, Shanghai 200241, China;
    2. Geographic Information Science Key Laboratory of Ministry of Education, East China Normal University, Shanghai 200241, China
  • Received:2016-05-20 Revised:2016-09-26 Online:2017-01-20
  • Supported by:
    National Natural Science Foundation of China (71403088);National Social Science Fund Key Projects (13&ZD161);Supported by the 111 Project (B14019)

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Abstract: Under the background of global warming, the interaction of temperature and rainfall makes the agricultural meteorological disasters occur frequently, causing destructive risk to agricultural production. In this paper, we collected daily data of rainfall and temperature observed at 24 meteorological stations in Anhui Province in the period of 1980-2014 and collected the monthly average rainfall data of each station. We calculated the moment average rainfall of each station by subtracting average monthly rainfall data from the monthly raw rainfall data divided by the average. Finally, we used the average of moment average rainfall of 24 stations as rainfall data of Anhui Province. According to the rainfall frequency histogram, the distribution of rainfall data was asymmetric, showing some level of right-skewness. According to the temperature frequency histogram, the distribution of temperature data was basically symmetric while presenting "peak thick tail" features. Therefore, we determined the marginal distributions of temperature and rainfall data through non parametric kernel estimation method. The frequency histograms of rainfall and temperature showed that there was a negative correlation between them, suggesting that the diagram presented the symmetric upper and lower tails of rainfall and temperature. Based on this symmetry, we selected three types of Copula functions, i.e., normal Copula, t-Copula and frank-Copula. Finally, based on the principle of minimum squared Euclidean distance, bivariate t-copula function is chosen to draw the probability density function of rainfall and temperature. The results showed that from the perspective of joint probability distribution of temperature and precipitation in Anhui Province, when the rainfall was rising, the temperature dropped; or when the temperature was rising, the rainfall decreased. There was a medium negative correlation (-0.280) between rainfall and temperature. From the perspective of probability density function diagram of t-copula and upper and lower tail correlation coefficient, the temperature and rainfall in Anhui Province had a relatively obvious dependence relation in extreme, which means, when the temperature and rainfall were beyond normal range, their dependence changed from negative correlations to positive correlations. This phenomenon would occur more in extreme weather conditions, such as extreme high temperature or rainstorm.

Key words: temperature, rainfall, Copula function, probability density function of rainfall and temperature, extremum correlation

CLC Number: 

  • S114
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