SCIENTIA GEOGRAPHICA SINICA ›› 2023, Vol. 43 ›› Issue (4): 726-736.doi: 10.13249/j.cnki.sgs.2023.04.016

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Impact of threshold selection on the spatiotemporal change characteristics of high temperature

Liu Tingting1,2(), Zhu Xiufang1,2, Sun Shao3(), Zhang Shizhe1, Guo Rui1, Xu Kun1   

  1. 1. Key Laboratory of Environmental Evolution and Natural Disasters, Ministry of education, Beijing Normal University, Beijing 100875, China
    2. Institute of Remote Sensing Science and Engineering, Department of Geographical Sciences, Beijing Normal University, Beijing 100875, China
    3. National Climate Center, China Meteorological Administration, Beijing 100081, China
  • Received:2022-07-01 Revised:2022-10-12 Online:2023-04-30 Published:2023-04-20
  • Contact: Sun Shao E-mail:602018834@qq.com;sunshao@cma.gov.cn
  • Supported by:
    National Natural Science Foundation of China(42077436);National Key Research and Development Program of China(2019YFAO606900)

Abstract:

Under the background of the global warming, the frequency of extreme high temperature events is increasing. Although there have been many studies on the frequency and spatiotemporal distribution of high temperature around the world, there is still no unified definition of high temperature. In order to analyze the differences in high temperature events detected by different thresholds, and to strengthen the understanding of the multi-dimensional characteristics of high temperature, we detected high temperature by using different threshold methods, including three absolute thresholds (32℃, 35℃ and 38℃) and two relative thresholds (90% and 95%) based on the daily maximum temperature and daily minimum temperature data from 1979 to 2019 in the daily data set of China's surface climate data. Then, we calculated three high temperature indicators (including the absolute threshold high temperature days, absolute threshold high temperature accumulated temperature and relative threshold high temperature days) and used Sen's slope, Mann-Kendall, Hurst index and empirical orthogonal function (EOF) to analyze their trends and spatiotemporal distribution patterns, and finally compared the difference in trends and spatiotemporal distribution patterns of the high temperature indexes calculated in terms of different thresholds. The results show that: 1) The high temperature in most areas of China showed an increasing trend, but there are different in the trend and trend persistence of different high temperature indexes calculated from different thresholds. The number of stations with significant increase in high temperature days obtained by relative threshold method is much more than that by absolute threshold method. The absolute threshold method showed that the trend persistence of high temperature days was stronger in Xinjiang, South China and Huang-Huai-Hai Region, while the relative threshold method showed that the trend persistence of high temperature days was higher in southeast coast and central and western of China. 2) There are also significant differences among the patterns of EOF modes calculated from different thresholds. The second mode of high temperature indexes calculated by the absolute threshold reflected a reverse pattern of southern part of East China and most parts of southern China and other regions, while the second mode of high temperature indexes calculated by the relative thresholds reflected a reverse distribution pattern of northern and southern China. Therefore, researchers need to choose appropriate high temperature threshold according to their own research purposes and research problems.

Key words: high temperature definition, absolute threshold, relative threshold, Hurst, EOF

CLC Number: 

  • P732