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Spatial and temporal analysis of changes in temperature extremes in the non-monsoon region of China from 1961 to 2016

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Abstract

Changes in temperature extremes have far-reaching consequences for fragile ecological processes, hydrologic cycles, and human society in semiarid and arid regions. Therefore, detecting the spatial and temporal variations in temperature extremes and their driving mechanisms is crucial. Based on daily temperature records from 1961 to 2016 at 154 meteorological stations in the non-monsoon region of China, the spatial and temporal variations in 12 extreme temperature indices and the diurnal temperature range (DTR) were analyzed, and the association of these variations with atmospheric circulation patterns was also investigated. The major conclusions are as follows. (1) DTR and cold temperature extremes decreased significantly except for the coldest days (TXn) and coldest nights (TNn), which increased significantly, while all the warm temperature extremes significantly increased in the past 56 years; that is, all the temperature-based indices show patterns consistent with a general warming trend. (2) Cold extremes slowed during the global warming hiatus (1998–2016) compared with 1961–2016; however, the variation trends in the warm extremes did not change dramatically between the two periods. (3) Almost all temperature indices display the largest trend magnitudes in the cold-half year (autumn and winter), the variation trends in most cold extremes are significantly higher than those in warm extremes, and the warming rates of the nighttime indices are also significantly faster than those of the daytime indices. (4) Spatially, for most significant temperature indices, the stations located on the Tibetan Plateau show larger variation trends. (5) Both annual and seasonal Atlantic multidecadal oscillation (AMO) index are significantly correlated with almost all of the temperature indices, except for TXn; further, the summer and winter western Pacific subtropical high intensity (WPI) index, the summer and winter North Atlantic oscillation (NAO) index, and the winter Arctic oscillation (AO) index display significant relationships with most of the temperature extremes, which indicates that the large atmospheric circulation patterns play significant roles in the changing temperature extremes in this region. Overall, the results provide scientific references for understanding and predicting the spatial and temporal trends of extreme climate in the future.

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Acknowledgements

This work was financially supported by Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDA20060101); the National Key Research and Development Program on monitoring, early warning and prevention of major natural disasters (grant no. 2017YFC1502401); the National Natural Science Foundation of China (Grant No.91837208 and No.41661144043); Chinese Academy of Sciences (Grant No. QYZDJ-SSWDQC019). Meanwhile, the first author thanks the China Meteorological Administration (CMA) and the National Oceanic and Atmospheric Administration (NOAA) for providing the data used in this study.

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Authors and Affiliations

  1. Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, No.16 Lincui Road, Chaoyang, Beijing, 100101, China

    Yuyang Wang & Yaoming Ma

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Yuyang Wang & Yaoming Ma

  3. State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, No.19 Xinjiekou Waidajie, Haidian, Beijing, 100875, China

    Zhiyong Ding

  4. CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, 100101, China

    Yaoming Ma

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  1. Yuyang Wang
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Wang, Y., Ding, Z. & Ma, Y. Spatial and temporal analysis of changes in temperature extremes in the non-monsoon region of China from 1961 to 2016. Theor Appl Climatol 137, 2697–2713 (2019). https://doi.org/10.1007/s00704-019-02767-2

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