Characteristics of Dry and Wet Climate Change in China from 1960 to 2019 Based on TerraClimate Dataset

XIAO Xiao, QIU Xin-fa, XU Jin-qin

Journal of Changjiang River Scientific Research Institute ›› 2023, Vol. 40 ›› Issue (2) : 27-33.

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Journal of Changjiang River Scientific Research Institute ›› 2023, Vol. 40 ›› Issue (2) : 27-33. DOI: 10.11988/ckyyb.20211079
WATER RESOURCES

Characteristics of Dry and Wet Climate Change in China from 1960 to 2019 Based on TerraClimate Dataset

  • XIAO Xiao1, QIU Xin-fa1, XU Jin-qin2
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Abstract

High spatial resolution TerraClimate dataset is employed to analyze the characteristics of dry and wet climate change in China under the influences of geographical terrain and underlying surface. According to monthly precipitation and evapotranspiration data from 1960 to 2019 in the TerraClimate data set, the range of dry and wet areas, dry and wet climate boundaries and climate change trend in China are analyzed based on precipitation and humidity index. Compared with those in the first three decades, the area of arid and humid regions in the latter three decades showed negative increase, and the area of semi-arid and semi-humid regions positive increase. The dividing line fluctuated mainly in Heilongjiang province, central and northeast Inner Mongolia, and Huaihe River. In recent six decades, the precipitation and humidity index tended to increase in the west and southeast, indicating that the climate was getting wet, and vice versa. Comparison with meteorological data analysis manifests that the TerraClimate dataset is more applicable and well reflects the dry and wet conditions in China and their variation characteristics, and the applicability of precipitation data is more prominent.

Key words

climate change / TerraClimate dataset / dry and wet climate boundary / precipitation / humidity index / trend analysis

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XIAO Xiao, QIU Xin-fa, XU Jin-qin. Characteristics of Dry and Wet Climate Change in China from 1960 to 2019 Based on TerraClimate Dataset[J]. Journal of Changjiang River Scientific Research Institute. 2023, 40(2): 27-33 https://doi.org/10.11988/ckyyb.20211079

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