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Spatiotemporal changes in snow depth and the influence factors in China from 1979 to 2019

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Abstract

Snow depth is an important parameter to characterize the characteristics of snow cover, and it is also one of the most sensitive response factors to regional climate change. However, the extent of snow depth variability and its driving mechanisms are still unknown in China. Therefore, in this study, we used the regression analysis, root-mean-square error analysis, anomalous year analysis, and correlation analysis methods to explore the spatiotemporal variation characteristics of snow depth in China from 1979 to 2019 based on the reanalysis snow depth dataset. The results show that (1) the snow distribution in China is obviously spatially heterogeneous, and the southeastern, western, and southern regions of the Qinghai-Tibet Plateau, northern Xinjiang, and northeastern China have high values of snow depth; (2) the high-value regions are also the sensitive regions for anomalous variations in snow depth in China; (3) in the past 41 years, the interannual variability of snow depth in China has shown a significantly decreasing trend, and the linear tendency of snow depth is − 0.093 cm/10 a (p < 0.01) and the snow depth in four seasons showed a decreasing trend (p < 0.05); and (4) the driving factors of snow heterogeneity are dissimilar in different regions and seasons. In temperate zones, average air temperature is the main factor affecting snow depth in cold temperature, mid temperature, and warm temperature zones; the maximum air temperature is the main factor affecting snow depth in mid temperate and warm temperate zones. Both the minimum air temperature and the average land-surface temperature are important factors affecting the snow depth in the cold temperate, mid temperate and warm temperate zones, and all passed the significance test of 0.01.

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Data availability

All the data used in this study are publicly available. The information on the sources of data is written in this paper.

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Acknowledgements

We would like to thank the National Qinghai-Tibet Plateau Science Data Center for providing the valuable datasets and wish to express our gratitude to “Ta-pieh Mountains National Observation and Research Field Station of Forest Ecosystem at Henan” for supplying the data processing platform.

Funding

This research was funded by the “National Natural Science Foundation Project of China (32130066),” “Henan Provincial Department of Science and Technology Research Project (212102310019),” “Sponsored by Natural Science Foundation of Henan (202300410531),” “Youth Science Foundation Program of Henan Natural Science Foundation (202300410077),” and “the major project of Collaborative Innovation Center on Yellow River Civilization jointly built by Henan Province and Ministry of Education (2020M19).”

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Authors and Affiliations

  1. College of Geography and Environmental, Henan University, Kaifeng, 475004, China

    Rumeng Li, Haoming Xia, Xiaoyang Zhao, Xiqing Bian, Yan Guo & Yaochen Qin

  2. Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security, Kaifeng, 475004, China

    Haoming Xia

  3. Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, 475004, China

    Haoming Xia & Yaochen Qin

Authors
  1. Rumeng Li
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  2. Haoming Xia
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  3. Xiaoyang Zhao
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  4. Xiqing Bian
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  5. Yan Guo
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  6. Yaochen Qin
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Contributions

All the authors contributed to the study conception and design. Conceptualization: Haoming Xia; data curation: Rumeng Li; formal analysis: Haoming Xia and Rumeng Li; funding acquisition: Haoming Xia; investigation: Rumeng Li and Haoming Xia; methodology: Haoming Xia and Rumeng Li; project administration: Haoming Xia and Yaochen Qin; resources: Rumeng Li and Haoming Xia; supervision: Haoming Xia; validation: Rumeng Li, Haoming Xia, Xiaoyang Zhao, Xiqing Bian, and Yan Guo; visualization: Rumeng Li. The first draft of the manuscript was written by Rumeng Li, and all the authors commented on previous versions of the manuscript. All the authors read and approved the final version of the manuscript.

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Correspondence to Haoming Xia.

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Li, R., Xia, H., Zhao, X. et al. Spatiotemporal changes in snow depth and the influence factors in China from 1979 to 2019. Environ Sci Pollut Res 30, 30221–30236 (2023). https://doi.org/10.1007/s11356-022-24281-1

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  • DOI: https://doi.org/10.1007/s11356-022-24281-1

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