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Spatiotemporal variability of snowfall and its concentration in northern Xinjiang, Northwest China

  • Tao Yang
  • Qian Li
  • Wenjiang Liu
  • Xiang Liu
  • Lanhai LiEmail author
  • Philippe De Maeyer
Original Paper
  • 38 Downloads

Abstract

This study investigated the spatial and temporal variability of snowfall and its concentration across northern Xinjiang, Northwest China based on the corrected dataset (derived from 26 stations) using a wet-bulb temperature method during the snowfall hydrological years from 1961 to 2017. The snowfall concentration was analyzed by means of three indices: the snowfall concentration index (CI), snowfall concentration degree (SCD), and snowfall concentration period (SCP). The results demonstrated that the snowfall and temperature increased by 5.69 mm and 0.35 °C per decade, respectively, in northern Xinjiang during the time period from 1961 to 2017. Maximum snowfall occurred at a critical temperature ranging from − 2 to 1 °C. The increased snowfall mainly took place in northern Xinjiang during winter. The distribution of the high snowfall CI value indicated that the daily snowfall showed a high irregularity in the northern slope of the Tianshan Mountains and the northern Altay Mountains, in which more than 77% snowfall was contributed by the 25% snowfall days in a year. The results of SCP revealed that the snowfall concentrated in northern Xinjiang during December, with an earlier arrival in the north and east of northern Xinjiang than in the western part. The SCD results proved that the monthly snowfall was more concentrated in the northern Altay Mountains, Ili Valley, and Boertala Valley than over the eastern part of northern Xinjiang during a year. The snowfall in almost all stations increased in concentration throughout the year. The obtained study results could provide scientific reference for future water resource management and snow disaster prevention under a warming climate.

Notes

Acknowledgments

The authors would like to thank the National Meteorological Administration of China (http://data.cma.cn) for providing downloadable daily climate data series in the study area and Dr. L. X. Li from Ontario Veterinary Medical Association for her linguistic assistance during the revision of this manuscript.

Funding information

This study was supported by the projects of the National Natural Science Foundation of China (NSFC Grant No. 41401030, U1703241), National Project of Investigation of Basic Resources for Science and Technology (No. 2017FY100501).

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Authors and Affiliations

  1. 1.State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and GeographyChinese Academy of SciencesUrumqiChina
  2. 2.Ili Station for Watershed Ecosystem ResearchChinese Academy of SciencesXinyuanChina
  3. 3.University of Chinese Academy of SciencesBeijingChina
  4. 4.Department of GeographyGhent UniversityGhentBelgium
  5. 5.Sino-Belgian Joint Laboratory of Geo-informationUrumqiChina
  6. 6.Sino-Belgian Joint Laboratory of Geo-informationGhentBelgium
  7. 7.CAS Research Center for Ecology and Environment of Central AsiaUrumqiChina
  8. 8.Institute of Geography and Resources ScienceSichuan Normal UniversityChengduChina
  9. 9.Xinjiang Regional Centre of Resources and Environmental Science InstrumentsChinese Academy of SciencesUrumqiChina

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