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The Cryosphere An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/tc-2019-300
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-2019-300
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  18 Dec 2019

18 Dec 2019

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This discussion paper is a preprint. It has been under review for the journal The Cryosphere (TC). The manuscript was not accepted for further review after discussion.

Spatiotemporal variation of snow depth in the Northern Hemisphere from 1992 to 2016

Xiongxin Xiao1,2, Tingjun Zhang1,4, Xinyue Zhong3, Xiaodong Li1, and Yuxing Li1 Xiongxin Xiao et al.
  • 1Key Laboratory of Western China’s Environmental Systems (Ministry of Education), College of Earth and Environment Sciences, Lanzhou University, Lanzhou 730000, China
  • 2School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
  • 3Key Laboratory of Remote Sensing of Gansu Province, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China
  • 4University Corporation for Polar Research, Beijing 100875, China

Abstract. Snow cover is an effective indicator of climate change due to its impact on regional and global surface energy and water balance, and thus also weather and climate, hydrological processes and water resources, and the ecosystem as a whole. The overall objective of this study is to investigate changes and variations of snow depth and snow mass over the Northern Hemisphere from 1992 to 2016. We developed a long term Northern Hemisphere daily snow depth and snow water equivalent product (NHSnow) by applying the support vector regression snow depth retrieval algorithm, using passive microwave remote sensing data from the period. NHSnow product was evaluated along with the other two snow cover products (GlobSnow and ERA-Interim/Land) for its accuracy across the Northern Hemisphere. The evaluation results show that NHSnow performs comparably well with relatively high accuracy (bias: −0.59 cm, mean absolute error: 15.12 cm, and root mean square error: 20.11 cm) when benchmarked against the station snow depth measurements. Further analyses were conducted across the Northern Hemisphere using snow depth, snow mass, and snow cover days as indices. Analysis results show that annual average snow mass have a significant declining trend, with a rate of about 19.72 km3 yr.−1 or a 13 % reduction in snow mass. Although spatial variation pattern of snow depth and snow cover days exhibited slight regional differences, they generally reveal the decreasing trend over the most area of the Northern Hemisphere. Our work provides evidence that rapid changes in snow depth and snow mass are occurring since the beginning of the 21st century, accompanied by dramatic climate warming.

Xiongxin Xiao et al.

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Xiongxin Xiao et al.

Xiongxin Xiao et al.

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Short summary
Seasonal snow cover is an important component of the climate system and global water cycle that stores large amounts of freshwater. Our research attempts to develop a long-term Northern Hemisphere daily snow depth and snow water equivalent product data using a new algorithm applying in historical passive microwave dataset from 1992 to 2016. Our further analysis showed that snow cover has a significant declining trend across the Northern Hemisphere, especially beginning in the new century.
Seasonal snow cover is an important component of the climate system and global water cycle that...
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