Articles | Volume 14, issue 9
https://doi.org/10.5194/essd-14-4445-2022
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the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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https://doi.org/10.5194/essd-14-4445-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
29 Sep 2022
Data description paper |
| 29 Sep 2022
| 29 Sep 2022
HMRFS–TP: long-term daily gap-free snow cover products over the Tibetan Plateau from 2002 to 2021 based on hidden Markov random field model
Yan Huang
CORRESPONDING AUTHOR
Key Laboratory of Geographic Information Science, Ministry of
Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Jiahui Xu
Key Laboratory of Geographic Information Science, Ministry of
Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Jingyi Xu
Key Laboratory of Geographic Information Science, Ministry of
Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Yelei Zhao
Key Laboratory of Geographic Information Science, Ministry of
Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Bailang Yu
Key Laboratory of Geographic Information Science, Ministry of
Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Hongxing Liu
Department of Geography, the University of Alabama, Tuscaloosa, AL
35487, USA
Shujie Wang
Department of Geography, Earth and Environmental Systems Institute,
Pennsylvania State University, University Park, PA 16802, USA
Wanjia Xu
Key Laboratory of Geographic Information Science, Ministry of
Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Jianping Wu
Key Laboratory of Geographic Information Science, Ministry of
Education, East China Normal University, Shanghai 200241, China
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Zhaojun Zheng
National Satellite Meteorological Center, Beijing 100081, China
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Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Flavio Pignone, Giulia Bruno, Luca Pulvirenti, Giuseppe Squicciarino, Elisabetta Fiori, Lauro Rossi, Silvia Puca, Alexander Toniazzo, Pietro Giordano, Marco Falzacappa, Sara Ratto, Hervè Stevenin, Antonio Cardillo, Matteo Fioletti, Orietta Cazzuli, Edoardo Cremonese, Umberto Morra di Cella, and Luca Ferraris
Earth Syst. Sci. Data, 15, 639–660, https://doi.org/10.5194/essd-15-639-2023, https://doi.org/10.5194/essd-15-639-2023, 2023
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Snow cover has profound implications for worldwide water supply and security, but knowledge of its amount and distribution across the landscape is still elusive. We present IT-SNOW, a reanalysis comprising daily maps of snow amount and distribution across Italy for 11 snow seasons from September 2010 to August 2021. The reanalysis was validated using satellite images and snow measurements and will provide highly needed data to manage snow water resources in a warming climate.
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Short summary
Reliable snow cover information is important for understating climate change and hydrological cycling. We generate long-term daily gap-free snow products over the Tibetan Plateau (TP) at 500 m resolution from 2002 to 2021 based on the hidden Markov random field model. The accuracy is 91.36 %, and is especially improved during snow transitional period and over complex terrains. This dataset has great potential to study climate change and to facilitate water resource management in the TP.
Reliable snow cover information is important for understating climate change and hydrological...
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