Articles | Volume 15, issue 7
https://doi.org/10.5194/essd-15-3223-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-3223-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
26 Jul 2023
Data description paper |
| 26 Jul 2023
| 26 Jul 2023
A new sea ice concentration product in the polar regions derived from the FengYun-3 MWRI sensors
Ying Chen
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan, 430079, China
Ruibo Lei
Key Laboratory for Polar Science of the Ministry of Natural Resources, Polar Research Institute of China, Shanghai, China
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan, 430079, China
Xi Zhao
School of Geospatial Engineering and Science, Sun Yat-Sen University & Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, China
Shengli Wu
Key Laboratory of Radiometric Calibration and Validation for
Environmental Satellites, National Satellite Meteorological Center (National
Center for Space Weather), China Meteorological Administration, Beijing,
China
Innovation Center for FengYun Meteorological Satellite (FYSIC),
Beijing, China
Yue Liu
Jiangsu Provincial Surveying and Mapping Engineering Institute,
Nanjing, China
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan, 430079, China
Pei Fan
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan, 430079, China
Qing Ji
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan, 430079, China
Peng Zhang
Key Laboratory of Radiometric Calibration and Validation for
Environmental Satellites, National Satellite Meteorological Center (National
Center for Space Weather), China Meteorological Administration, Beijing,
China
Innovation Center for FengYun Meteorological Satellite (FYSIC),
Beijing, China
Xiaoping Pang
CORRESPONDING AUTHOR
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan, 430079, China
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We provide a dataset of snow water equivalent, the depth of liquid water that results from melting a given depth of snow. The dataset contains 11 071 sites over the Northern Hemisphere, spans the period 1950–2022, and is based on daily observations of snow depth on the ground and a model. The dataset fills a lack of accessible historical ground snow data, and it can be used for a variety of applications such as the impact of climate change on global and regional snow and water resources.
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
Short summary
Short summary
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.
Yan Huang, Jiahui Xu, Jingyi Xu, Yelei Zhao, Bailang Yu, Hongxing Liu, Shujie Wang, Wanjia Xu, Jianping Wu, and Zhaojun Zheng
Earth Syst. Sci. Data, 14, 4445–4462, https://doi.org/10.5194/essd-14-4445-2022, https://doi.org/10.5194/essd-14-4445-2022, 2022
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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.
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Short summary
The sea ice concentration product derived from the Microwave Radiation Image sensors on board the FengYun-3 satellites can reasonably and independently identify the seasonal and long-term changes of sea ice, as well as extreme cases of annual maximum and minimum sea ice extent in polar regions. It is comparable with other sea ice concentration products and applied to the studies of climate and marine environment.
The sea ice concentration product derived from the Microwave Radiation Image sensors on board...
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