Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies.
Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies.
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DOI:
10.1038/s41597-022-01889-z
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发表时间:
2023-01-14
期刊:
影响因子:
9.8
通讯作者:
Albergel, Clement
中科院分区:
文献类型:
--
作者:
Carrea, Laura;Cretaux, Jean-Francois;Liu, Xiaohan;Wu, Yuhao;Calmettes, Beatriz;Duguay, Claude R.;Merchant, Christopher J.;Selmes, Nick;Simis, Stefan G. H.;Warren, Mark;Yesou, Herve;Mueller, Dagmar;Jiang, Dalin;Embury, Owen;Berge-Nguyen, Muriel;Albergel, Clement
A consistent dataset of lake surface water temperature, ice cover, water-leaving reflectance, water level and extent is presented. The collection constitutes the Lakes Essential Climate Variable (ECV) for inland waters. The data span combined satellite observations from 1992 to 2020 inclusive and quantifies over 2000 relatively large lakes, which represent a small fraction of the number of lakes worldwide but a significant fraction of global freshwater surface. Visible and near-infrared optical imagery, thermal imagery and microwave radar data from satellites have been exploited. All observations are provided in a common grid at 1/120° latitude-longitude resolution, jointly in daily files. The data/algorithms have been validated against in situ measurements where possible. Consistency analysis between the variables has guided the development of the joint dataset. It is the most complete collection of consistent satellite observations of the Lakes ECV currently available. Lakes are of significant interest to scientific disciplines such as hydrology, limnology, climatology, biogeochemistry and geodesy. They are a vital resource for freshwater supply, and key sentinels for global environmental change.
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影响因子:
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通讯作者:
Seekell, D. A.
影响因子:
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Dall'Olmo, G;Gitelson, AA;Holz, JC
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Bonnefond, Pascal
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