A long-term monthly dataset of cloud fraction over the Arctic based on multiple satellite products using cumulative distribution function matching and Bayesian maximum entropy
The low accuracy of satellite Cloud fraction (CF) over the Arctic seriously restricts accurate assessment of regional and global radiant energy balance under the changing climate. Previous studies have reported that not a single satellite CF product could satisfy the needs of accuracy and spatio-tem...
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ftzenodo:oai:zenodo.org:7624605 2023-05-15T14:42:12+02:00 A long-term monthly dataset of cloud fraction over the Arctic based on multiple satellite products using cumulative distribution function matching and Bayesian maximum entropy Liu Xinyan He Tao 2022-12-24 https://zenodo.org/record/7624605 https://doi.org/10.5281/zenodo.7624605 unknown doi:10.5281/zenodo.7478918 https://zenodo.org/record/7624605 https://doi.org/10.5281/zenodo.7624605 oai:zenodo.org:7624605 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/other dataset 2022 ftzenodo https://doi.org/10.5281/zenodo.762460510.5281/zenodo.7478918 2023-03-11T02:02:09Z The low accuracy of satellite Cloud fraction (CF) over the Arctic seriously restricts accurate assessment of regional and global radiant energy balance under the changing climate. Previous studies have reported that not a single satellite CF product could satisfy the needs of accuracy and spatio-temporal coverage simultaneously for long-term applications over the Arctic. Merging multiple CF products with complementary properties is an effective way to produce more spatiotemporally complete and accurate CF data record. This study proposed a spatiotemporal statistical data fusion framework based on cumulative distribution function (CDF) matching and Bayesian maximum entropy (BME) method to produce a syncretic 1°×1° CF dataset in the Arctic during 2000-2020. The original datasets contain CF from MOD08/MYD08, CERES-SSF Terra/Aqua, CLARA-A2 AM/PM, PATMOS-x AM/PM, ISCCP-H AM/PM. The fused CF product is more consistent with the active satellite data GEWEX-CALIPSO and the ground-based observation data CRU TS4.05. Dataset Arctic Zenodo Arctic |
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The low accuracy of satellite Cloud fraction (CF) over the Arctic seriously restricts accurate assessment of regional and global radiant energy balance under the changing climate. Previous studies have reported that not a single satellite CF product could satisfy the needs of accuracy and spatio-temporal coverage simultaneously for long-term applications over the Arctic. Merging multiple CF products with complementary properties is an effective way to produce more spatiotemporally complete and accurate CF data record. This study proposed a spatiotemporal statistical data fusion framework based on cumulative distribution function (CDF) matching and Bayesian maximum entropy (BME) method to produce a syncretic 1°×1° CF dataset in the Arctic during 2000-2020. The original datasets contain CF from MOD08/MYD08, CERES-SSF Terra/Aqua, CLARA-A2 AM/PM, PATMOS-x AM/PM, ISCCP-H AM/PM. The fused CF product is more consistent with the active satellite data GEWEX-CALIPSO and the ground-based observation data CRU TS4.05. |
format |
Dataset |
author |
Liu Xinyan He Tao |
spellingShingle |
Liu Xinyan He Tao A long-term monthly dataset of cloud fraction over the Arctic based on multiple satellite products using cumulative distribution function matching and Bayesian maximum entropy |
author_facet |
Liu Xinyan He Tao |
author_sort |
Liu Xinyan |
title |
A long-term monthly dataset of cloud fraction over the Arctic based on multiple satellite products using cumulative distribution function matching and Bayesian maximum entropy |
title_short |
A long-term monthly dataset of cloud fraction over the Arctic based on multiple satellite products using cumulative distribution function matching and Bayesian maximum entropy |
title_full |
A long-term monthly dataset of cloud fraction over the Arctic based on multiple satellite products using cumulative distribution function matching and Bayesian maximum entropy |
title_fullStr |
A long-term monthly dataset of cloud fraction over the Arctic based on multiple satellite products using cumulative distribution function matching and Bayesian maximum entropy |
title_full_unstemmed |
A long-term monthly dataset of cloud fraction over the Arctic based on multiple satellite products using cumulative distribution function matching and Bayesian maximum entropy |
title_sort |
long-term monthly dataset of cloud fraction over the arctic based on multiple satellite products using cumulative distribution function matching and bayesian maximum entropy |
publishDate |
2022 |
url |
https://zenodo.org/record/7624605 https://doi.org/10.5281/zenodo.7624605 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
doi:10.5281/zenodo.7478918 https://zenodo.org/record/7624605 https://doi.org/10.5281/zenodo.7624605 oai:zenodo.org:7624605 |
op_rights |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.5281/zenodo.762460510.5281/zenodo.7478918 |
_version_ |
1766313901385842688 |