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    Analysis of Daytime Cloud Fraction Spatiotemporal Variation over the Arctic from 2000 to 2019 from Multiple Satellite Products

    Source: Journal of Climate:;2022:;volume( 035 ):;issue: 023::page 3995
    Author:
    Xinyan Liu
    ,
    Tao He
    ,
    Lin Sun
    ,
    Xiongxin Xiao
    ,
    Shunlin Liang
    ,
    Siwei Li
    DOI: 10.1175/JCLI-D-22-0007.1
    Publisher: American Meteorological Society
    Abstract: Insufficient understanding of complex Arctic cloud properties introduced large errors in estimating radiant energy balance parameters at the regional and global scales. Comprehensive and reliable cloud information is necessary for improving the accuracy of flux inversion. This study evaluated daytime cloud fraction (CF) uncertainties from 16 available satellite products and estimated the spatiotemporal distributions of Arctic daytime CF during 2000–19. Our results show that the differences among multiple products had significant temporal and spatial heterogeneities. Temporally, the maximum and minimum interproduct discrepancies occurred in April and the summer months, respectively. Spatially, the largest uncertainties were seen over Greenland. Substantial inconsistency also occurred on the central and Pacific sides of the Arctic Ocean. The active satellite product tended to capture more clouds in these two regions. We found that the inconsistencies caused by sensor differences were smaller than those caused by algorithm differences; that is, for MODIS based CF products, the inconsistencies caused by different sensors and different algorithms are ±2% and ±5%, while for AVHRR-based products, these inconsistencies are ±6% and ±15%, respectively. The annual average daytime CF in sunlit months was 70.9% ± 2.93% and increased over the Arctic during study periods. These upward trends might cool the Arctic by approximately 0.05–0.5 W m
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      Analysis of Daytime Cloud Fraction Spatiotemporal Variation over the Arctic from 2000 to 2019 from Multiple Satellite Products

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4290120
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    contributor authorXinyan Liu
    contributor authorTao He
    contributor authorLin Sun
    contributor authorXiongxin Xiao
    contributor authorShunlin Liang
    contributor authorSiwei Li
    date accessioned2023-04-12T18:43:01Z
    date available2023-04-12T18:43:01Z
    date copyright2022/11/11
    date issued2022
    identifier otherJCLI-D-22-0007.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4290120
    description abstractInsufficient understanding of complex Arctic cloud properties introduced large errors in estimating radiant energy balance parameters at the regional and global scales. Comprehensive and reliable cloud information is necessary for improving the accuracy of flux inversion. This study evaluated daytime cloud fraction (CF) uncertainties from 16 available satellite products and estimated the spatiotemporal distributions of Arctic daytime CF during 2000–19. Our results show that the differences among multiple products had significant temporal and spatial heterogeneities. Temporally, the maximum and minimum interproduct discrepancies occurred in April and the summer months, respectively. Spatially, the largest uncertainties were seen over Greenland. Substantial inconsistency also occurred on the central and Pacific sides of the Arctic Ocean. The active satellite product tended to capture more clouds in these two regions. We found that the inconsistencies caused by sensor differences were smaller than those caused by algorithm differences; that is, for MODIS based CF products, the inconsistencies caused by different sensors and different algorithms are ±2% and ±5%, while for AVHRR-based products, these inconsistencies are ±6% and ±15%, respectively. The annual average daytime CF in sunlit months was 70.9% ± 2.93% and increased over the Arctic during study periods. These upward trends might cool the Arctic by approximately 0.05–0.5 W m
    publisherAmerican Meteorological Society
    titleAnalysis of Daytime Cloud Fraction Spatiotemporal Variation over the Arctic from 2000 to 2019 from Multiple Satellite Products
    typeJournal Paper
    journal volume35
    journal issue23
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-22-0007.1
    journal fristpage3995
    journal lastpage4023
    page3995–4023
    treeJournal of Climate:;2022:;volume( 035 ):;issue: 023
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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