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    Evaluation of Six Atmospheric Reanalyses over Arctic Sea Ice from Winter to Early Summer

    Source: Journal of Climate:;2019:;volume 032:;issue 014::page 4121
    Author:
    Graham, Robert M.
    ,
    Cohen, Lana
    ,
    Ritzhaupt, Nicole
    ,
    Segger, Benjamin
    ,
    Graversen, Rune G.
    ,
    Rinke, Annette
    ,
    Walden, Von P.
    ,
    Granskog, Mats A.
    ,
    Hudson, Stephen R.
    DOI: 10.1175/JCLI-D-18-0643.1
    Publisher: American Meteorological Society
    Abstract: AbstractThis study evaluates the performance of six atmospheric reanalyses (ERA-Interim, ERA5, JRA-55, CFSv2, MERRA-2, and ASRv2) over Arctic sea ice from winter to early summer. The reanalyses are evaluated using observations from the Norwegian Young Sea Ice campaign (N-ICE2015), a 5-month ice drift in pack ice north of Svalbard. N-ICE2015 observations include surface meteorology, vertical profiles from radiosondes, as well as radiative and turbulent heat fluxes. The reanalyses simulate surface analysis variables well throughout the campaign, but have difficulties with most forecast variables. Wintertime (January?March) correlation coefficients between the reanalyses and observations are above 0.90 for the surface pressure, 2-m temperature, total column water vapor, and downward longwave flux. However, all reanalyses have a positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3?19 W m?2. These biases are associated with poorly represented surface inversions and are largest during cold-stable periods. Notably, the recent ERA5 and ASRv2 datasets have some of the largest temperature and net longwave biases, respectively. During spring (April?May), reanalyses fail to simulate observed persistent cloud layers. Therefore they overestimate the net shortwave flux (5?79 W m?2) and underestimate the net longwave flux (8?38 W m?2). Promisingly, ERA5 provides the best estimates of downward radiative fluxes in spring and summer, suggesting improved forecasting of Arctic cloud cover. All reanalyses exhibit large negative (upward) residual heat flux biases during winter, and positive (downward) biases during summer. Turbulent heat fluxes over sea ice are simulated poorly in all seasons.
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      Evaluation of Six Atmospheric Reanalyses over Arctic Sea Ice from Winter to Early Summer

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4263177
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    contributor authorGraham, Robert M.
    contributor authorCohen, Lana
    contributor authorRitzhaupt, Nicole
    contributor authorSegger, Benjamin
    contributor authorGraversen, Rune G.
    contributor authorRinke, Annette
    contributor authorWalden, Von P.
    contributor authorGranskog, Mats A.
    contributor authorHudson, Stephen R.
    date accessioned2019-10-05T06:42:43Z
    date available2019-10-05T06:42:43Z
    date copyright5/9/2019 12:00:00 AM
    date issued2019
    identifier otherJCLI-D-18-0643.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4263177
    description abstractAbstractThis study evaluates the performance of six atmospheric reanalyses (ERA-Interim, ERA5, JRA-55, CFSv2, MERRA-2, and ASRv2) over Arctic sea ice from winter to early summer. The reanalyses are evaluated using observations from the Norwegian Young Sea Ice campaign (N-ICE2015), a 5-month ice drift in pack ice north of Svalbard. N-ICE2015 observations include surface meteorology, vertical profiles from radiosondes, as well as radiative and turbulent heat fluxes. The reanalyses simulate surface analysis variables well throughout the campaign, but have difficulties with most forecast variables. Wintertime (January?March) correlation coefficients between the reanalyses and observations are above 0.90 for the surface pressure, 2-m temperature, total column water vapor, and downward longwave flux. However, all reanalyses have a positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3?19 W m?2. These biases are associated with poorly represented surface inversions and are largest during cold-stable periods. Notably, the recent ERA5 and ASRv2 datasets have some of the largest temperature and net longwave biases, respectively. During spring (April?May), reanalyses fail to simulate observed persistent cloud layers. Therefore they overestimate the net shortwave flux (5?79 W m?2) and underestimate the net longwave flux (8?38 W m?2). Promisingly, ERA5 provides the best estimates of downward radiative fluxes in spring and summer, suggesting improved forecasting of Arctic cloud cover. All reanalyses exhibit large negative (upward) residual heat flux biases during winter, and positive (downward) biases during summer. Turbulent heat fluxes over sea ice are simulated poorly in all seasons.
    publisherAmerican Meteorological Society
    titleEvaluation of Six Atmospheric Reanalyses over Arctic Sea Ice from Winter to Early Summer
    typeJournal Paper
    journal volume32
    journal issue14
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-18-0643.1
    journal fristpage4121
    journal lastpage4143
    treeJournal of Climate:;2019:;volume 032:;issue 014
    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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