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    Estimation of the Impact of Sampling Errors in the VOS Observations on Air–Sea Fluxes. Part I: Uncertainties in Climate Means

    Source: Journal of Climate:;2007:;volume( 020 ):;issue: 002::page 279
    Author:
    Gulev, Sergey
    ,
    Jung, Thomas
    ,
    Ruprecht, Eberhard
    DOI: 10.1175/JCLI4010.1
    Publisher: American Meteorological Society
    Abstract: Sampling uncertainties in the voluntary observing ship (VOS)-based global ocean?atmosphere flux fields were estimated using the NCEP?NCAR reanalysis and ECMWF 40-yr Re-Analysis (ERA-40) as well as seasonal forecasts without data assimilation. Air?sea fluxes were computed from 6-hourly reanalyzed individual variables using state-of-the-art bulk formulas. Individual variables and computed fluxes were subsampled to simulate VOS-like sampling density. Random simulation of the number of VOS observations and simulation of the number of observations with contemporaneous sampling allowed for estimation of random and total sampling uncertainties respectively. Although reanalyses are dependent on VOS, constituting an important part of data assimilation input, it is assumed that the reanalysis fields adequately reproduce synoptic variability at the sea surface. Sampling errors were quantified by comparison of the regularly sampled (i.e., 6 hourly) and subsampled monthly fields of surface variables and fluxes. In poorly sampled regions random sampling errors amount to 2.5°?3°C for air temperature, 3 m s?1 for the wind speed, 2?2.5 g kg?1 for specific humidity, and 15%?20% of the total cloud cover. The highest random sampling errors in surface fluxes were found for the sensible and latent heat flux and range from 30 to 80 W m?2. Total sampling errors in poorly sampled areas may be higher than random ones by 60%. In poorly sampled subpolar latitudes of the Northern Hemisphere and throughout much of the Southern Ocean the total sampling uncertainty in the net heat flux can amount to 80?100 W m?2. The highest values of the uncertainties associated with the interpolation/extrapolation into unsampled grid boxes are found in subpolar latitudes of both hemispheres for the turbulent fluxes, where they can be comparable with the sampling errors. Simple dependencies of the sampling errors on the number of samples and the magnitude of synoptic variability were derived. Sampling errors estimated from different reanalyses and from seasonal forecasts yield qualitatively comparable spatial patterns, in which the actual values of uncertainties are controlled by the magnitudes of synoptic variability. Finally, estimates of sampling uncertainties are compared with the other errors in air?sea fluxes and the reliability of the estimates obtained is discussed.
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      Estimation of the Impact of Sampling Errors in the VOS Observations on Air–Sea Fluxes. Part I: Uncertainties in Climate Means

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4221146
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    contributor authorGulev, Sergey
    contributor authorJung, Thomas
    contributor authorRuprecht, Eberhard
    date accessioned2017-06-09T17:02:43Z
    date available2017-06-09T17:02:43Z
    date copyright2007/01/01
    date issued2007
    identifier issn0894-8755
    identifier otherams-78473.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4221146
    description abstractSampling uncertainties in the voluntary observing ship (VOS)-based global ocean?atmosphere flux fields were estimated using the NCEP?NCAR reanalysis and ECMWF 40-yr Re-Analysis (ERA-40) as well as seasonal forecasts without data assimilation. Air?sea fluxes were computed from 6-hourly reanalyzed individual variables using state-of-the-art bulk formulas. Individual variables and computed fluxes were subsampled to simulate VOS-like sampling density. Random simulation of the number of VOS observations and simulation of the number of observations with contemporaneous sampling allowed for estimation of random and total sampling uncertainties respectively. Although reanalyses are dependent on VOS, constituting an important part of data assimilation input, it is assumed that the reanalysis fields adequately reproduce synoptic variability at the sea surface. Sampling errors were quantified by comparison of the regularly sampled (i.e., 6 hourly) and subsampled monthly fields of surface variables and fluxes. In poorly sampled regions random sampling errors amount to 2.5°?3°C for air temperature, 3 m s?1 for the wind speed, 2?2.5 g kg?1 for specific humidity, and 15%?20% of the total cloud cover. The highest random sampling errors in surface fluxes were found for the sensible and latent heat flux and range from 30 to 80 W m?2. Total sampling errors in poorly sampled areas may be higher than random ones by 60%. In poorly sampled subpolar latitudes of the Northern Hemisphere and throughout much of the Southern Ocean the total sampling uncertainty in the net heat flux can amount to 80?100 W m?2. The highest values of the uncertainties associated with the interpolation/extrapolation into unsampled grid boxes are found in subpolar latitudes of both hemispheres for the turbulent fluxes, where they can be comparable with the sampling errors. Simple dependencies of the sampling errors on the number of samples and the magnitude of synoptic variability were derived. Sampling errors estimated from different reanalyses and from seasonal forecasts yield qualitatively comparable spatial patterns, in which the actual values of uncertainties are controlled by the magnitudes of synoptic variability. Finally, estimates of sampling uncertainties are compared with the other errors in air?sea fluxes and the reliability of the estimates obtained is discussed.
    publisherAmerican Meteorological Society
    titleEstimation of the Impact of Sampling Errors in the VOS Observations on Air–Sea Fluxes. Part I: Uncertainties in Climate Means
    typeJournal Paper
    journal volume20
    journal issue2
    journal titleJournal of Climate
    identifier doi10.1175/JCLI4010.1
    journal fristpage279
    journal lastpage301
    treeJournal of Climate:;2007:;volume( 020 ):;issue: 002
    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
    yabeshDSpacePersian