Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part I. Uncertainties in climate means

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 ind...

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Published in:Journal of Climate
Main Authors: Gulev, Sergej K., Jung, Thomas, Ruprecht, Eberhard
Format: Article in Journal/Newspaper
Language:English
Published: AMS (American Meteorological Society) 2007
Subjects:
Online Access:https://oceanrep.geomar.de/id/eprint/5895/
https://oceanrep.geomar.de/id/eprint/5895/1/JCLI4010.pdf
https://doi.org/10.1175/JCLI4010.1
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spelling ftoceanrep:oai:oceanrep.geomar.de:5895 2023-05-15T18:25:59+02:00 Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part I. Uncertainties in climate means Gulev, Sergej K. Jung, Thomas Ruprecht, Eberhard 2007 text https://oceanrep.geomar.de/id/eprint/5895/ https://oceanrep.geomar.de/id/eprint/5895/1/JCLI4010.pdf https://doi.org/10.1175/JCLI4010.1 en eng AMS (American Meteorological Society) https://oceanrep.geomar.de/id/eprint/5895/1/JCLI4010.pdf Gulev, S. K., Jung, T. and Ruprecht, E. (2007) Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part I. Uncertainties in climate means. Open Access Journal of Climate, 20 (2). pp. 279-301. DOI 10.1175/JCLI4010.1 <https://doi.org/10.1175/JCLI4010.1>. doi:10.1175/JCLI4010.1 info:eu-repo/semantics/openAccess Article PeerReviewed 2007 ftoceanrep https://doi.org/10.1175/JCLI4010.1 2023-04-07T14:51:46Z 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 ... Article in Journal/Newspaper Southern Ocean OceanRep (GEOMAR Helmholtz Centre für Ocean Research Kiel) Southern Ocean Journal of Climate 20 2 279 301
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collection OceanRep (GEOMAR Helmholtz Centre für Ocean Research Kiel)
op_collection_id ftoceanrep
language English
description 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 ...
format Article in Journal/Newspaper
author Gulev, Sergej K.
Jung, Thomas
Ruprecht, Eberhard
spellingShingle Gulev, Sergej K.
Jung, Thomas
Ruprecht, Eberhard
Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part I. Uncertainties in climate means
author_facet Gulev, Sergej K.
Jung, Thomas
Ruprecht, Eberhard
author_sort Gulev, Sergej K.
title Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part I. Uncertainties in climate means
title_short Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part I. Uncertainties in climate means
title_full Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part I. Uncertainties in climate means
title_fullStr Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part I. Uncertainties in climate means
title_full_unstemmed Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part I. Uncertainties in climate means
title_sort estimation of the impact of sampling errors in the vos observations on air-sea fluxes. part i. uncertainties in climate means
publisher AMS (American Meteorological Society)
publishDate 2007
url https://oceanrep.geomar.de/id/eprint/5895/
https://oceanrep.geomar.de/id/eprint/5895/1/JCLI4010.pdf
https://doi.org/10.1175/JCLI4010.1
geographic Southern Ocean
geographic_facet Southern Ocean
genre Southern Ocean
genre_facet Southern Ocean
op_relation https://oceanrep.geomar.de/id/eprint/5895/1/JCLI4010.pdf
Gulev, S. K., Jung, T. and Ruprecht, E. (2007) Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part I. Uncertainties in climate means. Open Access Journal of Climate, 20 (2). pp. 279-301. DOI 10.1175/JCLI4010.1 <https://doi.org/10.1175/JCLI4010.1>.
doi:10.1175/JCLI4010.1
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1175/JCLI4010.1
container_title Journal of Climate
container_volume 20
container_issue 2
container_start_page 279
op_container_end_page 301
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