Improvement in airsea flux estimates derived from satellite observations
A new method is developed to estimate daily turbulent airsea fluxes over the global ocean on a 0.25 degrees grid. The required surface wind speed (w(10)) and specific air humidity (q(10)) at 10m height are both estimated from remotely sensed measurements. w(10) is obtained from the SeaWinds scattero...
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Online Access: | https://archimer.ifremer.fr/doc/00137/24825/23575.pdf https://doi.org/10.1080/01431161.2013.787502 https://archimer.ifremer.fr/doc/00137/24825/ |
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ftarchimer:oai:archimer.ifremer.fr:24825 2023-05-15T17:41:24+02:00 Improvement in airsea flux estimates derived from satellite observations Bentamy, Abderrahim Grodsky, Semyon A. Katsaros, Kristina Mestas-nunez, Alberto M. Blanke, Bruno Desbiolles, Fabien 2013-07 application/pdf https://archimer.ifremer.fr/doc/00137/24825/23575.pdf https://doi.org/10.1080/01431161.2013.787502 https://archimer.ifremer.fr/doc/00137/24825/ eng eng Taylor & Francis Ltd https://archimer.ifremer.fr/doc/00137/24825/23575.pdf doi:10.1080/01431161.2013.787502 https://archimer.ifremer.fr/doc/00137/24825/ 2013 Taylor & Francis info:eu-repo/semantics/openAccess restricted use International Journal Of Remote Sensing (0143-1161) (Taylor & Francis Ltd), 2013-07 , Vol. 34 , N. 14 , P. 5243-5261 text Publication info:eu-repo/semantics/article 2013 ftarchimer https://doi.org/10.1080/01431161.2013.787502 2021-09-23T20:23:00Z A new method is developed to estimate daily turbulent airsea fluxes over the global ocean on a 0.25 degrees grid. The required surface wind speed (w(10)) and specific air humidity (q(10)) at 10m height are both estimated from remotely sensed measurements. w(10) is obtained from the SeaWinds scatterometer on board the QuikSCAT satellite. A new empirical model relating brightness temperatures (T-b) from the Special Sensor Microwave Imager (SSM/I) and q(10) is developed. It is an extension of the author's previous q(10) model. In addition to T-b, the empirical model includes sea surface temperature (SST) and airsea temperature difference data. The calibration of the new empirical q(10) model utilizes q(10) from the latest version of the National Oceanography Centre airsea interaction gridded data set (NOCS2.0). Compared with mooring data, the new satellite q(10) exhibits better statistical results than previous estimates. For instance, the bias, the root mean square (RMS), and the correlation coefficient values estimated from comparisons between satellite and moorings in the northeast Atlantic and the Mediterranean Sea are 0.04gkg(1), 0.87gkg(1), and 0.95, respectively. The new satellite q(10) is used in combination with the newly reprocessed QuikSCAT V3, the latest version of SST analyses provided by the National Climatic Data Center (NCDC), and 10m air temperature estimated from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses (ERA-Interim), to determine three daily gridded turbulent quantities at 0.25 degrees spatial resolution: surface wind stress, latent heat flux (LHF), and sensible heat flux (SHF). Validation of the resulting fields is performed through a comprehensive comparison with daily, in situ values of LHF and SHF from buoys. In the northeast Atlantic basin, the satellite-derived daily LHF has bias, RMS, and correlation of 5Wm(2), 27Wm(2), and 0.89, respectively. For SHF, the statistical parameters are 2Wm(2), 10Wm(2), and 0.94, respectively. At global scale, the new satellite LHF and SHF are compared to NOCS2.0 daily estimates. Both daily fluxes exhibit similar spatial and seasonal variability. The main departures are found at latitudes south of 40 degrees S, where satellite latent and sensible heat fluxes are generally larger. Article in Journal/Newspaper Northeast Atlantic Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer) International Journal of Remote Sensing 34 14 5243 5261 |
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Open Polar |
collection |
Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer) |
op_collection_id |
ftarchimer |
language |
English |
description |
A new method is developed to estimate daily turbulent airsea fluxes over the global ocean on a 0.25 degrees grid. The required surface wind speed (w(10)) and specific air humidity (q(10)) at 10m height are both estimated from remotely sensed measurements. w(10) is obtained from the SeaWinds scatterometer on board the QuikSCAT satellite. A new empirical model relating brightness temperatures (T-b) from the Special Sensor Microwave Imager (SSM/I) and q(10) is developed. It is an extension of the author's previous q(10) model. In addition to T-b, the empirical model includes sea surface temperature (SST) and airsea temperature difference data. The calibration of the new empirical q(10) model utilizes q(10) from the latest version of the National Oceanography Centre airsea interaction gridded data set (NOCS2.0). Compared with mooring data, the new satellite q(10) exhibits better statistical results than previous estimates. For instance, the bias, the root mean square (RMS), and the correlation coefficient values estimated from comparisons between satellite and moorings in the northeast Atlantic and the Mediterranean Sea are 0.04gkg(1), 0.87gkg(1), and 0.95, respectively. The new satellite q(10) is used in combination with the newly reprocessed QuikSCAT V3, the latest version of SST analyses provided by the National Climatic Data Center (NCDC), and 10m air temperature estimated from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses (ERA-Interim), to determine three daily gridded turbulent quantities at 0.25 degrees spatial resolution: surface wind stress, latent heat flux (LHF), and sensible heat flux (SHF). Validation of the resulting fields is performed through a comprehensive comparison with daily, in situ values of LHF and SHF from buoys. In the northeast Atlantic basin, the satellite-derived daily LHF has bias, RMS, and correlation of 5Wm(2), 27Wm(2), and 0.89, respectively. For SHF, the statistical parameters are 2Wm(2), 10Wm(2), and 0.94, respectively. At global scale, the new satellite LHF and SHF are compared to NOCS2.0 daily estimates. Both daily fluxes exhibit similar spatial and seasonal variability. The main departures are found at latitudes south of 40 degrees S, where satellite latent and sensible heat fluxes are generally larger. |
format |
Article in Journal/Newspaper |
author |
Bentamy, Abderrahim Grodsky, Semyon A. Katsaros, Kristina Mestas-nunez, Alberto M. Blanke, Bruno Desbiolles, Fabien |
spellingShingle |
Bentamy, Abderrahim Grodsky, Semyon A. Katsaros, Kristina Mestas-nunez, Alberto M. Blanke, Bruno Desbiolles, Fabien Improvement in airsea flux estimates derived from satellite observations |
author_facet |
Bentamy, Abderrahim Grodsky, Semyon A. Katsaros, Kristina Mestas-nunez, Alberto M. Blanke, Bruno Desbiolles, Fabien |
author_sort |
Bentamy, Abderrahim |
title |
Improvement in airsea flux estimates derived from satellite observations |
title_short |
Improvement in airsea flux estimates derived from satellite observations |
title_full |
Improvement in airsea flux estimates derived from satellite observations |
title_fullStr |
Improvement in airsea flux estimates derived from satellite observations |
title_full_unstemmed |
Improvement in airsea flux estimates derived from satellite observations |
title_sort |
improvement in airsea flux estimates derived from satellite observations |
publisher |
Taylor & Francis Ltd |
publishDate |
2013 |
url |
https://archimer.ifremer.fr/doc/00137/24825/23575.pdf https://doi.org/10.1080/01431161.2013.787502 https://archimer.ifremer.fr/doc/00137/24825/ |
genre |
Northeast Atlantic |
genre_facet |
Northeast Atlantic |
op_source |
International Journal Of Remote Sensing (0143-1161) (Taylor & Francis Ltd), 2013-07 , Vol. 34 , N. 14 , P. 5243-5261 |
op_relation |
https://archimer.ifremer.fr/doc/00137/24825/23575.pdf doi:10.1080/01431161.2013.787502 https://archimer.ifremer.fr/doc/00137/24825/ |
op_rights |
2013 Taylor & Francis info:eu-repo/semantics/openAccess restricted use |
op_doi |
https://doi.org/10.1080/01431161.2013.787502 |
container_title |
International Journal of Remote Sensing |
container_volume |
34 |
container_issue |
14 |
container_start_page |
5243 |
op_container_end_page |
5261 |
_version_ |
1766142926338916352 |