Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction
A conceptual coupled ocean-atmosphere model was used to study coupled ensemble data assimilation schemes with a focus on the role of ocean-atmosphere interaction in the assimilation. The optimal scheme was the fully coupled data assimilation scheme that employs the coupled covariance matrix and assi...
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大气科学进展英文版
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Online Access: | https://hdl.handle.net/20.500.11897/220955 https://doi.org/10.1007/s00376-013-2268-z |
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ftpekinguniv:oai:localhost:20.500.11897/220955 2023-05-15T17:34:41+02:00 Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction Liu Zhengyu Wu Shu Zhang Shaoqing Liu Yun Rong Xinyao Wu, S (reprint author), Univ Wisconsin, Nelson Inst Ctr Climat Res, Madison, WI 53706 USA. Peking Univ, Lab Climate Ocean & Atmosphere Studies, Beijing 100871, Peoples R China. Univ Wisconsin, Nelson Inst Ctr Climat Res, Madison, WI 53706 USA. Univ Wisconsin, Dept Atmospher & Ocean Sci, Madison, WI 53706 USA. NOAA, Geophys Fluid Dynam Lab, Princeton, NJ 08540 USA. China Meteorol Adm, Meteorol Res Inst, Beijing 100081, Peoples R China. 2013 https://hdl.handle.net/20.500.11897/220955 https://doi.org/10.1007/s00376-013-2268-z en eng 大气科学进展英文版 ADVANCES IN ATMOSPHERIC SCIENCES.2013,30,(5),1235-1248. 814106 0256-1530 http://hdl.handle.net/20.500.11897/220955 doi:10.1007/s00376-013-2268-z WOS:000323278000001 SCI ensemble Kalman filter coupled model ocean-atmosphere interaction coupled covariance NORTH-ATLANTIC EL-NINO PREDICTABILITY CIRCULATION PREDICTION FORECASTS SYSTEM ENSO Journal 2013 ftpekinguniv https://doi.org/20.500.11897/220955 https://doi.org/10.1007/s00376-013-2268-z 2021-08-01T08:38:25Z A conceptual coupled ocean-atmosphere model was used to study coupled ensemble data assimilation schemes with a focus on the role of ocean-atmosphere interaction in the assimilation. The optimal scheme was the fully coupled data assimilation scheme that employs the coupled covariance matrix and assimilates observations in both the atmosphere and ocean. The assimilation of synoptic atmospheric variability that captures the temporal fluctuation of the weather noise was found to be critical for the estimation of not only the atmospheric, but also oceanic states. The synoptic atmosphere observation was especially important in the mid-latitude system, where oceanic variability is driven by weather noise. The assimilation of synoptic atmospheric variability in the coupled model improved the atmospheric variability in the analysis and the subsequent forecasts, reducing error in the surface forcing and, in turn, in the ocean state. Atmospheric observation was able to further improve the oceanic state estimation directly through the coupled covariance between the atmosphere and ocean states. Relative to the mid-latitude system, the tropical system was influenced more by ocean-atmosphere interaction and, thus, the assimilation of oceanic observation becomes more important for the estimation of the ocean and atmosphere. http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000323278000001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 Meteorology & Atmospheric Sciences SCI(E) 中国科技核心期刊(ISTIC) 中国科学引文数据库(CSCD) 9 ARTICLE 5 1235-1248 30 Journal/Newspaper North Atlantic Peking University Institutional Repository (PKU IR) Advances in Atmospheric Sciences 30 5 1235 1248 |
institution |
Open Polar |
collection |
Peking University Institutional Repository (PKU IR) |
op_collection_id |
ftpekinguniv |
language |
English |
topic |
ensemble Kalman filter coupled model ocean-atmosphere interaction coupled covariance NORTH-ATLANTIC EL-NINO PREDICTABILITY CIRCULATION PREDICTION FORECASTS SYSTEM ENSO |
spellingShingle |
ensemble Kalman filter coupled model ocean-atmosphere interaction coupled covariance NORTH-ATLANTIC EL-NINO PREDICTABILITY CIRCULATION PREDICTION FORECASTS SYSTEM ENSO Liu Zhengyu Wu Shu Zhang Shaoqing Liu Yun Rong Xinyao Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction |
topic_facet |
ensemble Kalman filter coupled model ocean-atmosphere interaction coupled covariance NORTH-ATLANTIC EL-NINO PREDICTABILITY CIRCULATION PREDICTION FORECASTS SYSTEM ENSO |
description |
A conceptual coupled ocean-atmosphere model was used to study coupled ensemble data assimilation schemes with a focus on the role of ocean-atmosphere interaction in the assimilation. The optimal scheme was the fully coupled data assimilation scheme that employs the coupled covariance matrix and assimilates observations in both the atmosphere and ocean. The assimilation of synoptic atmospheric variability that captures the temporal fluctuation of the weather noise was found to be critical for the estimation of not only the atmospheric, but also oceanic states. The synoptic atmosphere observation was especially important in the mid-latitude system, where oceanic variability is driven by weather noise. The assimilation of synoptic atmospheric variability in the coupled model improved the atmospheric variability in the analysis and the subsequent forecasts, reducing error in the surface forcing and, in turn, in the ocean state. Atmospheric observation was able to further improve the oceanic state estimation directly through the coupled covariance between the atmosphere and ocean states. Relative to the mid-latitude system, the tropical system was influenced more by ocean-atmosphere interaction and, thus, the assimilation of oceanic observation becomes more important for the estimation of the ocean and atmosphere. http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000323278000001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 Meteorology & Atmospheric Sciences SCI(E) 中国科技核心期刊(ISTIC) 中国科学引文数据库(CSCD) 9 ARTICLE 5 1235-1248 30 |
author2 |
Wu, S (reprint author), Univ Wisconsin, Nelson Inst Ctr Climat Res, Madison, WI 53706 USA. Peking Univ, Lab Climate Ocean & Atmosphere Studies, Beijing 100871, Peoples R China. Univ Wisconsin, Nelson Inst Ctr Climat Res, Madison, WI 53706 USA. Univ Wisconsin, Dept Atmospher & Ocean Sci, Madison, WI 53706 USA. NOAA, Geophys Fluid Dynam Lab, Princeton, NJ 08540 USA. China Meteorol Adm, Meteorol Res Inst, Beijing 100081, Peoples R China. |
format |
Journal/Newspaper |
author |
Liu Zhengyu Wu Shu Zhang Shaoqing Liu Yun Rong Xinyao |
author_facet |
Liu Zhengyu Wu Shu Zhang Shaoqing Liu Yun Rong Xinyao |
author_sort |
Liu Zhengyu |
title |
Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction |
title_short |
Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction |
title_full |
Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction |
title_fullStr |
Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction |
title_full_unstemmed |
Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction |
title_sort |
ensemble data assimilation in a simple coupled climate model: the role of ocean-atmosphere interaction |
publisher |
大气科学进展英文版 |
publishDate |
2013 |
url |
https://hdl.handle.net/20.500.11897/220955 https://doi.org/10.1007/s00376-013-2268-z |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
SCI |
op_relation |
ADVANCES IN ATMOSPHERIC SCIENCES.2013,30,(5),1235-1248. 814106 0256-1530 http://hdl.handle.net/20.500.11897/220955 doi:10.1007/s00376-013-2268-z WOS:000323278000001 |
op_doi |
https://doi.org/20.500.11897/220955 https://doi.org/10.1007/s00376-013-2268-z |
container_title |
Advances in Atmospheric Sciences |
container_volume |
30 |
container_issue |
5 |
container_start_page |
1235 |
op_container_end_page |
1248 |
_version_ |
1766133600066994176 |