The Impact of "Bad" Argo Profiles on Ocean Data Assimilation  

作　　者：YAN Chang-Xiang ZHU Jiang 

机构地区：[1]International Center for Climate and Environment Science, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China [2]State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry （LAPC）, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

出　　处：《Atmospheric and Oceanic Science Letters》2010年第2期59-63,共5页大气和海洋科学快报（英文版）

基　　金：supported by the 973 Program(Grant No.2006CB403606);the Chinese Academy of Sciences(Grant Nos.KZCX2-YW-143 and KZCX2-YW-202);the 863 Program (Grant No.2009AA12Z138);the National Natural Science Foundation of China (Grant Nos.40606008,40437017,and 40221503)

摘　　要：Recent studies have found cold biases in a fraction of Argo profiles (hereinafter referred to as bad Array for Real-time Geostrophic Oceanography (Argo) profiles) due to the pressure drifts during 2003 and 2006. These bad Argo profiles have had an important impact on in situ observation-based global ocean heat content esti- mates. This study investigated the impact of bad Argo profiles on ocean data assimilation results that were based on observations from diverse ocean observation systems, such as in situ profiles (e.g., Argo, expendable bathy- thermograph (XBT), and Tropical Atmosphere Ocean (TAO), remote-sensing sea surface temperature products and satellite altimetry between 2004 and 2006. Results from this work show that the upper ocean heat content analysis is vulnerable to bad Argo profiles and demon- strate a cooling trend in the studied period despite the multiple independent data types that were assimilated. When the bad Argo profiles were excluded from the as- similation, the decreased heat content disappeared and a warming occurred. Combination of satellite altimetry and mass variation data from gravity satellite demonstrated an increase, which agrees well with the increased heat con- tent. Additionally, when an additional Argo profile quality control procedure was utilized that simply removed the profiles that presented static unstable water columns, the results were very similar to those obtained when the bad Argo profiles were excluded from the assimilation. This indicates that an ocean data assimilation that uses multiple data sources with improved quality control could be less vulnerable to a major observation system failure, such as a bad Argo event.Recent studies have found cold biases in a fraction of Argo profiles （hereinafter referred to as bad Array for Real-time Geostrophic Oceanography （Argo） profiles） due to the pressure drifts during 2003 and 2006. These bad Argo profiles have had an important impact on in situ observation-based global ocean heat content estimates. This study investigated the impact of bad Argo profiles on ocean data assimilation results that were based on observations from diverse ocean observation systems, such as in situ profiles （e.g., Argo, expendable bathythermograph （XBT）, and Tropical Atmosphere Ocean （TAO）, remote-sensing sea surface temperature products and satellite altimetry between 2004 and 2006. Results from this work show that the upper ocean heat content analysis is vulnerable to bad Argo profiles and demonstrate a cooling trend in the studied period despite the multiple independent data types that were assimilated. When the bad Argo profiles were excluded from the assimilation, the decreased heat content disappeared and a warming occurred. Combination of satellite altimetry and mass variation data from gravity satellite demonstrated an increase, which agrees well with the increased heat content. Additionally, when an additional Argo profile quality control procedure was utilized that simply removed the profiles that presented static unstable water columns, the results were very similar to those obtained when the bad Argo profiles were excluded from the assimilation. This indicates that an ocean data assimilation that uses multiple data sources with improved quality control could be less vulnerable to a major observation system failure, such as a bad Argo event.

关 键 词：data assimilation ARGO heat content ensemble optimal interpolation 

分 类 号：P456.7[天文地球—大气科学及气象学] P7