Improving the thermal structure predictions in the Yellow Sea by conducting targeted observations in the CNOP-identified sensitive areas

Abstract Targeted observation is an appealing procedure for improving model predictions. However, studies on oceanic targeted observations have been largely based on modeling efforts, and there is a need for field validating operations. Here, we report the results of a field targeted observation tha...

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Autores principales:	Kun Liu, Wuhong Guo, Lianglong Da, Jingyi Liu, Huiqin Hu, Baolong Cui
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9822b31b76b7485199b00e0027eb6794
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spelling	oai:doaj.org-article:9822b31b76b7485199b00e0027eb67942021-12-02T17:37:24ZImproving the thermal structure predictions in the Yellow Sea by conducting targeted observations in the CNOP-identified sensitive areas10.1038/s41598-021-98994-72045-2322https://doaj.org/article/9822b31b76b7485199b00e0027eb67942021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-98994-7https://doaj.org/toc/2045-2322Abstract Targeted observation is an appealing procedure for improving model predictions. However, studies on oceanic targeted observations have been largely based on modeling efforts, and there is a need for field validating operations. Here, we report the results of a field targeted observation that is designed based on the sensitive areas identified by the Conditional Nonlinear Optimal Perturbation approach to improve the 7th day thermal structure prediction in the Yellow Sea. By introducing the technique of cycle data assimilation and the new concept of time-varying sensitive areas, an observing strategy is designed and validated by a set of Observing System Simulation Experiments. Then, the impact of targeted observations was investigated by a choreographed field campaign in the summer of 2019. The results of the in-field Observing System Experiments show that, compared to conventional local data assimilation, conducting targeted observations in the sensitive areas can yield more benefit at the verification time. Furthermore, dynamic analysis demonstrates that the refinement of vertical thermal structures is mainly caused by the changes in the upstream horizontal temperature advection driven by the Yellow Sea Cold Water Mass circulation. This study highlights the effectiveness of targeted observations on reducing the forecast uncertainty in the ocean.Kun LiuWuhong GuoLianglong DaJingyi LiuHuiqin HuBaolong CuiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kun Liu Wuhong Guo Lianglong Da Jingyi Liu Huiqin Hu Baolong Cui Improving the thermal structure predictions in the Yellow Sea by conducting targeted observations in the CNOP-identified sensitive areas
description	Abstract Targeted observation is an appealing procedure for improving model predictions. However, studies on oceanic targeted observations have been largely based on modeling efforts, and there is a need for field validating operations. Here, we report the results of a field targeted observation that is designed based on the sensitive areas identified by the Conditional Nonlinear Optimal Perturbation approach to improve the 7th day thermal structure prediction in the Yellow Sea. By introducing the technique of cycle data assimilation and the new concept of time-varying sensitive areas, an observing strategy is designed and validated by a set of Observing System Simulation Experiments. Then, the impact of targeted observations was investigated by a choreographed field campaign in the summer of 2019. The results of the in-field Observing System Experiments show that, compared to conventional local data assimilation, conducting targeted observations in the sensitive areas can yield more benefit at the verification time. Furthermore, dynamic analysis demonstrates that the refinement of vertical thermal structures is mainly caused by the changes in the upstream horizontal temperature advection driven by the Yellow Sea Cold Water Mass circulation. This study highlights the effectiveness of targeted observations on reducing the forecast uncertainty in the ocean.
format	article
author	Kun Liu Wuhong Guo Lianglong Da Jingyi Liu Huiqin Hu Baolong Cui
author_facet	Kun Liu Wuhong Guo Lianglong Da Jingyi Liu Huiqin Hu Baolong Cui
author_sort	Kun Liu
title	Improving the thermal structure predictions in the Yellow Sea by conducting targeted observations in the CNOP-identified sensitive areas
title_short	Improving the thermal structure predictions in the Yellow Sea by conducting targeted observations in the CNOP-identified sensitive areas
title_full	Improving the thermal structure predictions in the Yellow Sea by conducting targeted observations in the CNOP-identified sensitive areas
title_fullStr	Improving the thermal structure predictions in the Yellow Sea by conducting targeted observations in the CNOP-identified sensitive areas
title_full_unstemmed	Improving the thermal structure predictions in the Yellow Sea by conducting targeted observations in the CNOP-identified sensitive areas
title_sort	improving the thermal structure predictions in the yellow sea by conducting targeted observations in the cnop-identified sensitive areas
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/9822b31b76b7485199b00e0027eb6794
work_keys_str_mv	AT kunliu improvingthethermalstructurepredictionsintheyellowseabyconductingtargetedobservationsinthecnopidentifiedsensitiveareas AT wuhongguo improvingthethermalstructurepredictionsintheyellowseabyconductingtargetedobservationsinthecnopidentifiedsensitiveareas AT lianglongda improvingthethermalstructurepredictionsintheyellowseabyconductingtargetedobservationsinthecnopidentifiedsensitiveareas AT jingyiliu improvingthethermalstructurepredictionsintheyellowseabyconductingtargetedobservationsinthecnopidentifiedsensitiveareas AT huiqinhu improvingthethermalstructurepredictionsintheyellowseabyconductingtargetedobservationsinthecnopidentifiedsensitiveareas AT baolongcui improvingthethermalstructurepredictionsintheyellowseabyconductingtargetedobservationsinthecnopidentifiedsensitiveareas
_version_	1718379897378832384

Improving the thermal structure predictions in the Yellow Sea by conducting targeted observations in the CNOP-identified sensitive areas

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