Development of Coupled Data Assimilation with the BCC Climate System Model: Highlighting the Role of Sea‐ice Assimilation for Global Analysis
|Author(s)||Liu X.1, Yao J.1, Wu T1, Zhang S.2, 3, 4, Xu F.5, 6, Zhang L.7, Jie W.1, Zhou W.8, Li Q.1, Liang X.1, Chu M.1, Yan J.1, Nie S.1, Cheng Y.1|
|Affiliation(s)||1 : National Climate Center China Meteorological Administration Beijing, China
2 : Key Laboratory of Physical Oceanography Ministry of Education/Institute for Advanced Ocean Study/Frontiers Science Center for Deep Ocean Multispheres and Earth System (DOMES) Ocean University of China Qingdao ,China
3 : Pilot National Laboratory for Marine Science and Technology (QNLM) Qingdao ,China
4 : International Laboratory for High‐Resolution Earth System Model and Prediction (iHESP) Qingdao, China
5 : Ministry of Education Key Laboratory for Earth System Modeling and Department of Earth System Science Tsinghua University Beijing ,China
6 : Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), China
7 : School of Atmospheric Science Nanjing University Nanjing ,China
8 : South China Sea Institute of Oceanology Chinese Academy of Sciences Guangzhou ,China
|Source||Journal of Advances in Modeling Earth Systems (1942-2466) (American Geophysical Union (AGU)), 2021-04 , Vol. 13 , N. 4 , P. e2020MS002368 (23p.)|
|Note||This article also appears in: Data Assimilation for Earth System Models|
|Keyword(s)||coupled data assimilation, sea‐ice assimilation, ocean analysis, atmosphere analysis|
The coupled data assimilation (CDA) system consisting of ocean, sea‐ice, and atmosphere data assimilation components with the Beijing Climate Center (BCC) Climate System Model has been developed to provide reliable analyses of the atmosphere, ocean, and sea‐ice states. It incorporates ocean temperature/salinity profiles, sea surface temperature, sea level height, and sea‐ice concentration observations at a daily frequency, and atmosphere reanalysis at a 6‐hourly frequency. Results show that the system is capable of realistically reproducing the climatology and variability of ocean, sea‐ice, and atmosphere. The performances in analyzing ocean component are comparable to those of well‐known ocean reanalyses that were once used to initialize the BCC model for climate predictions. A series of experiments with and without sea‐ice observations in the CDA framework are designed to explore the role of sea‐ice data assimilation (DA). The addition of sea‐ice DA exerts very small influence to the analysis of upper ocean temperature over the Arctic area, but leads to an evident reduction of temperature error in the upper 1000 m of ocean south of 60ºS. Particularly, only the inclusion of sea‐ice DA can make the ocean/ocean‐atmosphere DA effective in providing skillful analysis in the high‐latitude Southern Ocean. Furthermore, we find that only on the basis of ocean DA, can the addition of sea‐ice concentration assimilation improve the analysis of tropical tropospheric atmosphere, along with a better analysis of mid‐ and high‐latitude stratospheric atmosphere. These results address the importance of coordination of sea‐ice observations and ocean observations in CDA.
Plain Language Summary
Developing coupled data assimilation (CDA) technique has become an important task for many operational and research centers. Although CDA consisting of multiple assimilation components has made great progress in the past years, the impacts of each individual component, especially the sea‐ice data assimilation (DA), are not fully addressed yet. In this study, we have developed a CDA system and implemented a coordinated assimilation scheme of ocean, sea‐ice, and atmosphere data. This scheme shows reliable performances in analyzing the states of the ocean, sea‐ice,and atmosphere. A series of experiments are conducted to examine the impacts of sea‐ice DA on climate analysis. We stress that the importance of sea‐ice DA can be highlighted only in a multi‐component coordinated assimilation framework. On one hand, on the basis of ocean/ocean‐atmosphere DA, addition of sea‐ice DA can decrease the ocean temperature error in the upper 1000 m of the high‐latitude Southern Ocean. On the other hand, adding sea‐ice DA on the basis of ocean DA can improve the analysis of atmospheric variability in the tropical troposphere and mid‐ and high‐latitude stratosphere. These findings call for more attentions of operational model developers to comprehensively describe the role of sea‐ice DA in climate analysis and forecast.