2021
DOI: 10.1029/2020ms002368
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Development of Coupled Data Assimilation With the BCC Climate System Model: Highlighting the Role of Sea‐Ice Assimilation for Global Analysis

Abstract: 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 capab… Show more

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Cited by 15 publications
(17 citation statements)
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“…BCC-CSM2-MR is a coupled climate model developed by the Beijing Climate Center (BCC). This model participates in the current Coupled Model Inter-comparison Project, CMIP6, and the sub-seasonal to seasonal (S2S) prediction project and also provides routine seasonal forecasts (Liu et al, 2019;Liu et al, 2021;Zhu et al, 2021). The evaluation indicates that BCC-CSM2-MR shows better performance in the tropospheric air temperature and circulation in East Asia and Indian monsoon region (e.g., Wu et al, 2019;Kumar and Sarthi, 2021).…”
Section: Introductionmentioning
confidence: 99%
“…BCC-CSM2-MR is a coupled climate model developed by the Beijing Climate Center (BCC). This model participates in the current Coupled Model Inter-comparison Project, CMIP6, and the sub-seasonal to seasonal (S2S) prediction project and also provides routine seasonal forecasts (Liu et al, 2019;Liu et al, 2021;Zhu et al, 2021). The evaluation indicates that BCC-CSM2-MR shows better performance in the tropospheric air temperature and circulation in East Asia and Indian monsoon region (e.g., Wu et al, 2019;Kumar and Sarthi, 2021).…”
Section: Introductionmentioning
confidence: 99%
“…Note that the BCC1 and BCC2 participate in the S2S Project Phases I and II, respectively. The BCC2 has been substantially improved compared with its previous version, with a higher atmospheric resolution, a new data assimilation scheme, and modified convection and cloud physical processes (Wu et al ., 2019; 2021; Liu et al ., 2021). Therefore, it is meaningful to compare the practical MJO prediction skills of these two model versions.…”
Section: Methodsmentioning
confidence: 99%
“…The relaxation time scale is set to 30 min. More details can be found in Liu et al (2021). After the data assimilation, the model is capable of realistically reproducing the climatology and variability of ocean, sea-ice, and atmosphere (Liu et al, 2021).…”
Section: The Prediction Systemmentioning
confidence: 99%