An evaluation of the Arctic clouds and surface radiative fluxes in CMIP6 models

Jianfen Wei; Zhaomin Wang; Mingyi Gu; Jing-Jia Luo; Yunhe Wang

doi:10.1007/s13131-021-1705-6

Volume 40 Issue 1

Feb. 2021

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Jianfen Wei, Zhaomin Wang, Mingyi Gu, Jing-Jia Luo, Yunhe Wang. An evaluation of the Arctic clouds and surface radiative fluxes in CMIP6 models[J]. Acta Oceanologica Sinica, 2021, 40(1): 85-102. doi: 10.1007/s13131-021-1705-6

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Jianfen Wei, Zhaomin Wang, Mingyi Gu, Jing-Jia Luo, Yunhe Wang. An evaluation of the Arctic clouds and surface radiative fluxes in CMIP6 models[J]. Acta Oceanologica Sinica, 2021, 40(1): 85-102. doi: 10.1007/s13131-021-1705-6

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An evaluation of the Arctic clouds and surface radiative fluxes in CMIP6 models

doi: 10.1007/s13131-021-1705-6

Jianfen Wei^{1, 2},
Zhaomin Wang^{3, 4
,
,},
Mingyi Gu⁵,
Jing-Jia Luo^{2, 6
,
,},
Yunhe Wang^{7, 8}

1.
School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
2.
Institute for Climate and Application Research (ICAR), Nanjing University of Information Science and Technology, Nanjing 210044, China
3.
College of Oceanography, Hohai University, Nanjing 210098, China
4.
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
5.
School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
6.
Key Laboratory of Meteorological Disaster of Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China
7.
CAS Key Laboratory of Marine Geology and Environment, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
8.
University of Chinese Academy of Sciences, Beijing 100049, China

Funds: The Major State Basic Research Development Program of China under contract No. 2016YFA0601804; the Global Change Research Program of China under contract No. 2015CB953900; the National Natural Science Foundation of China under contract Nos 41941007 and 41876220; the China Postdoctoral Science Foundation under contract No. 2020M681661.

More Information

Corresponding author: E-mail: zhaomin.wang@hhu.edu.cn; jjluo@nuist.edu.cn
Received Date: 2020-05-09
Accepted Date: 2020-06-22

Available Online: 2021-04-21

Publish Date: 2021-01-25

Abstract

Abstract

To assess the performances of state-of-the-art global climate models on simulating the Arctic clouds and surface radiation balance, the 2001–2014 Arctic Basin surface radiation budget, clouds, and the cloud radiative effects (CREs) in 22 coupled model intercomparison project 6 (CMIP6) models are evaluated against satellite observations. For the results from CMIP6 multi-model mean, cloud fraction (CF) peaks in autumn and is lowest in winter and spring, consistent with that from three satellite observation products (CloudSat-CALIPSO, CERES-MODIS, and APP-x). Simulated CF also shows consistent spatial patterns with those in observations. However, almost all models overestimate the CF amount throughout the year when compared to CERES-MODIS and APP-x. On average, clouds warm the surface of the Arctic Basin mainly via the longwave (LW) radiation cloud warming effect in winter. Simulated surface energy loss of LW is less than that in CERES-EBAF observation, while the net surface shortwave (SW) flux is underestimated. The biases may result from the stronger cloud LW warming effect and SW cooling effect from the overestimated CF by the models. These two biases compensate each other, yielding similar net surface radiation flux between model output (3.0 W/m²) and CERES-EBAF observation (6.1 W/m²). During 2001–2014, significant increasing trend of spring CF is found in the multi-model mean, consistent with previous studies based on surface and satellite observations. Although most of the 22 CMIP6 models show common seasonal cycles of CF and liquid water path/ice water path (LWP/IWP), large inter-model spreads exist in the amounts of CF and LWP/IWP throughout the year, indicating the influences of different cloud parameterization schemes used in different models. Cloud Feedback Model Intercomparison Project (CFMIP) observation simulator package (COSP) is a great tool to accurately assess the performance of climate models on simulating clouds. More intuitive and credible evaluation results can be obtained based on the COSP model output. In the future, with the release of more COSP output of CMIP6 models, it is expected that those inter-model spreads and the model-observation biases can be substantially reduced. Longer term active satellite observations are also necessary to evaluate models’ cloud simulations and to further explore the role of clouds in the rapid Arctic climate changes.
- Arctic Basin,
- surface radiation budget,
- cloud radiative effect (CRE),
- CMIP6 models,
- CERES,
- CloudSat-CALIPSO,
- APP-x

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References(94)

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