A Dissection of the Inter-Model Spread of the Aerosol Direct Radiative Effect in CMIP6 Models

被引:0
|
作者
Yu, Qiurun [1 ]
Huang, Yi [1 ]
机构
[1] McGill Univ, Dept Atmospher & Ocean Sci, Montreal, PQ, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
aerosol direct radiative effect; CMIP6; inter-model differences; radiative transfer; aerosol-surface multi-scattering; aerosol optical depth; ATMOSPHERE MODEL; UNCERTAINTY;
D O I
10.1029/2023GL105112
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The all-sky Aerosol Direct Radiative Effect (ADRE) varies considerably among global climate models (GCMs), which results from differences in aerosol and atmospheric states and ADRE sensitivity to aerosol-related radiative processes. This study uses a regression method to analyze the inter-model spread of ADRE among the GCMs of the Sixth Coupled Model Intercomparison Projects (CMIP6). The key state variables examined include scattering and absorbing aerosol optical depth, surface albedo, and shortwave cloud radiative effect. We find that differences in state variables and radiative sensitivity explain 67% and 17%, respectively, of the global ADRE anomaly. The ADRE anomaly in different models is dominated by different factors, which sometimes leads to compensating effects. For the global mean ADRE anomaly, aerosol optical depth differences dominate in CNRM-ESM2-1 and GFDL-ESM4 models, while ADRE sensitivity variations to aerosol-only scattering effect dominate in HadGEM3-GC31-LL, MPI-ESM-1-2-HAM, and MRI-ESM2-0 models. Aerosols scatter and absorb solar radiation, impacting the Earth's climate. Global climate models differ in their quantification of this effect. The differences in quantification arise from different state variables, including the aerosol properties and atmospheric conditions. Additionally, the radiative sensitivity of aerosol effect to aerosol-related physical processes varies with models. In this study, we identify the primary causes of the differences in aerosol radiative effect among climate models and quantify their respective impacts by using a regression method. We find that besides the aerosol optical depth, whose influence on aerosol radiative effect is well recognized, the radiative sensitivity of aerosol and surface interactions significantly contributes to the aerosol radiative effect differences in the latest climate models. A regression model is used to dissect the inter-model spread of the all-sky Aerosol Direct Radiative Effect (ADRE) in Sixth Coupled Model Intercomparison Projects ModelsThe model explains 86% of ADRE inter-model spread, with variances in state-variable and radiative sensitivity contributing 67% and 17% eachDifferences in aerosol optical depth and ADRE sensitivity to aerosol-surface interactions drive the spatial variance in global ADRE spread
引用
收藏
页数:10
相关论文
共 50 条
  • [21] On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates
    Vial, Jessica
    Dufresne, Jean-Louis
    Bony, Sandrine
    CLIMATE DYNAMICS, 2013, 41 (11-12) : 3339 - 3362
  • [22] Estimating the CMIP6 Anthropogenic Aerosol Radiative Effects with the Advantage of Prescribed Aerosol Forcing
    Shi, Xiangjun
    Li, Chunhan
    Li, Lijuan
    Zhang, Wentao
    Liu, Jiaojiao
    ATMOSPHERE, 2021, 12 (03)
  • [23] The potential impact of model horizontal resolution on the simulation of atmospheric cloud radiative effect in CMIP6 models
    Lin, Qiao-Jun
    Yu, Jia-Yuh
    TERRESTRIAL ATMOSPHERIC AND OCEANIC SCIENCES, 2022, 33 (01):
  • [24] The potential impact of model horizontal resolution on the simulation of atmospheric cloud radiative effect in CMIP6 models
    Qiao-Jun Lin
    Jia-Yuh Yu
    Terrestrial, Atmospheric and Oceanic Sciences, 2022, 33
  • [25] Intermodel Spread in the Pattern Effect and Its Contribution to Climate Sensitivity in CMIP5 and CMIP6 Models
    Dong, Yue
    Armour, Kyle C.
    Zelinka, Mark D.
    Proistosescu, Cristian
    Battisti, David S.
    Zhou, Chen
    Andrews, Timothy
    JOURNAL OF CLIMATE, 2020, 33 (18) : 7755 - 7775
  • [26] An evaluation of the Arctic clouds and surface radiative fluxes in CMIP6 models
    Jianfen Wei
    Zhaomin Wang
    Mingyi Gu
    Jing-Jia Luo
    Yunhe Wang
    Acta Oceanologica Sinica, 2021, 40 (01) : 85 - 102
  • [27] An evaluation of the Arctic clouds and surface radiative fluxes in CMIP6 models
    Jianfen Wei
    Zhaomin Wang
    Mingyi Gu
    Jing-Jia Luo
    Yunhe Wang
    Acta Oceanologica Sinica, 2021, 40 : 85 - 102
  • [28] The trend and spatial spread of multisectoral climate extremes in CMIP6 models
    Adeyeri, Oluwafemi E.
    Zhou, Wen
    Wang, Xuan
    Zhang, Ruhua
    Laux, Patrick
    Ishola, Kazeem A.
    Usman, Muhammad
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [29] An evaluation of the Arctic clouds and surface radiative fluxes in CMIP6 models
    Wei, Jianfen
    Wang, Zhaomin
    Gu, Mingyi
    Luo, Jing-Jia
    Wang, Yunhe
    ACTA OCEANOLOGICA SINICA, 2021, 40 (01) : 85 - 102
  • [30] The trend and spatial spread of multisectoral climate extremes in CMIP6 models
    Oluwafemi E. Adeyeri
    Wen Zhou
    Xuan Wang
    Ruhua Zhang
    Patrick Laux
    Kazeem A. Ishola
    Muhammad Usman
    Scientific Reports, 12