Substantial Uncertainties in Arctic Aerosol Simulations by Microphysical Processes Within the Global Climate‐Aerosol Model CAM‐ATRAS
Substantial Uncertainties in Arctic Aerosol Simulations by Microphysical Processes Within the Global Climate‐Aerosol Model CAM‐ATRAS
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DOI:
10.1029/2022jd036943
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发表时间:
2022-08
期刊:
影响因子:
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通讯作者:
H. Matsui;Mingxu Liu
中科院分区:
文献类型:
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作者:
H. Matsui;Mingxu Liu
Aerosols can modulate the Arctic climate through their interactions with radiation, clouds, and snow and ice surfaces. Atmospheric simulations of Arctic aerosols remain highly uncertain, for which the importance of aerosol microphysical properties and processes has not been properly evaluated. To identify the cause of this large uncertainty, we evaluate the variability ranges of aerosols in the Arctic resulting from uncertainties in various aerosol microphysical properties/processes, including particle size distributions at emission, particle mixing states, activation efficiency, and wet removal processes, by using a global climate‐aerosol model Community Atmosphere Model with the Aerosol Two‐dimensional bin module for foRmation and Aging Simulation. We find that the combined uncertainties associated with these multiple microphysical properties/processes yield a factor of 10–50 differences (maximum‐to‐minimum ratio) in the concentrations and radiative effects of aerosols in the Arctic. Black carbon shows the highest variability among aerosol species because its lower hygroscopicity and higher critical supersaturation cause the fraction of activation and wet removal during transport to be highly sensitive to the model treatment of aerosol and cloud microphysics. Aerosol‐radiation‐cloud interactions at the top of atmosphere vary from −0.40 to +0.30 W m−2 in the Arctic (from the preindustrial to present day) and can be positive or negative depending on the treatment of microphysical properties/processes. These results indicate that microphysical properties/processes are more important than previously thought in aerosol simulations in the Arctic and demonstrate that a better understanding and more sophisticated model representation of aerosol microphysical properties/processes are required to improve the accuracy of Arctic aerosol simulations and their impacts on climate.