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Simulating and Evaluating Global Aerosol Distributions With the Online Aerosol‐Coupled CAS‐FGOALS Model
Author(s) -
Wang Hao,
Dai Tie,
Goto Daisuke,
Bao Qing,
He Bian,
Liu Yimin,
Takemura Toshihiko,
Nakajima Teruyuki,
Shi Guangyu
Publication year - 2020
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1029/2019jd032097
Subject(s) - aeronet , aerosol , environmental science , satellite , angstrom exponent , atmospheric sciences , albedo (alchemy) , relative humidity , single scattering albedo , meteorology , remote sensing , climatology , geography , geology , physics , art , astronomy , performance art , art history
We implement an existing aerosol module named Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) in the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System (CAS‐FGOALS) model and simulate the global aerosol properties over 2002–2014. The simulated surface mass concentrations of individual aerosols generally reproduce the observed ones. The simulated spatial‐temporal distributions of the aerosol optical depths (AODs) are evaluated with multisource satellite retrievals, and the simulated AOD, Ångström Exponent (AE), and single scattering albedo (SSA) are further evaluated with the ground‐based Aerosol Robotic Network (AERONET) measurements. The spatial distribution of the modeled AOD is found to be generally comparable to the satellite retrievals. The interannual and seasonal variations of the modeled AOD over various aerosol regimes are also overall consistent with the AERONET observations. With respect to the AE, our model can reproduce the interannual variations fairly well over the dust dominant regions, and generally capture the seasonal variations over the industrial domain regions. Over the industrial domain regions, however, the systematic underestimation of the simulated AE is found, which is in part due to the biases of wind fields and overestimation of the relative humidity (RH) by the host model. With respect to the SSA, our model can also generally reproduce the observed seasonal variations, while the modeled values are typically lower than the observations, especially over North Africa.