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Sensitivity studies of aerosol data assimilation and direct radiative feedbacks in modeling dust aerosols
Abstract In order to study dust aerosol assimilation and radiative forcing in modeling East Asian dust aerosols and their impacts on the regional atmosphere, a three-dimensional variational data assimilation (3DV) and an aerosol radiative feedback scheme (RAD) are online implemented into a mesoscale numerical weather prediction system GRAPES/CUACE_Dust. Four modeling experiments are conducted: one control running (CTL) excluding 3DV and RAD as well as three sensitive running experiments respectively with 3DV, RAD, the integrated 3DV and RAD (3DV_RAD). The results indicate the 3DV-running shows a distinct improvement in the daily averaged dust concentrations, while the 3DV_RAD performs the better modeling during strong dust storms. The comparisons of the model bias for air temperature, pressure and wind speed from the CTL, RAD, and 3DV_RAD experiments present that the dust direct radiation leads to decreases in the lower tropospheric temperature and increases in the upper tropospheric temperature, which results in enhancing air pressure in the lower troposphere and declining air pressure in the upper troposphere. The 3DV_RAD modeling in the middle and upper troposphere is more reasonable than the RAD modeling, which suggests the importance of integration of aerosol assimilation and radiation forcing in modeling aerosols and meteorological fields.
Highlights ► 3DV improves modeling dust concentration and 3DV_RAD further corrects the modeling. ► 3DV_RAD is more efficiency in enhancing model ability in upper air meteorological fields than that in low and surface. ► Dust radiative feedback is negative at daytime and positive at night time.
Sensitivity studies of aerosol data assimilation and direct radiative feedbacks in modeling dust aerosols
Abstract In order to study dust aerosol assimilation and radiative forcing in modeling East Asian dust aerosols and their impacts on the regional atmosphere, a three-dimensional variational data assimilation (3DV) and an aerosol radiative feedback scheme (RAD) are online implemented into a mesoscale numerical weather prediction system GRAPES/CUACE_Dust. Four modeling experiments are conducted: one control running (CTL) excluding 3DV and RAD as well as three sensitive running experiments respectively with 3DV, RAD, the integrated 3DV and RAD (3DV_RAD). The results indicate the 3DV-running shows a distinct improvement in the daily averaged dust concentrations, while the 3DV_RAD performs the better modeling during strong dust storms. The comparisons of the model bias for air temperature, pressure and wind speed from the CTL, RAD, and 3DV_RAD experiments present that the dust direct radiation leads to decreases in the lower tropospheric temperature and increases in the upper tropospheric temperature, which results in enhancing air pressure in the lower troposphere and declining air pressure in the upper troposphere. The 3DV_RAD modeling in the middle and upper troposphere is more reasonable than the RAD modeling, which suggests the importance of integration of aerosol assimilation and radiation forcing in modeling aerosols and meteorological fields.
Highlights ► 3DV improves modeling dust concentration and 3DV_RAD further corrects the modeling. ► 3DV_RAD is more efficiency in enhancing model ability in upper air meteorological fields than that in low and surface. ► Dust radiative feedback is negative at daytime and positive at night time.
Sensitivity studies of aerosol data assimilation and direct radiative feedbacks in modeling dust aerosols
Wang, Hong (author) / Niu, Tao (author)
Atmospheric Environment ; 64 ; 208-218
2012-09-27
11 pages
Article (Journal)
Electronic Resource
English