Estimation of the Aerosol Radiative Effect over the Tibetan Plateau Based on the Latest CALIPSO Product
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Based on the CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation) Version 4.10 products released on 8 November 2016, the Level 2 (L2) aerosol product over the Tibetan Plateau (TP) is evaluated and the aerosol radiative effect is also estimated in this study. As there are still some missing aerosol data points in the daytime CALIPSO Version 4.10 L2 product, this study re-calculated the aerosol extinction coefficient to explore the aerosol radiative effect over the TP based on the CALIPSO Level 1 (L1) and CloudSat 2B-CLDCLASS-LIDAR products. The energy budget estimation obtained by using the AODs (aerosol optical depths) from calculated aerosol extinction coefficient as an input to a radiative transfer model shows better agreement with the Earth’s Radiant Energy System (CERES) and CloudSat 2B-FLXHR-LIDAR observations than that with the input of AODs from aerosol extinction coefficient from CALIPSO Version 4.10 L2 product. The radiative effect and heating rate of aerosols over the TP are further simulated by using the calculated aerosol extinction coefficient. The dust aerosols may heat the atmosphere by retaining the energy in the layer. The instantaneous heating rate can be as high as 5.5 K day–1 depending on the density of the dust layers. Overall, the dust aerosols significantly affect the radiative energy budget and thermodynamic structure of the air over the TP, mainly by altering the shortwave radiation budget. The significant influence of dust aerosols over the TP on the radiation budget may have important implications for investigating the atmospheric circulation and future regional and global climate.
Key wordsaerosol radiative effect Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Version 4.10 product Tibetan Plateau
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The CALIPSO, CloudSat, and CERES data were obtained from the NASA Langley Research Center Atmospheric Sciences Data Center, and the authors gratefully acknowledge their efforts in making these data available online. We also gratefully acknowledge Q. Fu and K. N. Liou for providing the Fu–Liou model.
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