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Preprints
https://doi.org/10.5194/acp-2020-60
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-60
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  17 Feb 2020

17 Feb 2020

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A revised version of this preprint was accepted for the journal ACP and is expected to appear here in due course.

Solar radiative forcing of aerosol particles near the Taklimakan desert during the Dust Aerosol Observation-Kashi campaign in Spring 2019

Li Li1, Zhengqiang Li1, Wenyuan Chang2, Yang Ou1, Philippe Goloub3, Chengzhe Li4, Kaitao Li1, Qiaoyun Hu3, Jianping Wang1, and Manfred Wendisch5 Li Li et al.
  • 1Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
  • 2Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • 3Laboratoire d’Optique Atmosphérique, Université de Lille 1/CNRS, Lille 59655, France
  • 4Department of Chemical and Biochemical Engineering, University of Iowa, Iowa 52242, USA
  • 5Leipzig Institute for Meteorology, Leipzig University, Leipzig 04103, Germany

Abstract. The Taklimakan desert is a main and continuous source of Asian dust particles causing a significant direct aerosol solar radiative forcing (ASRF). In order to improve the accuracy of the estimation of dust radiative forcing effects, the Dust Aerosol Observation-Kashi (DAO-K) campaign was carried out near the Taklimakan desert in April 2019. The objective of the campaign is to provide comprehensive parameters such as: dust optical and microphysical properties, vertical distribution and surface albedo, for the calculation of ASRF. The measurements were employed in radiative transfer (RT) simulations and the estimations are improved by considering the actual measured atmospheric profiles and diurnal variations of land surface albedo in addition to reliable aerosol parameters. The RT model estimates the ASRF results in average daily mean cooling effects of −19 W m−2 at the top of atmosphere and −36 W m−2 at the bottom of atmosphere during the DAO-K campaign. The Weather Research and Forecasting model with Chemistry (WRF-Chem) with assimilations of the aerosol optical depth and PM2.5 and PM10 concentrations measurements is prone to overestimate the radiative forcing effects of dust aerosols. The percent difference of daily mean ASRF between the two simulations are greater than 50 % in heavy dust episode. Ground-based observations of downward irradiances have validated that the RT simulations are in good agreement with simultaneous observations, whereas the WRF-Chem estimations exhibit obvious discrepancy with these independent measurements. Data assimilations can partly reduce the discrepancy, but there is still room for improving the WRF-Chem simulation of dust aerosol radiative forcing.

Li Li et al.

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Li Li et al.

Li Li et al.

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Latest update: 07 Aug 2020
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Short summary
Comprehensive aerosol, atmospheric, and surface parameters were applied in radiative transfer model simulation to achieve a high-accuracy estimation of dust radiative forcing effects with daily mean cooling effects of −19 W m−2 at the top of atmosphere and −36 W m−2 at the bottom of atmosphere during the Dust Aerosol Observation-Kashi campaign. Data assimilations can obvious improve the WRF-Chem simulations, but there is still room for enhancing the WRF-Chem estimation of dust radiative forcing.
Comprehensive aerosol, atmospheric, and surface parameters were applied in radiative transfer...
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