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https://doi.org/10.5194/acp-2020-825
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-825
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Sep 2020

14 Sep 2020

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This preprint is currently under review for the journal ACP.

Improving the Sectional MOSAIC Aerosol models of WRF-Chem with the revised Gridpoint Statistical Interpolation System and multi-wavelength aerosol optical measurements: DAO-K experiment 2019 at Kashi, near the Taklamakan Desert, northwestern China

Wenyuan Chang1, Ying Zhang2, Zhengqiang Li2, Jie Chen3, and Kaitao Li2 Wenyuan Chang et al.
  • 1State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • 2Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
  • 3National Meteorological Information Center, China Meteorological Administration, Beijing 100081, China

Abstract. The Gridpoint Statistical Interpolation data assimilation (DA) system was developed for the four-size bin sectional Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosol mechanism in the Weather Research and Forecasting-Chemistry (WRF-Chem) model. The forward and adjoint operators for the aerosol optical depth (AOD) analysis were derived from WRF-Chem aerosol optical code. We applied three-dimensional variational DA to assimilate the multi-wavelength AOD, ambient aerosol scattering coefficient, and aerosol absorption coefficient, measured by the sun-sky photometer, nephelometer, and aethalometer, respectively. These were undertaken during a dust observation field campaign at Kashi in northwestern China in April 2019. The results showed that the DA analyses decreased the low biases in the model aerosols; however, it had had some deficiencies. Assimilating the surface particle concentration increased the coarse particles in the dust episodes, but AOD, and the coefficients for aerosol scattering and absorption, were still lower than observed values. Assimilating aerosol scattering coefficient separately from AOD improved the two optical quantities. However, it caused an overestimation of the particle concentrations at the surface. Assimilating the aerosol absorption coefficient yielded the highest positive bias in the surface particle concentration, aerosol scattering coefficient, and AOD. The positive biases in the DA analysis were caused by the forward operator underestimating particle scattering and absorption efficiency. As a compensation, the DA system increased particle concentrations excessively so as to fit the observed optical values. The best overall improvements were obtained from the simultaneous assimilation of the surface particle concentration and AOD. The assimilation did not substantially change the aerosol chemical fractions. After DA, the clear-sky aerosol radiative forcing at Kashi was −10.5 W m−2 at the top of the atmosphere, which was 46 % higher than the background radiative forcing value.

Wenyuan Chang et al.

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Short summary
The MOSAIC aerosol mechanism in WRF-Chem has been often used for aerosol simulation, but variational data assimilation (DA) for the MOSAIC aerosols is still in need. This study provides an initial version of our variational DA system for the MOSAIC aerosols. The adjoint operators for multi-source aerosol optical data are present. We applied the DA system in an aerosol field campaign to assimilate multi-wavelength aerosol optical data. This DA system will expand to incorporate more aerosol data.
The MOSAIC aerosol mechanism in WRF-Chem has been often used for aerosol simulation, but...
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