Abstract

This paper presents a three-dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including aerosol optical depth (AOD) retrievals and lidar-based aerosol profiles, which was developed for the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) within the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model. For computational efficiency, 32 model variables in the MOSAIC_4bin scheme are lumped into 20 aerosol state variables that are representative of mass concentrations in the DA system. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was employed, which was obtained by simplifying the optical module in WRF-Chem. The tangent linear (TL) and adjoint (AD) operators were then established and passed the TL/AD sensitivity test. The Himawari-8 derived aerosol optical thickness (AOT) data were assimilated to validate the system and investigate the effects of assimilation on both AOT and PM2.5 simulations. Two comparative experiments were performed with a cycle of 24 h from November 23 to 29, 2018, during which a heavy air pollution event occurred in North China. The DA performances of the model simulation were evaluated against independent aerosol observations, including the Aerosol Robotic Network (AERONET) AOT and surface PM2.5 measurements. The results show that Himawari-8 AOT assimilation can significantly improve model AOT analyses and forecasts. Generally, the control experiments without assimilation seriously underestimated AOTs compared with observed values and were therefore unable to describe real aerosol pollution. The analysis fields closer to observations improved AOT simulations, indicating that the system successfully assimilated AOT observations into the model. In terms of statistical metrics, assimilating Himawari-8 AOTs only limitedly improved PM2.5 analyses in the inner simulation domain (D02); however, the positive effect can last for over 24 h. Assimilation effectively enlarged the underestimated PM2.5 concentrations to be closer to the real distribution in North China, which is of great value for studying heavy air pollution events

Highlights

  • 60 Atmospheric aerosols have considerable impacts on weather, climate, and human health.They are involved in many physical and chemical processes in the atmosphere, such as directly scattering and absorbing solar radiation, sources of cloud condensation nuclei, and air pollution (Pöschl, 2005; Gao et al, 2015; Chen et al, 2019)

  • This paper presents a three-dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including aerosol optical depth (AOD) retrievals and lidar-based aerosol profiles, which was developed for the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) within the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model

  • Using an observation operator based on the Mie scattering theory, a comprehensive 3DVAR DA system aiming for aerosol optical properties, 150 including AOD retrievals and aerosol profiles, is developed for the MOSAIC aerosol scheme within the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model for the first time

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Summary

Introduction

60 Atmospheric aerosols have considerable impacts on weather, climate, and human health. They are involved in many physical and chemical processes in the atmosphere, such as directly scattering and absorbing solar radiation, sources of cloud condensation nuclei, and air pollution (Pöschl, 2005; Gao et al, 2015; Chen et al, 2019) Conventional observations such as surface mass concentration measurements play an important role in 65 aerosol analysis and monitoring, for instance, China has established a nationwide monitoring network consisting of more than 1500 stations since 2013 to provide near real-time data of pollutants, including PM2.5, PM10, SO2, NO2, CO, and O3. Using an observation operator based on the Mie scattering theory, a comprehensive 3DVAR DA system aiming for aerosol optical properties, 150 including AOD retrievals and aerosol profiles, is developed for the MOSAIC aerosol scheme within the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model for the first time.

Model description
Basic formulation
Control variables
Observation operator and its adjoint
Effects on AOT simulations
Summary and discussions
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