Abstract

Abstract. This study provides comparisons of aerosol representation methods incorporated into a regional-scale nonhydrostatic meteorology–chemistry model (NHM-Chem). Three options for aerosol representations are currently available: the five-category non-equilibrium (Aitken, soot-free accumulation, soot-containing accumulation, dust, and sea salt), three-category non-equilibrium (Aitken, accumulation, and coarse), and bulk equilibrium (submicron, dust, and sea salt) methods. The three-category method is widely used in three-dimensional air quality models. The five-category method, the standard method of NHM-Chem, is an extensional development of the three-category method and provides improved predictions of variables relating to aerosol–cloud–radiation interaction processes by implementing separate treatments of light absorber and ice nuclei particles, namely, soot and dust, from the accumulation- and coarse-mode categories (implementation of aerosol feedback processes to NHM-Chem is still ongoing, though). The bulk equilibrium method was developed for operational air quality forecasting with simple aerosol dynamics representations. The total CPU times of the five-category and three-category methods were 91 % and 44 % greater than that of the bulk method, respectively. The bulk equilibrium method was shown to be eligible for operational forecast purposes, namely, the surface mass concentrations of air pollutants such as O3, mineral dust, and PM2.5. The simulated surface concentrations and depositions of bulk chemical species of the three-category method were not significantly different from those of the five-category method. However, the internal mixture assumption of soot/soot-free and dust/sea salt particles in the three-category method resulted in significant differences in the size distribution and hygroscopicity of the particles. The unrealistic dust/sea salt complete mixture of the three-category method induced significant errors in the prediction of the mineral dust-containing cloud condensation nuclei (CCN), which alters heterogeneous ice nucleation in cold rain processes. The overestimation of soot hygroscopicity by the three-category method induced errors in the BC-containing CCN, BC deposition, and light-absorbing aerosol optical thickness (AAOT). Nevertheless, the difference in AAOT was less pronounced with the three-category method because the overestimation of the absorption enhancement was compensated by the overestimation of hygroscopic growth and the consequent loss due to in-cloud scavenging. In terms of total properties, such as aerosol optical thickness (AOT) and CCN, the results of the three-category method were acceptable.

Highlights

  • Atmospheric aerosols scatter and absorb solar and thermal radiation and contribute to warming and cooling on regional to global scales

  • It should be noted here that the data assimilation was not applied to the simulations, because the current study focused on variations in the model performance due to the different aerosol representations

  • The cloud condensation nuclei (CCN) was proportional to the nss-SO24− concentrations, an indicator of anthropogenic secondary particles. These results indicate the importance of considering spatiotemporal variations of CCN spectra in the meteorological models, rather than using the prescribed ones that depend only on the land use category (LUC)

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Summary

Introduction

Atmospheric aerosols scatter and absorb solar (shortwave) and thermal (longwave) radiation and contribute to warming and cooling on regional to global scales. An increase in aerosols enhances atmospheric stability and suppresses convective precipitation as a result of their radiative activities cooling the ground surface and heating the atmosphere (Rosenfeld et al, 2008). The nonlinear degradation effect (or positive feedback) of surface air pollution (surface concentration of aerosols increases due to their enhanced atmospheric stability) depends on these properties (Kajino et al, 2017). Because these aerosol properties substantially vary in time and space and the properties change during transport, it is essential to accurately simulate aerosol physical and chemical processes for both climate and pollution modeling

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