Comparison of three aerosol representations of NHM-Chem (v1.0) for the simulations of air quality and climate-relevant variables

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.

Improvement in Dust Storm Simulation by Considering Stone Coverage Effects for Stony Deserts in East Asia

“…Consequently, even if the parameters for particle size distributions or geometric deviations are changed in the model, the mass concentration of dust particles is hardly influenced under the conditions in this study. This simple representation of dust chemistry and dynamics did not deteriorate the model performance of mineral dust particles (Kajino et al., 2021). This dust‐specific version is called NHM‐Chem‐Dust hereafter.…”

“…We conducted dust emission and transport simulations using an Eulerian model based on a regional meteorology-chemistry model called NHM-Chem (Kajino et al, 2019(Kajino et al, , 2021. Although the NHM-Chem is available for both offline and online connections to the JMA-NHM, this study used the offline version.…”

Potential Impacts of Energy and Vehicle Transformation through 2050 on the Atmospheric Environment of Japan: focus on PM2.5 Metals and Aerosol Acidity inducing Respiratory Inflammation

“…ISORROPIA-II can simulate the thermodynamic equilibrium of water-soluble inorganic ions and calculate the pH of aerosol particles in the equilibrium state. ISORROPIA-II was implemented in NHM-Chem for the calculation of the condensation of HNO 3 , NH 3 , HCl, and H 2 O (Kajino et al, 2021), but aerosol pH was not dynamically solved. In addition, ISORROPIA-II in NHM-Chem solves the aerosol thermodynamics of each aerosol category but does not solve the aerosol pH of bulk submicron aerosols discussed in the study.…”

Statistical Evaluation of the Temperature Forecast Error in the Lower-Level Troposphere on Short-Range Timescales Induced by Aerosol Variability

“…Simulations of atmospheric aerosols typically involve various elemental processes, such as primary emission of aerosols and precursor gases, chemical reactions and secondary formation, transportation, dry and wet deposition processes, and aerosol-atmosphere interaction processes. Thus, numerous aerosol simulation studies have been conducted with regional (e.g., Kajino et al, 2019Kajino et al, , 2021aGrell et al, 2005) and global (Bhattacharjee et al, 2018;Gong et al, 2012;Morcrette et al, 2009;Rémy et al, 2019;Tanaka, 2003;Tanaka and Chiba, 2005) models. Regardless of these numerous studies, high uncertainties are associated with each elemental process.…”

“…Regardless of these numerous studies, high uncertainties are associated with each elemental process. To reduce these uncertainties, several approaches have been studied, such as data assimilation to improve the spatiotemporal distribution (Benedetti et al, 2009;Sekiyama et al, 2011;Yumimoto et al, 2016;Kajino et al, 2021a), the inversion method to improve emissions (Maki et al, 2011;Sugimoto et al, 2010;Yumimoto et al, 2008), and the superensemble method (Kajino et al, 2021b). However, because the solution to all these processes requires very high computational resources, aerosols have been treated in a simple manner in numerical weather prediction (NWP) models.…”