Preprints
https://doi.org/10.5194/egusphere-2026-1666
https://doi.org/10.5194/egusphere-2026-1666
27 May 2026
 | 27 May 2026
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Beyond aerosol size parameter comparison: A practical method for evaluating aerosol microphysical processes of 3D aerosol physics and chemistry models using size-resolved aerosol measurement data - Application to NHM-Chem v2.0

Mizuo Kajino, Narihiro Orikasa, Rei Kudo, Atsushi Shimizu, Tomoaki Nishizawa, Yoshitaka Jin, Kazuo Osada, Satoko Kayaba, Tomoki Kajikawa, Rio Ishikawa, and Keiya Yumimoto

Abstract. Aerosol size is a key parameter for evaluating the climate and environmental impacts of aerosols. However, when discrepancies arise between simulated and observed aerosol size-distribution parameters (e.g., number concentration, mean diameter, and standard deviation), it is often difficult to judge how critical those differences are. Here, we propose a practical recipe for evaluating 3-D aerosol models with size-resolved measurement data: the Pseudo-physical Variable Comparison (PPVC) method. PPVC compares physically meaningful variables (e.g., cloud condensation nuclei concentrations and light extinction coefficients) and processes (e.g., condensation rate and Brownian coagulation rate) that are derived from observed and simulated size distributions of aerosols, together with prescribed representative values of relevant parameters (e.g., hygroscopicity or refractive index), instead of comparing only size parameters. We applied PPVC to evaluate a regional-scale meteorology–chemistry model, NHM-Chem (versions v1.0 and v2.0), using scanning mobility particle sizer (SMPS) and aerodynamic particle sizer (APS) data measured in Tsukuba. The PPVC analysis showed that v2.0 improved the predictability of light extinction coefficients relative to v1.0. Using independent datasets, we also found that NHM-Chem v2.0 generally outperformed v1.0 not only for aerosol optical depth (AOD) but also for the predicted fine-mode fractions of inorganic species, owing to improvements in aerosol size distributions. We propose a new metric to evaluate the overall consistency of simulated aerosol physical parameters: the Distance of Deviations between simulated and observed Aerosol Physical Parameters (DDAP). DDAP for NHM-Chem v1.0 and v2.0 were 4.2 × 10−2 and 3.5 × 10−2, respectively, indicating that the microphysical properties and processes simulated by v2.0 were approximately 17% more consistent with observations than those of v1.0.

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Mizuo Kajino, Narihiro Orikasa, Rei Kudo, Atsushi Shimizu, Tomoaki Nishizawa, Yoshitaka Jin, Kazuo Osada, Satoko Kayaba, Tomoki Kajikawa, Rio Ishikawa, and Keiya Yumimoto

Status: open (until 22 Jul 2026)

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Mizuo Kajino, Narihiro Orikasa, Rei Kudo, Atsushi Shimizu, Tomoaki Nishizawa, Yoshitaka Jin, Kazuo Osada, Satoko Kayaba, Tomoki Kajikawa, Rio Ishikawa, and Keiya Yumimoto
Mizuo Kajino, Narihiro Orikasa, Rei Kudo, Atsushi Shimizu, Tomoaki Nishizawa, Yoshitaka Jin, Kazuo Osada, Satoko Kayaba, Tomoki Kajikawa, Rio Ishikawa, and Keiya Yumimoto
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Latest update: 27 May 2026
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Short summary
Aerosol size distribution is important for understanding the climate impacts of aerosols; however, it is difficult to validate modeled size distributions. This study introduces a new method that compares physical variables, such as cloud condensation nuclei and light extinction coefficients, derived from size distribution measurements. Using data from Tsukuba, Japan, the method shows that the new model (v2.0) improves predictions of aerosol size distribution by about 17% compared to v1.0.
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