Articles | Volume 17, issue 23
https://doi.org/10.5194/gmd-17-8495-2024
https://doi.org/10.5194/gmd-17-8495-2024
Development and technical paper
 | 
29 Nov 2024
Development and technical paper |  | 29 Nov 2024

NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components

Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang

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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
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