Aerosol impacts on post-monsoon meteorology in North India predicted by the Japan Meteorological Agency’s online-coupled meteorology–chemistry model NHM-Chem v2.0

Kajino, Mizuo; Makoto Deushi; Akihiro Hashimoto; Rei Kudo; Ryoji Nagasawa; Tsuyoshi Thomas Sekiyama; Tomoki Kajikawa; Satoko Kayaba; Yukari Hara; Keiya Yumimoto; Dilip Ganguly; Sachiko Hayashida; Takashi Maki

doi:10.51094/jxiv.3338

##article.authors##

Kajino, Mizuo Meteorological Research Institute, Japan Meteorological Agency
Makoto Deushi Meteorological Research Institute, Japan Meteorological Agency
Akihiro Hashimoto Meteorological Research Institute, Japan Meteorological Agency
Rei Kudo Meteorological Research Institute, Japan Meteorological Agency
Ryoji Nagasawa Meteorological Research Institute, Japan Meteorological Agency
Tsuyoshi Thomas Sekiyama Meteorological Research Institute, Japan Meteorological Agency
Tomoki Kajikawa Graduate School of Science and Technology, University of Tsukuba
Satoko Kayaba National Institute for Environmental Studies
Yukari Hara Research Institte for Applied Mechanics, Kyushu University
Keiya Yumimoto Research Institte for Applied Mechanics, Kyushu University
Dilip Ganguly Centre for Atmospheric Sciences, Indian Institute of Technology Delhi
Sachiko Hayashida Research Institute for Humanity and Nature
Takashi Maki Meteorological Research Institute, Japan Meteorologcal Agency

DOI:

https://doi.org/10.51094/jxiv.3338

キーワード:

Crop residue burning、 PM2.5、 Aerosol-to-meteorology feedback、 Model development、 Multi-model intercomparison

抄録

The Japan Meteorological Agency’s online-coupled meteorology–chemistry model with aerosol-to-meteorology feedback, NHM-Chem v2.0, was developed and applied to post-monsoon air pollution episodes associated with Kharif crop residue burning (CRB) over North India in 2022. Model performance in simulating increases in surface concentrations of PM_2.5 owing to aerosol–radiation feedback (referred to as “positive feedback”) were compared with those of WRF-Chem. Online NHM-Chem was 2.5 times faster than WRF-Chem, whereas WRF-Chem better reproduced spatiotemporal PM_2.5 variations than NHM-Chem, probably because meteorological fields such as wind direction and planetary boundary layer (PBL) height predicted by WRF-Chem were generally more accurate than those from NHM-Chem. Both models successfully reproduced high PM_2.5 episodes exceeding 300 µg m⁻³ caused by CRB plume transport under northwesterly winds, whereas the models failed to reproduce CRB plume transport during convective conditions. During the plume event (2–4 November), daytime solar radiation and PBL height decreased by 30%–40% and 50%–80%, respectively, increasing surface PM_2.5 concentrations by up to 100% over the Delhi National Capital Region compared with clean-air scenarios. The contribution of CRB to surface PM_2.5 varied from 40% to 80%, depending on the selection of models. Both model simulations indicated that CRB increased surface PM_2.5 from anthropogenic and CRB sources equally by 15%–50% through positive feedback. Thus, discontinuing CRB would not only reduce CRB-related PM_2.5 but also lower anthropogenic surface PM_2.5 by 15%–50%.

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