Articles | Volume 19, issue 6
https://doi.org/10.5194/gmd-19-2479-2026
https://doi.org/10.5194/gmd-19-2479-2026
Development and technical paper
 | 
27 Mar 2026
Development and technical paper |  | 27 Mar 2026

PM2.5 assimilation within JEDI for NOAA's regional Air Quality Model (AQMv7): application to the September 2020 Western US wildfires

Hongli Wang, Cory Martin, Jérôme Barré, Ruifang Li, Steve Weygandt, Jianping Huang, Youhua Tang, Hyundeok Choi, Andrew Tangborn, Kai Wang, Haixia Liu, and Jeffrey Lee

Download

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2025-4098', Anonymous Referee #1, 30 Oct 2025
  • RC2: 'Comment on egusphere-2025-4098', Anonymous Referee #2, 06 Nov 2025
  • RC3: 'Comment on egusphere-2025-4098', Anonymous Referee #3, 10 Nov 2025

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Hongli Wang on behalf of the Authors (22 Feb 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (28 Feb 2026) by Narendra Ojha
RR by Anonymous Referee #1 (02 Mar 2026)
RR by Anonymous Referee #3 (10 Mar 2026)
ED: Publish subject to technical corrections (11 Mar 2026) by Narendra Ojha
AR by Hongli Wang on behalf of the Authors (12 Mar 2026)  Author's response   Manuscript 
Download
Short summary
This paper describes efforts to develop aerosol data assimilation capabilities for NOAA’s regional air quality modeling system by assimilating PM2.5 observations within the Joint Effort for Data Assimilation Integration framework. Results from the September 2020 Western U.S. wildfires show that assimilating AirNow and/or PurpleAir PM2.5 data reduces mean absolute errors of 1–24 h PM2.5 forecasts over the continental United States on average relative to a control without data assimilation.
Share