16 Nov 2023
 | 16 Nov 2023
Status: this preprint is open for discussion.

Evaluation of CMIP6 model simulations of PM2.5 and its components over China

Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie Hammer, Larry Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura

Abstract. Earth system models (ESMs) participating in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) simulate various components of fine particulate matter (PM2.5) as major climate forcers. Yet the model performance for PM2.5 components remains little evaluated due in part to lack of observational data. Here, we evaluate near-surface concentrations of PM2.5 and its five main components over China as simulated by fourteen CMIP6 models, including organic carbon (OC, available in 14 models), black carbon (BC, 14 models), sulfate (14 models), nitrate (4 models), and ammonium (5 models). For this purpose, we collect observational data between 2000 and 2014 from a satellite-based dataset for total PM2.5 and from 2469 measurement records in the literature for PM2.5 components. Seven models output total PM2.5 concentrations, and they all underestimate the observed total PM2.5 over eastern China, with GFDL-ESM4 (–1.5 %) and MPI-ESM-1-2-HAM (–1.1 %) exhibiting the smallest biases averaged over the whole country. The other seven models, for which we recalculate total PM2.5 from the available components output, underestimate the total PM2.5 concentrations, partly because of the missing model representations of nitrate and ammonium. Concentrations of the five individual components are underestimated in almost all models, except that sulfate is overestimated in MPI-ESM-1-2-HAM by 12.6 % and in MRI-ESM2-0 by 24.5 %. The underestimation is the largest for OC (by –71.2 % to –37.8 % across the 14 models) and the smallest for BC (–47.9 % to –12.1 %). The multi-model mean (MMM) reproduces fairly well the observed spatial pattern for OC (R = 0.51), sulfate (R = 0.57), nitrate (R = 0.70) and ammonium (R = 0.75), yet the agreement is poorer for BC (R = 0.39). The varying performances of ESMs on total PM2.5 and its components have important implications for the modeled magnitude and spatial pattern of aerosol radiative forcing.

Fangxuan Ren et al.

Status: open (until 11 Jan 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Fangxuan Ren et al.


Total article views: 33 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
22 9 2 33 3 2 2
  • HTML: 22
  • PDF: 9
  • XML: 2
  • Total: 33
  • Supplement: 3
  • BibTeX: 2
  • EndNote: 2
Views and downloads (calculated since 16 Nov 2023)
Cumulative views and downloads (calculated since 16 Nov 2023)

Viewed (geographical distribution)

Total article views: 32 (including HTML, PDF, and XML) Thereof 32 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 29 Nov 2023
Short summary
We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its five components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce well the observed spatial pattern for OC, sulfate, nitrate and ammonium, yet the agreement is poorer for BC.