Articles | Volume 17, issue 12
https://doi.org/10.5194/gmd-17-4821-2024
https://doi.org/10.5194/gmd-17-4821-2024
Model evaluation paper
 | 
20 Jun 2024
Model evaluation paper |  | 20 Jun 2024

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 S. Hammer, Larry W. 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

Data sets

WCRP Coupled Model Intercomparison Project (Phase 6) World Climate Research Programme (WCRP) https://esgf-node.llnl.gov/projects/cmip6/

Regional Estimates of Chemical Composition of Fine Particulate Matter Using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors (https://sites.wustl.edu/acag/datasets/surface-pm2-5-archive/#V4.CH.03) A. van Donkelaar et al. https://doi.org/10.1021/acs.est.8b06392

Download
Short summary
We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 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 the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.