EGU24-3748, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-3748
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

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

Fangxuan Ren1, Jintai Lin1, Jamiu A. Adeniran1, Jingxu Wang2, Randall V. Martin3, Aaron van Donkelaar3, Melanie S. Hammer4, Larry W. Horowitz5, Steven T. Turnock6,7, Naga Oshima8, Jie Zhang9, Susanne Bauer10, Kostas Tsigaridis11,10, Øyvind Seland12, Pierre Nabat13, David Neubauer14, Gary Strand15, Twan van Noije16, Philippe Le Sager16, Toshihiko Takemura17, and the ACM Group*
Fangxuan Ren et al.
  • 1Peking University, School of Physics, Department of Atmospheric and Oceanic Sciences, China (renfx@stu.pku.edu.cn)
  • 2Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
  • 3Department of Energy, Environmental, and Chemical Engineering, Washington University, St. Louis, MO, USA
  • 4St. Francis Xavier University, Department of Earth Sciences, Antigonish, NS, Canada
  • 5NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
  • 6Met Office Hadley Center, Exeter, UK
  • 7University of Leeds Met Office Strategic (LUMOS) Research Group, University of Leeds, UK
  • 8Meteorological Research Institute, Tsukuba, Japan
  • 9Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
  • 10NASA Goddard Institute for Space Studies, New York, NY, USA
  • 11Center for Climate Systems Research, Columbia University, New York, NY, USA
  • 12Norwegian Meteorological Institute, P.O. Box 43 Blindern, Oslo, Norway
  • 13Centre National de Recherches Météorologiques (CNRM), Météo-France, CNRS, Toulouse, France
  • 14Institute of Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
  • 15Climate and Global Dynamics Laboratory, the National Center for Atmospheric Research, Boulder, CO, USA
  • 16Royal Netherlands Meteorological Institute, De Bilt, Netherlands
  • 17Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan
  • *A full list of authors appears at the end of the 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.

ACM Group:

Jintai Lin, Fangxuan Ren, Chenghao Xu

How to cite: Ren, F., Lin, J., Adeniran, J. A., Wang, J., Martin, R. V., van Donkelaar, A., Hammer, M. S., Horowitz, L. W., Turnock, S. T., Oshima, N., Zhang, J., Bauer, S., Tsigaridis, K., Seland, Ø., Nabat, P., Neubauer, D., Strand, G., van Noije, T., Le Sager, P., and Takemura, T. and the ACM Group: Evaluation of CMIP6 model simulations of PM2.5 and its components over China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3748, https://doi.org/10.5194/egusphere-egu24-3748, 2024.