Publication Abstracts
Ren et al. 2024
Ren, F., J. Lin, C. Xu, J.A. Adeniran, J. Wang, R.V. Martin, A. van Donkelaar, M. Hammer, L. Horowitz, S.T. Turnock, N. Oshima, J. Zhang, , , Ø. Seland, P. Nabat, D. Neubauer, G. Strand, T. van Noije, P. Le Sager, and T. Takemura, 2024: Evaluation of CMIP6 model simulations of PM2.5 and its components over China. Geosci. Model Dev., 17, no. 12, 4821-4836, doi:10.5194/gmd-17-4821-2024.
arth 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 a lack of observational data. Here, we evaluate near-surface concentrations of PM2.5 and its five main components over China as simulated by 14 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 component 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 the observed spatial pattern for OC (R = 0.51), sulfate (R = 0.57), nitrate (R = 0.70) and ammonium (R = 0.74) fairly well, 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.
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BibTeX Citation
@article{re08100s,
author={Ren, F. and Lin, J. and Xu, C. and Adeniran, J. A. and Wang, J. and Martin, R. V. and van Donkelaar, A. and Hammer, M. and Horowitz, L. and Turnock, S. T. and Oshima, N. and Zhang, J. and Bauer, S. and Tsigaridis, K. and Seland, Ø. and Nabat, P. and Neubauer, D. and Strand, G. and van Noije, T. and Le Sager, P. and Takemura, T.},
title={Evaluation of CMIP6 model simulations of PM2.5 and its components over China},
year={2024},
journal={Geoscientific Model Development},
volume={17},
number={12},
pages={4821--4836},
doi={10.5194/gmd-17-4821-2024},
}
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RIS Citation
TY - JOUR ID - re08100s AU - Ren, F. AU - Lin, J. AU - Xu, C. AU - Adeniran, J. A. AU - Wang, J. AU - Martin, R. V. AU - van Donkelaar, A. AU - Hammer, M. AU - Horowitz, L. AU - Turnock, S. T. AU - Oshima, N. AU - Zhang, J. AU - Bauer, S. AU - Tsigaridis, K. AU - Seland, Ø. AU - Nabat, P. AU - Neubauer, D. AU - Strand, G. AU - van Noije, T. AU - Le Sager, P. AU - Takemura, T. PY - 2024 TI - Evaluation of CMIP6 model simulations of PM2.5 and its components over China JA - Geosci. Model Dev. JO - Geoscientific Model Development VL - 17 IS - 12 SP - 4821 EP - 4836 DO - 10.5194/gmd-17-4821-2024 ER -
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