Atmospheric Chemistry and Physics (Dec 2021)

The role of anthropogenic aerosols in the anomalous cooling from 1960 to 1990 in the CMIP6 Earth system models

  • J. Zhang,
  • J. Zhang,
  • K. Furtado,
  • K. Furtado,
  • S. T. Turnock,
  • S. T. Turnock,
  • J. P. Mulcahy,
  • J. P. Mulcahy,
  • L. J. Wilcox,
  • L. J. Wilcox,
  • B. B. Booth,
  • B. B. Booth,
  • D. Sexton,
  • D. Sexton,
  • T. Wu,
  • T. Wu,
  • F. Zhang,
  • F. Zhang,
  • Q. Liu,
  • Q. Liu

DOI
https://doi.org/10.5194/acp-21-18609-2021
Journal volume & issue
Vol. 21
pp. 18609 – 18627

Abstract

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The Earth system models (ESMs) that participated in the sixth Coupled Model Intercomparison Project (CMIP6) tend to simulate excessive cooling in surface air temperature (TAS) between 1960 and 1990. The anomalous cooling is pronounced over the Northern Hemisphere (NH) midlatitudes, coinciding with the rapid growth of anthropogenic sulfur dioxide (SO2) emissions, the primary precursor of atmospheric sulfate aerosols. Structural uncertainties between ESMs have a larger impact on the anomalous cooling than internal variability. Historical simulations with and without anthropogenic aerosol emissions indicate that the anomalous cooling in the ESMs is attributed to the higher aerosol burden in these models. The aerosol forcing sensitivity, estimated as the outgoing shortwave radiation (OSR) response to aerosol concentration changes, cannot well explain the diversity of pothole cooling (PHC) biases in the ESMs. The relative contributions to aerosol forcing sensitivity from aerosol–radiation interactions (ARIs) and aerosol–cloud interactions (ACIs) can be estimated from CMIP6 simulations. We show that even when the aerosol forcing sensitivity is similar between ESMs, the relative contributions of ARI and ACI may be substantially different. The ACI accounts for between 64 % and 87 % of the aerosol forcing sensitivity in the models and is the main source of the aerosol forcing sensitivity differences between the ESMs. The ACI can be further decomposed into a cloud-amount term (which depends linearly on cloud fraction) and a cloud-albedo term (which is independent of cloud fraction, to the first order), with the cloud-amount term accounting for most of the inter-model differences.