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Current Climate Change Reports

, Volume 4, Issue 1, pp 11–22 | Cite as

Inferred Net Aerosol Forcing Based on Historical Climate Changes: a Review

  • Chris E. ForestEmail author
Aerosols and Climate (O Boucher, Section Editor)
Part of the following topical collections:
  1. Topical Collection on Aerosols and Climate

Abstract

Purpose of Review

This review summarizes the inverse methods used to estimate the net aerosol forcing inferred from the historical climate change records for the Earth.

Recent Findings

The available methods are similar in design while differing in their assumptions. Primary differences are (a) the complexity of the earth system model used for forward simulations of the historical period (~ 1850 to the present), (b) the uncertainty sampling methodology, and (c) the representation of internal climate variability in the statistical approach. All methods, in some fashion, include the net aerosol radiative forcing as a residual forcing that is scaled to find simulations that match the observed records of surface air and deep ocean temperatures. Inverse methods also require sampling the model response uncertainty in the equilibrium climate sensitivity and the transient climate response (i.e., the delay due to mixing heat into the deep ocean), and therefore, a joint probability distribution is estimated that includes uncertainty across multiple components.

Summary

The resulting estimates of the net aerosol forcing and its uncertainty are, by construction, necessarily linked to the earth system model, its response characteristics, and the estimates of the internal chaotic variability. Summary results indicate that the net aerosol forcing during the late twentieth century was − 0.77 Wm−2 with a 5–95% range of − 1.15 to − 0.31 Wm−2 based on 19 results from simple- to full-complexity climate system models.

Keywords

Anthropogenic radiative forcing Net aerosol radiative forcing Inverse methods Observed historical climate change Intermediate complexity earth system models Internal climate variability Joint probability distributions 

Notes

Acknowledgments

The author would like to thank A.G. Libardoni and A.P. Sokolov for their comments, O. Boucher for his patience and helpful review suggestions, and the two anonymous reviewers.

Funding Information

This work was supported in part by the Office of Science (BER), the U.S. Department of Energy Grant No. DE-FG02-94ER61937, and the National Science Foundation through the Network for Sustainable Climate Risk Management (SCRiM) under NSF cooperative agreement GEO-1240507.

Compliance with Ethical Standards

Conflict of Interest

On behalf of myself, the corresponding author states that there is no conflict of interest.

Supplementary material

40641_2018_85_MOESM1_ESM.docx (65 kb)
ESM 1 (DOCX 64 kb)

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Authors and Affiliations

  1. 1.Department of Meteorology and Atmospheric Science; Department of Geosciences; Earth and Environmental Systems InstituteThe Pennsylvania State UniversityUniversity ParkUSA

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