Editing IPCC:AR6/WGI/Chapter-7 (section)

==== 7.3.3.3 Energy Budget Constraints on the Total Aerosol ERF ====

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Energy balance models of reduced complexity have in recent years increasingly been combined with Monte Carlo approaches to provide valuable ‘top-down’ (also called inverse) observational constraints on the total aerosol ERF. These top-down approaches report ranges of aerosol ERF that are found to be consistent with the global mean temperature record and, in some cases, also observed ocean heat uptake. However, the total aerosol ERF is also used together with the historical temperature record in ( [[#7.5|Section 7.5]] to constrain equilibrium climate sensitivity (ECS) and transient climate response (TCR). Using top-down estimates as a separate line of evidence also for the total aerosol ERF would therefore be circular. Nevertheless, it is useful to examine the development of these estimates since AR5, and the degree to which these estimates are consistent with the upper and lower bounds of the assessments of total aerosol ERF (ERFari+aci).

When the first top-down estimates emerged (e.g., [[#Knutti--2002|Knutti et al., 2002]] ), it became clear that some of the early (‘bottom-up’) ESM estimates of total aerosol ERF were inconsistent with the plausible top-down range. However, as more inverse estimates have been published, it has increasingly become clear that they too are model-dependent and span a wide range of ERF estimates, with confidence intervals that in some cases do not overlap ( [[#Forest--2018|Forest, 2018]] ). It has also become evident that these methods are sensitive to revised estimates of other forcings and/or updates to observational datasets. A recent review of 19 such estimates reported a mean of –0.77 W m <sup>–2</sup> for the total aerosol ERF, and a 95% confidence interval of [–1.15 to –0.31] W m <sup>–2</sup> ( [[#Forest--2018|Forest, 2018]] ). Adding to that review, a more recent study using the same approach reported an estimate of total aerosol ERF of –0.89 [–1.82 to –0.01] W m <sup>–2</sup> ( [[#Skeie--2018|Skeie et al., 2018]] ). However, in the same study, an alternative way of incorporating ocean heat content in the analysis produced a total aerosol ERF estimate of –1.34 [–2.20 to –0.46] W m <sup>–2</sup> , illustrating the sensitivity to the manner in which observations are included. A new approach to inverse estimates took advantage of independent climate radiative response estimates from eight prescribed SST and sea ice-concentration simulations over the historical period to estimate the total anthropogenic ERF. From this a total aerosol ERF of –0.8 [–1.6 to +0.1] W m <sup>–2</sup> was derived (valid for near-present relative to the late 19th century). This range was found to be more invariant to parameter choices than earlier inverse approaches ( [[#Andrews--2020|Andrews and Forster, 2020]] ).

Beyond the inverse estimates described above, other efforts have been made since AR5 to constrain the total aerosol ERF. For example, [[#Stevens--2015|Stevens (2015)]] used a simple (one-dimensional) model to simulate the historical total aerosol ERF evolution consistent with the observed temperature record. Given the lack of temporally extensive cooling trends in the 20th-century record and the fact that the historical evolution of GHG forcing is relatively well constrained, the study concluded that a more negative total aerosol ERF than –1.0 W m <sup>–2</sup> was incompatible with the historical temperature record. This was countered by [[#Kretzschmar--2017|Kretzschmar et al. (2017)]] , who argued that the model employed in [[#Stevens--2015|Stevens (2015)]] was too simplistic to account for the effect of geographical redistributions of aerosol emissions over time. Following the logic of [[#Stevens--2015|Stevens (2015)]] , but basing their estimates on a subset of CMIP5 models as opposed to a simplified modelling framework, Kretzschmar et al. argued that a total aerosol ERF as negative as –1.6 W m <sup>–2</sup> was consistent with the observed temperature record. Similar arguments were put forward by [[#Booth--2018|Booth et al. (2018)]] , who emphasized that the degree of non-linearity of the total aerosol ERF with aerosol emissions is a central assumption in [[#Stevens--2015|Stevens (2015)]] .

The historical temperature record was also the key observational constraint applied in two additional studies ( [[#Rotstayn--2015|Rotstayn et al., 2015]] ; [[#Shindell--2015|Shindell et al., 2015]] ) based on a subset of CMIP5 models. [[#Rotstayn--2015|Rotstayn et al. (2015)]] found a strong temporal correlation (&gt;0.9) between the total aerosol ERF and the global surface temperature. They used this relationship to produce a best estimate for the total aerosol ERF of –0.97 W m <sup>–2</sup> , but with considerable unquantified uncertainty, in part due to uncertainties in the TCR. [[#Shindell--2015|Shindell et al. (2015)]] came to a similar best estimate for the total aerosol ERF of –1.0 W m <sup>–2</sup> and a 95% confidence interval of –1.4 to –0.6 W m <sup>–2</sup> but based this on spatial temperature and ERF patterns in the models in comparison with observed spatial temperature patterns.

A separate observational constraint on the total ERF was proposed by [[#Cherian--2014|Cherian et al. (2014)]] , who compared trends in downward fluxes of solar radiation observed at surface stations across Europe (described in ( [[#7.2.2.3|Section 7.2.2.3]] ) to those simulated by a subset of CMIP5 models. Based on the relationship between solar radiation trends and the total aerosol ERF in the models, they inferred a total aerosol ERF of –1.3 W m <sup>–2</sup> and a standard deviation of ± 0.4 W m <sup>–2</sup> .

Based solely on energy balance considerations or other observational constraints, it is ''extremely likely'' that the total aerosol ERF is negative ( ''high confidence'' ), but ''extremely unlikely'' that the total aerosol ERF is more negative than –2.0 W m <sup>–2</sup> ( ''high confidence'' ).

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