










Estimates of greenhouse gas forcing

The term
In addition to the converse of the Booth et al. (2018) arguments, there are structural reasons as to why Eq. (3) may give a too negative (pessimistic) estimate of
- Any concavity (
decreasing in magnitude with ) would lead to a less negative . Following Kretzschmar et al. (2017), Booth et al. (2018) take CMIP models at face value—something often excused due to a purported lack of better alternatives, but which, given the well-documented deficiencies of the CMIP model’s representation of aerosol forcing (Boucher et al. 2013; Stevens 2015; Stevens and Fiedler 2017; Malavelle et al. 2017; Toll et al. 2017), conflates error with uncertainty—and use them as a basis to argue against the idea that is concave (their first point). The idea that is concave is not an idea introduced by S15; it has long been a staple of aerosol modeling (Boucher and Pham 2002; Carslaw et al. 2013), which as shown by S15 is consistent with the best estimates of as given in the AR5 (see Fig. 3 in S15) and studies by Carslaw et al. (2013) and Myhre et al. (2013). Indeed, the analysis in S15 was substantially motivated by the Carslaw et al. (2013) invocation of concavity (their Fig. 3) to argue for the importance of knowledge of the preindustrial aerosol to estimate .1 In addition to assessing the implications of the concavity argument for global forcing, S15’s novel contribution was actually to outline reasons why concavity might not be as important as emphasized in the earlier literature, reasoning that motivated the development (Stevens et al. 2017) and application (Stevens and Fiedler 2017) of the multiplume model to account for the possibility of such effects. The upshot is that concavity in the relationship between and plays a relatively minor role in S15—a value of as estimated here without concavity [e.g., Eq. (3)] as opposed to as estimated by S15 with concavity—but any concavity implies that as estimated by Eq. (3) would be too negative. - S15 conjectures that it is implausible that the region of Earth—the North Atlantic and adjacent continents—that had the greatest (many times the global mean) aerosol loading through the twentieth century should be among the regions that simultaneously warm the most. Kretzschmar et al. (2017) uses CMIP5 simulations to argue that substantial warming in the hemisphere where the forcing is most negative is less implausible than one might think, an argument that Booth et al. (2018) reiterate (their second point). As already discussed by Stevens and Fiedler (2017), the contra-indicative result from the analysis of a small subset of CMIP5 models would be more compelling if the pattern and magnitude of the temporally evolving clear-sky aerosol forcing in those models were more plausible. Inverse modeling studies, with more strongly constrained aerosol forcing patterns, provide further reason to be skeptical of the Kretzschmar et al. (2017) argument. In these studies, models that latitudinally resolve the forcing and response yield a substantially less negative
as compared to studies based only on global means (Forest 2018). An attempt by S15 to incorporate such hemispheric constraints reduced the magnitude of the lower bound by 25%, yielding not too different from the derived from the inverse modeling studies. Hence the additional constraints are potentially large (25% to 30%). I continue to think that it remains reasonable to suppose that a consideration of the spatial pattern of the forcing, along with the associated response in regional (and seasonal) surface temperatures, should more strongly constrain , but agree that S15’s quantification of this effect is rather speculative. - S15’s energy budget analysis does not apply equally to all time intervals, as it rests on two ideas: one being that—to separate forcing from feedback—the forced temperature response should share the same sign as its radiative forcing; the other being that the time period that gives the strongest constraint is the most useful. Thus, and in marked contrast to my understanding of Booth et al.’s fourth point, the choice of time interval is essential. For time intervals that are too short, or chosen in a way that gives too much weight to changing natural forcings (e.g., from volcanoes2) then it is not possible to separate the forced temperature response from natural variability. Consideration of time intervals that imply an unambiguously positive net forcing risks conflating feedbacks with forcing, something S15 expressly attempts to avoid. My interpretation of Booth et al.’s Fig. 2 is that the climate sensitivity of their model is too large. This, not an insufficiently negative
is then what causes the late-century warming to be overestimated in those runs whose is more in line with S15’s arguments and whose temperature better matches the midcentury warming. S15 identified the mid-twentieth century as being a critical period precisely because it had a secular temperature trend that lay outside of natural variability (even including for the rebound from early-century volcanism) as estimated from a 100-member historical simulation (S15), and because it constrained to a degree that implied a substantial reduction in aerosol forcing uncertainty. Even so, and in retrospect, it was a somewhat conservative estimate; the argument applies equally to the period between 1850 and 1960, sill prior to the 1963 eruption of Agung, and applying it over this period (e.g., Table 1) leads to a substantially less negative .
Taking the above arguments into consideration, I see no reason to question the central point of S15, which is that a consideration of the midcentury temperature record, and best estimates of anthropogenic aerosol and aerosol precursor emissions, supports the other lines of evidence presented in S15 in indicating that the more negative range of estimates of aerosol forcing as given by Boucher et al. (2013) is implausible. One can argue as to whether the ideas outlined above limit
Even if I do not find the combination of arguments that Booth et al. (2018) advance for the plausibility of
Ideas in this paper were stimulated by conversations through the course of the Grand Science Challenge “Clouds, Circulation and Climate Sensitivity Ringberg 2018 Bounding Aerosol Forcing” workshop, organized by Johannes Quaas and Nicolas Bellouin. Johannes Mülmenstädt is thanked for comments on a draft version of this manuscript. The careful reading and thoughtful comments by the editor, John Chiang, and two anonymous reviewers also helped improve the presentation of my ideas.
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K. Carslaw (2018, personal communication) indicated that he was thinking of this as a local argument, but this was not stated in the manuscript, which only talked about global effects, nor is it consistent with the evocation of the preindustrial rather than the pristine airmass aerosol in that manuscript.
The idea that the residual noise from subtracting a volcanic signal whose magnitude is only roughly known outweighs the additional signal one might obtain by extending the analysis into periods with a substantial volcanic forcing seems at least as adventurous as my idea that the hemispheric response to hemispheric forcing adds additional constraints on the forcing as compared to a global analysis.
Because of its lower single scattering albedo the biomass burning aerosol is thought to have a more dominant contribution to aerosol–cloud as compared to aerosol–radiation interactions.