Aerosol Effective Radiative Forcings in CMIP Models
Abstract. Uncertainty in the effective radiative forcing (ERF) of climate primarily arises from the unknown contribution of aerosols, which impact radiative fluxes directly and through modifying cloud properties. Climate model simulations with fixed sea surface temperatures but perturbed atmospheric aerosol loadings allow for an estimate of how strongly the planet’s radiative energy budget has been perturbed by the increase in aerosols since pre-industrial times. The approximate partial radiative perturbation (APRP) technique further decomposes the contributions to the direct forcing from aerosol scattering and absorption, and to the indirect forcing from aerosol-induced changes in cloud scattering, amount, and absorption, as well as the effects of aerosols on surface albedo. Here we evaluate previously published APRP-derived estimates of aerosol effective radiative forcings from these simulations and find that they are slightly biased as a result of large but compensating errors. These biases are largest for the aerosol direct effect owing to underestimated aerosol absorption. Correcting these biases eliminates the residuals and leads to better agreement with ground-truth estimates derived from double-calls to the radiation code. The APRP method – when properly implemented – remains a highly accurate and efficient technique for diagnosing aerosol ERF in cases where double radiation calls are not available, and in all cases it provides quantification of the individual contributors to the ERF that are highly useful but not otherwise available.
Mark D. Zelinka et al.
Status: open (until 06 Jun 2023)
- RC1: 'Comment on egusphere-2023-689', Anonymous Referee #1, 17 May 2023 reply
- RC2: 'Comment on egusphere-2023-689', Anonymous Referee #2, 30 May 2023 reply
Mark D. Zelinka et al.
Mark D. Zelinka et al.
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In their manuscript, the authors revisit existing methods to decompose the aerosol forcing into different terms and compare them against each other. In particular they flag some errors in the implementation of the APRP method by Smith et al. (ACP, doi: 10.5194/acp-20-9591-2020, 2020). As Chris Smith is a co-author of this manuscript, I assume he agrees with this! Overall this is a technical yet interesting manuscript that also documents the aerosol forcings of CMIP5 and CMIP6 models. I recommend publication after my comments below are accounted for.
Comments (major and minor interspersed)
Title: I did not find the title to be very informative. May I suggest instead “On methods to estimate aerosol effective forcings in CMIP models” or something that conveys the idea that several methods are looked at and compared in this manuscript?
Abstract and possibly elsewhere, “forcing from aerosol scattering”: By scattering solar radiation, aerosols generally tend to increase the mean photon path and therefore gaseous absorption. I would argue that “forcing due to aerosol scattering” or “forcing induced by aerosol scattering” is a more appropriate term than “forcing from aerosol scattering”. Likewise for cloud scattering and absorption.
Equation 1: there is an additional term in this equation as ΔR also depends on the climate response over land (SST are fixed in these experiments but Land Surface Temperatures or LST are not). This is well explained in e.g. Sherwood et al (BAMS, 2015) as, I’m sure, the authors are aware. I would suggest that this additional term is included in Eq. 1. How it can be corrected or reasons why it can be neglected should be discussed.
Line 78: is “temperature” here meant to be “atmospheric temperature” or both “atmospheric” and “surface” temperature? See my comment above on Equation 1.
Line 78 and elsewhere: IPCC AR6 is too vague, please cite explicitly the relevant Chapter or Chapters.
Equation 5: Aerosols may also change surface albedo by changing the distribution between direct and diffuse radiation. Indeed albedo is not an intrinsic property of the surface but depends on the properties of the incoming solar radiation. Several models now include different albedoes for direct and diffuse radiation, in particular over the ocean. By increasing the fraction of diffuse radiation at the surface in clear sky and by changing the amount of cloudiness, aerosols may thus modify the surface albedo. This additional term is probably small, and maybe negligible, but worth mentioning.
Line 115: should it be IPCC ari and aci rather than direct and indirect effects?
APRP method, section 2.2.2: I would strongly encourage the authors to include a bit more description of the APRP method so that this manuscript can be read as a stand alone piece without the need to refer back to Taylor et al (2007) to make sense of it.
Equation 15: although there is no change in notation, it may be worth repeating here that ΔR is the difference in R between two simulations.
Line 160: see my comments above. Does it mean that the ΔR term due to the change in LST is negligible? Can you provide evidence of this?
Lines 165-169: this paragraph needs more context to be understood. A more detailed section 2.2.2 would help the reader to appreciate fully this paragraph.
Figure 1: It may be worth saying in the caption that each circle represents a different CMIP model.
Section 3.3: It may be worth saying that the forcing year is different for CMIP5 and CMIP6 (2014 for the latter, I’m not sure for the former). However this should not have much of an impact as the aerosol forcing is thought to be pretty flat over that period.
A Table summarizing all the symbols / notations used in the manuscript would be useful.