the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Decomposing the Effective Radiative Forcing of anthropogenic aerosols based on CMIP6 Earth System Models
Alkiviadis Kalisoras
Aristeidis K. Georgoulias
Dimitris Akritidis
Robert J. Allen
Vaishali Naik
Chaincy Kuo
Sophie Szopa
Pierre Nabat
Dirk Olivié
Twan van Noije
Philippe Le Sager
David Neubauer
Naga Oshima
Jane Mulcahy
Larry W. Horowitz
Prodromos Zanis
Abstract. Anthropogenic aerosols play a major role for the Earth-Atmosphere system by influencing the Earth’s radiative budget and climate. The effect of the perturbation induced by changes in anthropogenic aerosols on the Earth's energy balance is quantified in terms of the effective radiative forcing (ERF) which is the recommended metric for perturbations affecting the Earth’s top-of-atmosphere energy budget since it is a better way to link this perturbation to subsequent global mean surface temperature change. In this work, the present-day ERF of anthropogenic aerosols is quantified using simulations from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The ERFs of individual aerosol species, such as sulphates, organic carbon (OC), and black carbon (BC) are calculated along with the ERF due to all anthropogenic aerosols and the transient ERF over the historical period (1850–2014). Additionally, ERF is analyzed into three components: (a) ERFARI, representing aerosol-radiation interactions, (b) ERFACI, accounting for aerosol-cloud interactions, and (c) ERFALB, which is mainly due to the contribution of surface albedo changes caused by anthropogenic aerosols. Here, the total anthropogenic aerosol ERF (calculated using the piClim-aer experiment) is estimated to be -1.11 ± 0.26 W m-2, mostly due to the large contribution of ERFACI (-1.14 ± 0.33 W m-2), compared to ERFARI (-0.02 ± 0.20 W m-2) and ERFALB (0.05 ± 0.07 W m-2). The total ERF caused by sulphates (piClim-SO2) is estimated at -1.11 ± 0.31 W m-2, the OC ERF (piClim-OC) is -0.35 ± 0.21 W m-2, whereas the ERF exerted by BC (piClim-BC) is 0.19 ± 0.18 W m-2. On top of that, our analysis reveals that ERFACI clearly prevails over the largest part of the Earth except for the BC experiment where ERFARI prevails over land. By the end of the historical period (1995–2014), the global mean total aerosol ERF is estimated at -1.28 ± 0.37 W m-2 (calculated using the histSST experiment). We find that sulphates dominate both present-day and transient ERF spatial patterns at the top of the atmosphere, exerting a strongly negative ERF especially over industrialized regions of the Northern Hemisphere, such as North America, Europe, East and South Asia. Since the mid-1980s ERF has become less negative over Eastern North America and Western and Central Europe, while over East and South Asia there is a steady increase in ERF magnitude towards more negative values until 2014.
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Alkiviadis Kalisoras et al.
Status: open (until 02 Jan 2024)
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RC1: 'Comment on egusphere-2023-2571', Anonymous Referee #1, 07 Dec 2023
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Review of “Decomposing the Effective Radiative Forcing of anthropogenic aerosols
based on CMIP6 Earth System Models”
This study examined the present-day and historical effective radiative forcing (ERF) of anthropogenic aerosols, using CMIP6 Earth system model simulations. ERF calculations cover individual aerosol species—sulphates, organic carbon (OC), and black carbon (BC)—and are further investigated into three components: aerosol-radiation interactions (ERFARI), aerosol-cloud interactions (ERFACI), and contributions from surface albedo changes (ERFALB). The total ERF is predominantly driven by ERFACI, with anthropogenic sulphate ERF being globally negative, particularly over Northern Hemisphere regions, while BC contributes to a positive global ERF due to a strong ERFARI. Additionally, the study reveals regional differences in ERF trends and demonstrates the dominant role of ERFACI from sulphates in driving these trends. The results are comprehensive and the manuscript is well written. Although most results are expected, this study would be a good reference for studying the ERF in state-of-the-art GCMs. I would recommend it to be published in Atmospheric Chemistry and Physics, subject to the following minor comments.
General comments:
It would be good to briefly introduce which inputdate datasets (e.g. emission data sets) and parameterizations are used in these models, which are highly relevant with ERF and could contribute to the inter-model uncertainties, such as cloud microphysical schemes (one moment/two moment, bulk/bin), activation, autoconversion schemes?
Semi-direct effects have been mentioned in the introduction part, but not discussed enough in the main text. These effects are especially important in interpreting ERF from BC aerosols, and could largely contribute to inter-model uncertainties. Clarification on whether these effects are included in the ERF calculations and how the models' parameterizations impact these uncertainties would enhance the study's comprehensiveness.
Minor comments:
L31: the range showing one standard deviation?
L39: ERF from anthropogenic aerosols?
L45: spatially heterogeneously
L53: Not all types of aerosols can 'efficiently' serve as CCN or IN.... It relies on sizes, types, supersaturation, mixing state, ..
L67: I would prefer 'conditions' than 'parameters' here.
L74: suggest also cite Martin Wild’s dimming effect paper here.
L105: Additionally, the magnitude of ERFaci might also depend on dynamic backgrounds (Zhang et al., 2016; 10.5194/acp-16-2765-2016) and large-scale circulation adjustments (Dagan et al., 2023: https://doi.org/10.1038/s41561-023-01319-8).
L105: ‘on aerosol radiative forcing calculations’: a work by Ghan et al., (2016) (10.1073/pnas.1514036113) might also be relevant, which demonstrates the chain processes within ERFaer and discussed the uncertainties of each process in GCMs.
L125: ‘but this would be difficult to apply in some climate models (Ramaswamy et al., 2019).’: some recent work has done this by fixing land surface temperature, see Andrews et al, 2021: https://doi.org/10.1029/2020JD033880)
L131: ‘’The total ERF due to aerosols’ : anthropogenic aerosols?
L142: The current paragraph appears to be overly dense with information, much of which seems to be a repetition of what is already presented in Table 1. It would be beneficial for the readers, in terms of enhanced readability and comprehension, if the key points and implications of these data were more clearly and explicitly given.
L275: Here and other places, please add units
L289: Are stratospheric (volcanic) aerosols included in od550so4?
L316-318: Positive ERFari over these regions are mostly due to absorbing aerosols?
L398: How does albedo change the LW ERF? Isn't it primarily influencing shortwave radiation by changing how solar energy is absorbed or reflected?
L399: ‘borne to mind’ change to ‘borne in mind’
L422: From Fig. 5, for BC, ERF LW is still positive, ERFari LW around zero and ERFaci LW positive - I didn't see 'a negative but weaker LW ERF' from BC...
L438: For this paragraph which focused on BC, it would benefit from some discussions on semi-direct effect.
Table 5: Briefly introduce what the abbreviations stand for - captions should be self-explained.
Fig 1,2,3: It is really hard to tell the difference between ‘//’ and ‘xx’ symbols in the figures…
Fig 7: I like the idea of showing the relative importance of ACI, ARI, and ALB geographically. Could you explain why there are some regions dominated by ALB over ocean in the BC case?.
Citation: https://doi.org/10.5194/egusphere-2023-2571-RC1
Alkiviadis Kalisoras et al.
Alkiviadis Kalisoras et al.
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