Aerosol-cloud interactions in global models of indirect aerosol radiative forcing

This reply addresses a comment questioning one of the lines of evidence I used in a 2015 study (S15) to argue for a less negative aerosol radiative forcing. The comment raises four points of criticism. Two of these have been raised and addressed elsewhere; here I additionally show that even if they have merit the S15 lower bound remains substantially (0.5 W m–2) less negative than that given in the AR5. Regarding the two other points of criticism, one appears to be based on a poor understanding of the nature of S15’s argument; the other rests on speculation as to the nature of the uncertainty in historical SO2 estimates. In the spirit of finding possible flaws with the top-down constraints from S15, I instead hypothesize that an interesting—albeit unlikely—way S15 could be wrong is by inappropriately discounting the contribution of biomass burning to radiative forcing through aerosol–cloud interactions. This hypothesis is interesting as it opens the door for a role for the anthropogenic (biomass) aerosol in causing the Little Ice Age and again raises the specter of greater warming from ongoing reductions in SO2 emissions.

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Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-17727-2021 ◽

2021 ◽

Vol 21 (23) ◽

pp. 17727-17741

Author(s):

Zhonghua Zheng ◽

Matthew West ◽

Lei Zhao ◽

Po-Lun Ma ◽

Xiaohong Liu ◽

...

Keyword(s):

Radiative Forcing ◽

Mixing State ◽

Aerosol Model ◽

Aerosol Radiative Forcing ◽

Aerosol Cloud ◽

Process Representation ◽

Community Earth System Model ◽

Aerosol Cloud Interactions ◽

Aerosol Module ◽

Aerosol Mixing State

Abstract. Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. This study aims to verify the global distribution of aerosol mixing state represented by modal models. To quantify the aerosol mixing state, we used the aerosol mixing state indices for submicron aerosol based on the mixing of optically absorbing and non-absorbing species (χo), the mixing of primary carbonaceous and non-primary carbonaceous species (χc), and the mixing of hygroscopic and non-hygroscopic species (χh). To achieve a spatiotemporal comparison, we calculated the mixing state indices using output from the Community Earth System Model with the four-mode version of the Modal Aerosol Module (MAM4) and compared the results with the mixing state indices from a benchmark machine-learned model trained on high-detail particle-resolved simulations from the particle-resolved stochastic aerosol model PartMC-MOSAIC. The two methods yielded very different spatial patterns of the mixing state indices. In some regions, the yearly averaged χ value computed by the MAM4 model differed by up to 70 percentage points from the benchmark values. These errors tended to be zonally structured, with the MAM4 model predicting a more internally mixed aerosol at low latitudes and a more externally mixed aerosol at high latitudes compared to the benchmark. Our study quantifies potential model bias in simulating mixing state in different regions and provides insights into potential improvements to model process representation for a more realistic simulation of aerosols towards better quantification of radiative forcing and aerosol–cloud interactions.

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Deconvolution of Boundary Layer Depth and Aerosol Constraints on Cloud Water Path in Subtropical Stratocumuli

10.5194/acp-2019-833 ◽

2019 ◽

Author(s):

Anna Possner ◽

Ryan Eastman ◽

Frida Bender ◽

Franziska Glassmeier

Keyword(s):

Radiative Forcing ◽

Process Modelling ◽

Liquid Water Path ◽

Water Path ◽

Aerosol Radiative Forcing ◽

Aerosol Cloud ◽

Modelling Studies ◽

Aerosol Cloud Interactions ◽

Marine Boundary Layers

Abstract. The liquid water path (LWP) adjustment due to aerosol-cloud interactions in marine stratocumuli remains a considerable source of uncertainty for climate sensitivity estimates. An unequivocal attribution of LWP changes to changes in aerosol concentration from climatology remains difficult due to the considerable covariance between meteorological conditions alongside changes in aerosol concentrations. Here, we show that LWP susceptibility in marine boundary layers (BLs) inferred from climatological relationships, triples in magnitude from −0.1 to −0.33 as the BL deepens. We further find deep BLs to be underrepresented in pollution track, process modelling and in-situ studies of aerosol-cloud interactions in marine stratocumuli. Susceptibility estimates based on these approaches are skewed towards shallow BLs of moderate LWP susceptibility. Therefore, extrapolating LWP susceptibility estimates from shallow BLs to the entire cloud climatology, may underestimate the true LWP adjustment within sub-tropical stratocumuli, and thus overestimate the effective aerosol radiative forcing in this region. Meanwhile, LWP susceptibility estimates inferred from climatology in deep BLs are still poorly constrained. While susceptibility estimates in shallow BLs are found to be consistent with process modelling studies, they are overestimated as compared to pollution track estimates.

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Estimating the CMIP6 Anthropogenic Aerosol Radiative Effects with the Advantage of Prescribed Aerosol Forcing

Atmosphere ◽

10.3390/atmos12030406 ◽

2021 ◽

Vol 12 (3) ◽

pp. 406

Author(s):

Xiangjun Shi ◽

Chunhan Li ◽

Lijuan Li ◽

Wentao Zhang ◽

Jiaojiao Liu

Keyword(s):

Radiative Forcing ◽

Radiative Effects ◽

Anthropogenic Aerosol ◽

Global Average ◽

Aerosol Cloud ◽

Aerosol Forcing ◽

Simulation Results ◽

Aerosol Cloud Interactions ◽

Aerosol Radiative Effects ◽

Aerosol Radiative

The prescribed anthropogenic aerosol forcing recommended by Coupled Model Intercomparison Project Phase 6 (CMIP6) was implemented in an atmospheric model. With the reduced complexity of anthropogenic aerosol forcing, each component of anthropogenic aerosol effective radiative forcing (ERF) can be estimated by one or more calculation methods, especially for instantaneous radiative forcing (RF) from aerosol–radiation interactions (RFari) and aerosol–cloud interactions (RFaci). Simulation results show that the choice of calculation method might impact the magnitude and reliability of RFari. The RFaci—calculated by double radiation calls—is the definition-based Twomey effect, which previously was impossible to diagnose using the default model with physically based aerosol–cloud interactions. The RFari and RFaci determined from present-day simulations are very robust and can be used as offline simulation results. The robust RFari, RFaci, and corresponding radiative forcing efficiencies (i.e., the impact of environmental properties) are very useful for analyzing anthropogenic aerosol radiative effects. For instance, from 1975 to 2000, both RFari and RFaci showed a clear response to the spatial change of anthropogenic aerosol. The global average RF (RFari + RFaci) has enhanced (more negative) by ~6%, even with a slight decrease in the global average anthropogenic aerosol, and this can be explained by the spatial pattern of radiative forcing efficiency.

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On the (in)accuracy of the spherical particle approximation in mineral aerosol radiative forcing simulations

Conference on Electromagnetic and Light Scattering ◽

10.1615/ichmt.2007.confelectromagligscat.210 ◽

2007 ◽

Author(s):

Michael Kahnert ◽

Timo Nousiainen ◽

Petri Raisanen

Keyword(s):

Spherical Particle ◽

Radiative Forcing ◽

Aerosol Radiative Forcing ◽

Particle Approximation ◽

Aerosol Radiative

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Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods

Nature Communications ◽

10.1038/s41467-021-23888-1 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Hailing Jia ◽

Xiaoyan Ma ◽

Fangqun Yu ◽

Johannes Quaas

Keyword(s):

Radiative Forcing ◽

Cloud Fraction ◽

Future Climate Change ◽

Satellite Measurements ◽

Aerosol Cloud ◽

Fine Mode ◽

Sampling Biases ◽

Aerosol Cloud Interactions ◽

Significant Underestimation ◽

Weak Satellite

AbstractSatellite-based estimates of radiative forcing by aerosol–cloud interactions (RFaci) are consistently smaller than those from global models, hampering accurate projections of future climate change. Here we show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements, which tend to artificially discard the clouds with high cloud fraction. Those missed clouds exert a stronger cooling effect, and are more sensitive to aerosol perturbations. By accounting for the sampling biases, the magnitude of RFaci (from −0.38 to −0.59 W m−2) increases by 55 % globally (133 % over land and 33 % over ocean). Notably, the RFaci further increases to −1.09 W m−2 when switching total aerosol optical depth (AOD) to fine-mode AOD that is a better proxy for CCN than AOD. In contrast to previous weak satellite-based RFaci, the improved one substantially increases (especially over land), resolving a major difference with models.

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100 Years of Progress in Cloud Physics, Aerosols, and Aerosol Chemistry Research

Meteorological Monographs ◽

10.1175/amsmonographs-d-18-0024.1 ◽

2019 ◽

Vol 59 ◽

pp. 11.1-11.72 ◽

Cited By ~ 4

Author(s):

Sonia M. Kreidenweis ◽

Markus Petters ◽

Ulrike Lohmann

Keyword(s):

Radiative Forcing ◽

Cloud Microphysics ◽

Climate System ◽

Mitigation Strategies ◽

Climate Projections ◽

Weather Modification ◽

Theoretical Understanding ◽

Aerosol Cloud ◽

Chemistry Research ◽

Aerosol Cloud Interactions

Abstract This chapter reviews the history of the discovery of cloud nuclei and their impacts on cloud microphysics and the climate system. Pioneers including John Aitken, Sir John Mason, Hilding Köhler, Christian Junge, Sean Twomey, and Kenneth Whitby laid the foundations of the field. Through their contributions and those of many others, rapid progress has been made in the last 100 years in understanding the sources, evolution, and composition of the atmospheric aerosol, the interactions of particles with atmospheric water vapor, and cloud microphysical processes. Major breakthroughs in measurement capabilities and in theoretical understanding have elucidated the characteristics of cloud condensation nuclei and ice nucleating particles and the role these play in shaping cloud microphysical properties and the formation of precipitation. Despite these advances, not all their impacts on cloud formation and evolution have been resolved. The resulting radiative forcing on the climate system due to aerosol–cloud interactions remains an unacceptably large uncertainty in future climate projections. Process-level understanding of aerosol–cloud interactions remains insufficient to support technological mitigation strategies such as intentional weather modification or geoengineering to accelerating Earth-system-wide changes in temperature and weather patterns.

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