Decomposing Effective Radiative Forcing Due to Aerosol Cloud Interactions by Global Cloud Regimes

Langton, Tom; Stier, Philip; Watson-Parris, Duncan; Mulcahy, Jane

doi:10.1029/2021gl093833

Cited by 3 publications

(6 citation statements)

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“…This increase in the percentage of cloud dimming due to thin clouds with a decrease in f c may be attributed to the high amounts and extent of variation in f thin , which are minimum for Sc‐dominated overcast cloud regime and increases coherently with scene heterogeneity as f c decreases in the Cu‐dominated regime. Such a wide range of possible variations in CRE SW,TOA , even at fixed cloud cover, highlights the dominant role of thin clouds in controlling the SW radiative effect (Goren et al., 2023; McCoy et al., 2017, 2023).…”

Section: Resultsmentioning

confidence: 99%

“…A possible explanation of the non‐linear relationship between

\mathcal{L}

and f thin for f c < 0.8 relies on the results of Goren et al. (2023), who demonstrated that the deeper the cloud cores, the thinner their anvils. These observations also aligns with our results of increase in cloud heterogeneity with f thin (as discussed previously in Section 3.2).…”

Section: Resultsmentioning

confidence: 99%

“…SW CRE is primarily governed by the changes in total cloud cover and cloud optical thickness (King, 1987; Platnick & Twomey, 1994; Twomey, 1977; Zelinka et al., 2012, 2016). Since the presence of thin clouds at a given cloud cover reduces the scene cloud optical thickness (see Figure 4b), they can significantly reduce the SW albedo and therefore the magnitude of SW CRE (Goren et al., 2023; McCoy et al., 2017, 2023). Figure 5a shows the CRE at the TOA for SW radiation (CRE SW,TOA ) in f c – f thin space.…”

Section: Resultsmentioning

confidence: 99%

“…Thin clouds can also modulate the aerosol‐cloud interactions. Studies have found that, for a given scene‐mean cloud albedo, homogeneous cloudy scenes display a larger albedo enhancement due to aerosols (Feingold et al., 2022; Goren et al., 2023). Given the intrinsic positive association between thin clouds and cloud heterogeneity (Figure 3b), high occurrence of thin clouds may dampen the susceptibility of the albedo to anthropogenic aerosols, and thus, the negative radiative forcing due to aerosol‐cloud interactions.…”

Section: Discussionmentioning

confidence: 99%

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Thin Clouds Control the Cloud Radiative Effect Along the Sc‐Cu Transition

Choudhury,

Goren

2024

JGR Atmospheres

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In situ and spaceborne studies reveal the prevalence of thin clouds in the major Stratocumulus‐to‐Cumulus Transition (SCT) regions. Using instantaneous satellite and reanalysis data, this study investigates the properties of thin clouds in the Southeast Pacific Ocean and their impact on the cloud radiative effect (CRE). Our findings demonstrate that thin clouds are intrinsic to the SCT. The overcast stratocumulus‐dominated regime exhibits a minimal presence of thin clouds, which become notably prominent after the clouds breakup into the cumulus‐dominated regime. The regime dependence of the occurrence of thin clouds is also observed in terms of the marine cold‐air outbreak parameter and the sea surface temperature. Thin clouds at a given cloud cover significantly modulate the shortwave (SW) and longwave (LW) components of CRE. SW CRE decreases by 46 %–65 % with increasing thin cloud cover. They account for a larger variance in cloud albedo than the combined influence of the liquid water path and effective radius. Furthermore, LW CRE decreases by about 12 %–52 % with thin cloud cover. An increase in the fraction of thin clouds also leads to a larger fraction of negative SW CRE offset by positive LW CRE at a given cloud cover. This LW compensation ranges from approximately 8 % at overcast cloud cover to as much as 19 % at about 50 % cloud cover. These findings elucidate the crucial role of thin clouds, and thus cloud morphology, in modulating CRE and underscore the necessity of their accurate representation in climate models.

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Section: Resultsmentioning

confidence: 99%

“…A possible explanation of the non‐linear relationship between

\mathcal{L}

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Thin Clouds Control the Cloud Radiative Effect Along the Sc‐Cu Transition

Choudhury,

Goren

2024

JGR Atmospheres

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“…Calculating the ERF aci then requires not only an analysis of how the regimes have changed but an analysis of the change in the occurrence of the regime (and potentially the combination of these two effects). This complicates the calcula tion of the ERF aci using present-day data and requires a GCM to estimate changes in regime frequency (Langton et al, 2021).…”

Section: Produce No Change In Occurrence As Aerosols Are Changedmentioning

confidence: 99%

Frontiers in Satellite‐Based Estimates of Cloud‐Mediated Aerosol Forcing

Rosenfeld,

Kokhanovsky,

Goren

et al. 2023

Reviews of Geophysics

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Atmospheric aerosols affect the Earth's climate in many ways, including acting as the seeds on which cloud droplets form. Since a large fraction of these particles is anthropogenic, the clouds' microphysical and radiative characteristics are influenced by human activity on a global scale leading to important climatic effects. The respective change in the energy budget at the top of the atmosphere is defined as the effective radiative forcing due to aerosol‐cloud interaction (ERFaci). It is estimated that the ERFaci offsets presently nearly 1/4 of the greenhouse‐induced warming, but the uncertainty is within a factor of two. A common method to calculate the ERFaci is by the multiplication of the susceptibility of the cloud radiative effect to changes in aerosols by the anthropogenic change of the aerosol concentration. This has to be done by integrating it over all cloud regimes. Here we review the various methods of the ERFaci estimation. Global measurements require satellites' global coverage. The challenge of quantifying aerosol amounts in cloudy atmospheres are met with the rapid development of novel methodologies reviewed here. The aerosol characteristics can be retrieved from space based on their optical properties, including polarization. The concentrations of the aerosols that serve as cloud drop condensation nuclei can be also estimated from their impact on the satellite‐retrieved cloud drop number concentrations. These observations are critical for reducing the uncertainty in the ERFaci calculated from global climate models (GCMs), but further development is required to allow GCMs to properly simulate and benefit these novel observables.

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Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing

Regayre¹,

Deaconu²,

Grosvenor³

et al. 2023

Atmos. Chem. Phys.

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Abstract. Aerosol radiative forcing uncertainty affects estimates of climate sensitivity and limits model skill in terms of making climate projections. Efforts to improve the representations of physical processes in climate models, including extensive comparisons with observations, have not significantly constrained the range of possible aerosol forcing values. A far stronger constraint, in particular for the lower (most-negative) bound, can be achieved using global mean energy balance arguments based on observed changes in historical temperature. Here, we show that structural deficiencies in a climate model, revealed as inconsistencies among observationally constrained cloud properties in the model, limit the effectiveness of observational constraint of the uncertain physical processes. We sample the uncertainty in 37 model parameters related to aerosols, clouds, and radiation in a perturbed parameter ensemble of the UK Earth System Model and evaluate 1 million model variants (different parameter settings from Gaussian process emulators) against satellite-derived observations over several cloudy regions. Our analysis of a very large set of model variants exposes model internal inconsistencies that would not be apparent in a small set of model simulations, of an order that may be evaluated during model-tuning efforts. Incorporating observations associated with these inconsistencies weakens any forcing constraint because they require a wider range of parameter values to accommodate conflicting information. We show that, by neglecting variables associated with these inconsistencies, it is possible to reduce the parametric uncertainty in global mean aerosol forcing by more than 50 %, constraining it to a range (around −1.3 to −0.1 W m−2) in close agreement with energy balance constraints. Our estimated aerosol forcing range is the maximum feasible constraint using our structurally imperfect model and the chosen observations. Structural model developments targeted at the identified inconsistencies would enable a larger set of observations to be used for constraint, which would then very likely narrow the uncertainty further and possibly alter the central estimate. Such an approach provides a rigorous pathway to improved model realism and reduced uncertainty that has so far not been achieved through the normal model development approach.

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Decomposing Effective Radiative Forcing Due to Aerosol Cloud Interactions by Global Cloud Regimes

Cited by 3 publications

References 23 publications

Thin Clouds Control the Cloud Radiative Effect Along the Sc‐Cu Transition

Thin Clouds Control the Cloud Radiative Effect Along the Sc‐Cu Transition

Frontiers in Satellite‐Based Estimates of Cloud‐Mediated Aerosol Forcing

Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing

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