Cloud feedback

Cloud feedback is a type of climate change feedback, where the overall cloud frequency, height, and the relative fraction of the different types of clouds are altered due to climate change, and these changes then affect the Earth's energy balance. On their own, clouds are already an important part of the climate system, as they consist of water vapor, which acts as a greenhouse gas and so contributes to warming; at the same time, they are bright and reflective of the Sun, which causes cooling. Clouds at low altitudes have a stronger cooling effect, and those at high altitudes have a stronger warming effect. Altogether, clouds make the Earth cooler than it would have been without them.

If climate change causes low-level cloud cover to become more widespread, then these clouds will increase planetary albedo and contribute to cooling, making the overall cloud feedback negative (one that slows down the warming). But if clouds become higher and thinner due to climate change, then the net cloud feedback will be positive and accelerate the warming, as clouds will be less reflective and trap more heat in the atmosphere. These processes have been represented in every major climate model from the 1980s onwards. Observations and climate model results now provide high confidence that the overall cloud feedback on climate change is positive.

However, some cloud types are more difficult to observe, and so climate models have less data about them and make different estimates about their role. Thus, models can simulate cloud feedback as very positive or only weakly positive, and these disagreements are the main reason why climate models can have substantial differences in transient climate response and climate sensitivity. In particular, a minority of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models have made headlines before the publication of the IPCC Sixth Assessment Report (AR6) due to their high estimates of equilibrium climate sensitivity. This had occurred because they estimated cloud feedback as highly positive. Those particular models were soon found to contradict both observations and paleoclimate evidence, and the AR6 used a more realistic estimate based on the majority of the models and this real-world evidence instead.

One reason why it has been more difficult to find an exact value of cloud feedbacks when compared to the others is because humans affect clouds in another major way besides the warming from greenhouse gases. Small atmospheric sulfate particles, or aerosols, are generated due to the same sulfur-heavy air pollution which also causes acid rain, but they are also very reflective, to the point their concentrations in the atmosphere cause reductions in visible sunlight known as global dimming. These particles affect the clouds in multiple ways, mostly making them more reflective. This means that changes in clouds caused by aerosols can be confused for an evidence of negative cloud feedback, and separating the two effects has been difficult.

Overview
Clouds have two major effects on the Earth's energy budget: they reflect shortwave radiation from sunlight back to space due to their high albedo, but the water vapor contained inside them also absorbs and re-emits the longwave radiation sent out by the Earth's surface as it is heated by sunlight, preventing its escape into space and retaining this heat energy for longer. In meteorology, the difference in the radiation budget caused by clouds, relative to cloud-free conditions, is described as cloud forcing, cloud radiative forcing (CRF) or cloud radiative effect (CRE) At the top of the atmosphere, it can be described by the following equation


 * $$ \Delta R_{TOA} = R_{Average} - R_{Clear} $$

The net cloud radiative effect can be decomposed into its longwave and shortwave components. This is because net radiation is absorbed solar minus the outgoing longwave radiation shown by the following equations


 * $$ \Delta R_{TOA} = \Delta Q_{abs} - \Delta OLR $$

The first term on the right is the shortwave cloud effect (Qabs ) and the second is the longwave effect (OLR).

The shortwave cloud effect is calculated by the following equation


 * $$ \Delta Q_{abs} = (S_o/4) \cdot (1 - \alpha_{cloudy}) - (S_o/4) \cdot (1 - \alpha_{clear}) $$

Where So is the solar constant, ∝cloudy is the albedo with clouds and ∝clear is the albedo on a clear day.

The longwave effect is calculated by the next following equation


 * $$ \Delta OLR = \sigma T_z^4 - F_{clear}^{up}$$

Where σ is the Stefan–Boltzmann constant, T is the temperature at the given height, and F is the upward flux in clear conditions.

Putting all of these pieces together, the final equation becomes


 * $$ \Delta R_{TOA} = (S_o/4) \cdot ((1 - \alpha_{cloudy}) - (1 - \alpha_{clear})) - \sigma T_z^4 + F_{clear}^{up} $$



Under dry, cloud-free conditions, water vapor in atmosphere contributes 67% of the greenhouse effect on Earth. When there is enough moisture to form typical cloud cover, the greenhouse effect from "free" water vapor goes down to 50%, but water vapor which is now inside the clouds amounts to 25%, and the net greenhouse effect is at 75%. According to 1990 estimates, the presence of clouds reduces the outgoing longwave radiation by about 31 W/m2. However, it also increases the global albedo from 15% to 30%, and this reduces the amount of solar radiation absorbed by the Earth by about 44 W/m2. Thus, there is a net cooling of about 13 W/m2. If the clouds were removed with all else remaining the same, the Earth would lose this much cooling and the global temperatures would increase.

Climate change increases the amount of water vapor in the atmosphere due to the Clausius–Clapeyron relation, in what is known as the water-vapor feedback. It also affects a range of cloud properties, such as their height, the typical distribution throughout the atmosphere, and cloud microphysics, such as the amount of water droplets held, all of which then affect clouds' radiative forcing. ifferences in those properties change the role of clouds in the Earth's energy budget. The name cloud feedback refers to this relationship between climate change, cloud properties, and clouds' radiative forcing. Clouds also affect the magnitude of internally generated climate variability.

Current understanding
Climate models have represented clouds and cloud processes for a very long time. Cloud feedback was already a standard feature in climate models designed in the 1980s. However, the physics of clouds are very complex, so models often represent various types of clouds in different ways, and even small variations between models can lead to significant changes in temperature and precipitation response. Climate scientists devote a lot of effort to resolving this issue. This includes the Cloud Feedback Model Intercomparison Project (CFMIP), where models simulate cloud processes under different conditions and their output is compared with the observational data. (AR6 WG1, Ch1, 223) When the Intergovernmental Panel on Climate Change had published its Sixth Assessment Report (AR6) in 2021, the uncertainty range regarding cloud feedback strength became 50% smaller since the time of the AR5 in 2014.

This happened because of major improvements in the understanding of cloud behaviour over the subtropical oceans. As the result, there was high confidence that the overall cloud feedback is positive (contributes to warming). The AR6 value for cloud feedback is +0.42 [–0.10 to 0.94] W m–2 per every 1 C-change in warming. This estimate is derived from multiple lines of evidence, including both models and observations. The tropical high-cloud amount feedback is the main remaining area for improvement. The only way total cloud feedback may still be slightly negative is if either this feedback, or the optical depth feedback in the Southern Ocean clouds is suddenly found to be "extremely large"; the probability of that is considered to be below 10%. As of 2024, most recent observations from the CALIPSO satellite instead indicate that the tropical cloud feedback is very weak.

In spite of these improvements, clouds remain the least well-understood climate feedback, and they are the main reason why models estimate differing values for equilibrium climate sensitivity (ECS). ECS is an estimate of long-term (multi-century) warming in response to a doubling in -equivalent greenhouse gas concentrations: if the future emissions are not low, it also becomes the most important factor for determining 21st century temperatures. In general, the current generation of gold-standard climate models, CMIP6, operates with larger climate sensitivity then the previous generation, and this is largely because cloud feedback is about 20% more positive then it was in CMIP5.

However, the median cloud feedback is only slightly larger in CMIP6 than it was in CMIP5; the average is so much higher only because several "hot" models have much stronger cloud feedback and higher sensitivity than the rest. Those models have a sensitivity of 5 C and their presence had increased the median model sensitivity from 3.2 C in CMIP5 to 3.7 C in CMIP6. These model results had attracted considerable attention when they were first published in 2019, as they would have meant faster and more severe warming if they were accurate. It was soon found that the output of those "hot" models is inconsistent with both observations and paleoclimate evidence, so the consensus AR6 value for cloud feedback is smaller than the mean model output alone. The best estimate of climate sensitivity in AR6 is at 3 C, as this is in a better agreement with observations and paleoclimate findings.

Role of aerosols


Atmospheric aerosols—fine partices suspended in the air—affect cloud formation and properties, which also alters their impact on climate. While some aerosols, such as black carbon particles, make the clouds darker and thus contribute to warming, by far the strongest effect is from sulfates, which increase the number of cloud droplets, making the clouds more reflective, and helping them cool the climate more. That is known as a direct aerosol effect; however, aerosols also have an indirect effect on liquid water path, and determing it involves computationally heavy continuous calculations of evaporation and condensation within clouds. Climate models generally assume that aerosols increase liquid water path, which makes the clouds even more reflective. However, satellite observations taken in 2010s suggested that aerosols decreased liquid water path instead, and in 2018, this was reproduced in a model which integrated more complex cloud microphysics. Yet, 2019 research found that earlier satellite observations were biased by failing to account for the thickest, most water-heavy clouds naturally raining more and shedding more particulates: very strong aerosol cooling was seen when comparing clouds of the same thickness.

Moreover, large-scale observations can be confounded by changes in other atmospheric factors, like humidity: i.e. it was found that while post-1980 improvements in air quality would have reduced the number of clouds over the East Coast of the United States by around 20%, this was offset by the increase in relative humidity caused by atmospheric response to AMOC slowdown. Similarly, while the initial research looking at sulfates from the 2014–2015 eruption of Bárðarbunga found that they caused no change in liquid water path, it was later suggested that this finding was confounded by counteracting changes in humidity. To avoid confounders, many observations of aerosol effects focus on ship tracks, but post-2020 research found that visible ship tracks are a poor proxy for other clouds, and estimates derived from them overestimate aerosol cooling by as much as 200%. At the same time, other research found that the majority of ship tracks are "invisible" to satellites, meaning that the earlier research had underestimated aerosol cooling by overlooking them. Finally, 2023 research indicates that all climate models have underestimated sulfur emissions from volcanoes which occur in the background, outside of major eruptions, and so had consequently overestimated the cooling provided by anthropogenic aerosols, especially in the Arctic climate. Estimates of how much aerosols affect cloud cooling are very important, because the amount of sulfate aerosols in the air had undergone dramatic changes in the recent decades. First, it had increased greatly from 1950s to 1980s, largely due to the widespread burning of sulfur-heavy coal, which caused an observable reduction in visible sunlight that had been described as global dimming. Then, it started to decline substantially from the 1990s onwards and is expected to continue to decline in the future, due to the measures to combat acid rain and other impacts of air pollution. Consequently, the aerosols provided a considerable cooling effect which counteracted or "masked" some of the greenhouse effect from human emissions, and this effect had been declining as well, which contributed to acceleration of climate change.

Climate models do account for the presence of aerosols and their recent and future decline in their projections, and typically estimate that the cooling they provide in 2020s is similar to the warming from human-added atmospheric methane, meaning that simultaneous reductions in both would effectively cancel each other out. However, the existing uncertainty about aerosol-cloud interactions likewise introduces uncertainty into models, particularly when concerning predictions of changes in weather events over the regions with a poorer historical record of atmospheric observations.

Possible climate tipping point
In 2019, a study employed a large eddy simulation model to estimate that equatorial stratocumulus clouds could break up and scatter when carbon dioxide levels rise above 1,200 ppm (almost three times higher than the current levels, and over 4 times greater than the preindustrial levels). The study estimated that this would cause a surface warming of about 8 C-change globally and 10 C-change in the subtropics, which would be in addition to at least 4 C-change already caused by such concentrations. In addition, stratocumulus clouds would not reform until the concentrations drop to a much lower level. It was suggested that this finding could help explain past episodes of unusually rapid warming such as Paleocene-Eocene Thermal Maximum In 2020, further work from the same authors revealed that in their large eddy simulation, this tipping point cannot be stopped with solar geoengineering: in a hypothetical scenario where very high emissions continue for a long time but are offset with extensive solar geoengineering, the break-up of stratocumulus clouds is simply delayed until  concentrations hit 1,700 ppm, at which point it would still cause around 5 C-change of unavoidable warming.

However, because large eddy simulation models are simpler and smaller-scale than the general circulation models used for climate projections, with limited representation of atmospheric processes like subsidence, this finding is currently considered speculative. Other scientists say that the model used in that study unrealistically extrapolates the behavior of small cloud areas onto all cloud decks, and that it is incapable of simulating anything other than a rapid transition, with some comparing it to "a knob with two settings". Additionally, concentrations would only reach 1,200 ppm if the world follows Representative Concentration Pathway 8.5, which represents the highest possible greenhouse gas emission scenario and involves a massive expansion of coal infrastructure. In that case, 1,200 ppm would be passed shortly after 2100.