Cloud feedback is a type of climate change feedback that has been difficult to quantify in climate models. Clouds can either amplify or dampen the effects of climate change by influencing Earth's energy balance. This is because clouds can affect the magnitude of climate change resulting from external radiative forcings. [1] On the other hand, clouds can affect the magnitude of internally generated climate variability. [2] [3] Climate models represent clouds in different ways, and small changes in cloud cover in the models have a large impact on the predicted climate. [4] [5] Changes in cloud cover are closely coupled with other feedbacks, including the water vapor feedback and ice–albedo feedback.
Climate change is expected to change the distribution and type of clouds. This can relate to "the spectrum of cloud types, the cloud fraction and height, the radiative properties of clouds, and finally the Earth’s radiation budget". [6]: 2224 If cloud cover increases, more sunlight will be reflected back into space, cooling the planet. If clouds become higher and thinner, they act as an insulator, reflecting heat from below back downwards and warming the planet. [7]
Seen from below, clouds emit infrared radiation back to the surface, and so exert a warming effect. But seen from above, clouds reflect sunlight and emit infrared radiation to space, and so exert a cooling effect. [8] Differences in planetary boundary layer cloud modeling can lead to large differences in calculated values of climate sensitivity. A model that decreases boundary layer clouds in response to global warming has a climate sensitivity twice that of a model that does not include this feedback. [9] However, satellite data shows that cloud optical thickness actually increases with increasing temperature. [10] Whether the net effect is warming or cooling depends on details such as the type and altitude of the cloud; details that are difficult to represent in climate models.
In preparation for the 2021 IPCC Sixth Assessment Report, a new generation of climate models have been developed by scientific groups around the world. [11] [12] The average estimated climate sensitivity has increased in Coupled Model Intercomparison Project Phase 6 (CMIP6) compared to the previous generation. Values range from 1.8 to 5.6 °C (3.2 to 10.1 °F) across 27 global climate models. [13] [14] The cause of the increased equilibrium climate sensitivity (ECS) lies mainly in improved modelling of clouds. Temperature rises are now believed to cause sharper decreases in the number of low clouds, and fewer low clouds means more sunlight is absorbed by the planet and less reflected to space. [13] [15] [16]
According to the IPCC Sixth Assessment Report, cloud feedback is "a climate feedback involving changes in any of the properties of clouds as a response to a change in the local or global surface temperature". [6]: 2224
Changes in climate may "affect the spectrum of cloud types, the cloud fraction and height, the radiative properties of clouds, and finally the Earth’s radiation budget". [6]: 2224 All of these factors have an impact on the magnitude of cloud feedback and whether it is positive (amplifying) or negative (reducing).
Global warming is expected to change the distribution and type of clouds. Seen from below, clouds emit infrared radiation back to the surface, and so exert a warming effect; seen from above, clouds reflect sunlight and emit infrared radiation to space, and so exert a cooling effect. Whether the net effect is warming or cooling depends on details such as the type and altitude of the cloud. Low clouds are brighter and optically thicker, while high clouds are optically thin (transparent) in the visible and trap IR. Reduction of low clouds tends to increase incoming solar radiation and therefore have a positive feedback, while a reduction in high clouds (since they mostly just trap IR) would result in a negative feedback. These details were poorly observed before the advent of satellite data and are difficult to represent in climate models. [20] Global climate models were showing a near-zero to moderately strong positive net cloud feedback, but the effective climate sensitivity has increased substantially in the latest generation of global climate models. Differences in the physical representation of clouds in models drive this enhanced climate sensitivity relative to the previous generation of models. [21] [22] [23]
A 2019 simulation predicts that if greenhouse gases reach three times the current level of atmospheric carbon dioxide that stratocumulus clouds could abruptly disperse, contributing to additional global warming. [24] [25]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, [26] 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. [27] 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. [28] 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. [29]
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. [30] 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, [31] it was later suggested that this finding was confounded by counteracting changes in humidity. [30]
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%. [32] 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. [33] 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. [34]
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. [36] [37] 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. [38] 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. [39] 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. [40] 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. [41] [37] [42] [43]
In meteorology, cloud forcing, cloud radiative forcing (CRF) or cloud radiative effect (CRE) is the difference between the radiation budget components for average cloud conditions and cloud-free conditions. Much of the interest in cloud forcing relates to its role as a feedback process in the present period of climate change. [44]
All global climate models used for climate change projections include the effects of water vapor and cloud forcing. The models include the effects of clouds on both incoming (solar) and emitted (terrestrial) radiation.
Clouds increase the global reflection of solar radiation from 15% to 30%, reducing the amount of solar radiation absorbed by the Earth by about 44 W/m2. This cooling is offset somewhat by the greenhouse effect of clouds which reduces the outgoing longwave radiation by about 31 W/m2. Thus the net cloud forcing of the radiation budget is a loss of about 13 W/m2. [45] If the clouds were removed with all else remaining the same, the Earth would gain this last amount in net radiation and begin to warm up.
These numbers should not be confused with the usual radiative forcing concept, which is for the change in forcing related to climate change.
Without the inclusion of clouds, water vapor alone contributes 36% to 70% of the greenhouse effect on Earth. When water vapor and clouds are considered together, the contribution is 66% to 85%. The ranges come about because there are two ways to compute the influence of water vapor and clouds: the lower bounds are the reduction in the greenhouse effect if water vapor and clouds are removed from the atmosphere leaving all other greenhouse gases unchanged, while the upper bounds are the greenhouse effect introduced if water vapor and clouds are added to an atmosphere with no other greenhouse gases. [46] The two values differ because of overlap in the absorption and emission by the various greenhouse gases. Trapping of the long-wave radiation due to the presence of clouds reduces the radiative forcing of the greenhouse gases compared to the clear-sky forcing. However, the magnitude of the effect due to clouds varies for different greenhouse gases. Relative to clear skies, clouds reduce the global mean radiative forcing due to CO2 by about 15%, [47] that due to CH4 and N2O by about 20%, [47] and that due to the halocarbons by up to 30%. [48] [49] [50] Clouds remain one of the largest uncertainties in future projections of climate change by global climate models, owing to the physical complexity of cloud processes and the small scale of individual clouds relative to the size of the model computational grid.
The following equation calculates this change in the radiation budget at the top of the atmosphere [51]
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
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
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
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
Changes in cloud cover is one of several contributors to climate change and climate sensitivity.
The radiative forcing caused by a doubling of atmospheric CO2 levels (from the pre-industrial 280 ppm) is approximately 3.7 watts per square meter (W/m2). In the absence of feedbacks, the energy imbalance would eventually result in roughly 1 °C (1.8 °F) of global warming. That figure is straightforward to calculate by using the Stefan–Boltzmann law [52] [53] and is undisputed. [54]
A further contribution arises from climate feedbacks, both self-reinforcing and balancing. [55] [56] The uncertainty in climate sensitivity estimates is entirely from the modelling of feedbacks in the climate system, including water vapour feedback, ice–albedo feedback, cloud feedback, and lapse rate feedback. [54] Balancing feedbacks tend to counteract warming by increasing the rate at which energy is radiated to space from a warmer planet. Exacerbating feedbacks increase warming; for example, higher temperatures can cause ice to melt, which reduces the ice area and the amount of sunlight the ice reflects, which in turn results in less heat energy being radiated back into space. Climate sensitivity depends on the balance between those feedbacks. [53]When the IPCC began to produce its IPCC Sixth Assessment Report in 2020, many climate models began to show a higher climate sensitivity. The estimates for Equilibrium Climate Sensitivity changed from 3.2 °C to 3.7 °C and the estimates for the Transient climate response from 1.8 °C, to 2.0 °C. That is probably because of better understanding of the role of clouds and aerosols. [57]
In preparation for the 2021 IPCC Sixth Assessment Report, a new generation of climate models have been developed by scientific groups around the world. [11] [12] The average estimated climate sensitivity has increased in Coupled Model Intercomparison Project Phase 6 (CMIP6) compared to the previous generation, with values spanning 1.8 to 5.6 °C (3.2 to 10.1 °F) across 27 global climate models and exceeding 4.5 °C (8.1 °F) in 10 of them. [13] [14] The cause of the increased equilibrium climate sensitivity (ECS) lies mainly in improved modelling of clouds. Temperature rises are now believed to cause sharper decreases in the number of low clouds, and fewer low clouds means more sunlight is absorbed by the planet and less reflected to space. [13] [15] [16] Models with the highest ECS values, however, are not consistent with observed warming. [58]
A 2019 simulation predicts that if greenhouse gases reach three times the current level of atmospheric carbon dioxide that stratocumulus clouds could abruptly disperse, contributing to additional global warming. [59]
In addition to how clouds themselves will respond to increased temperatures, other feedbacks affect clouds properties and formation. The amount and vertical distribution of water vapor is closely linked to the formation of clouds. Ice crystals have been shown to largely influence the amount of water vapor. [60] Water vapor in the subtropical upper troposphere has been linked to the convection of water vapor and ice. Changes in subtropical humidity could provide a negative feedback that decreases the amount of water vapor which in turn would act to mediate global climate transitions. [61]
Changes in cloud cover are closely coupled with other feedback, including the water vapor feedback and ice–albedo feedback. Changing climate is expected to alter the relationship between cloud ice and supercooled cloud water, which in turn would influence the microphysics of the cloud which would result in changes in the radiative properties of the cloud. Climate models suggest that a warming will increase fractional cloudiness. The albedo of increased cloudiness cools the climate, resulting in a negative feedback; while the reflection of infrared radiation by clouds warms the climate, resulting in a positive feedback. [62] Increasing temperatures in the polar regions is expected in increase the amount of low-level clouds, whose stratification prevents the convection of moisture to upper levels. This feedback would partially cancel the increased surface warming due to the cloudiness. This negative feedback has less effect than the positive feedback. The upper atmosphere more than cancels negative feedback that causes cooling, and therefore the increase of CO2 is actually exacerbating the positive feedback as more CO2 enters the system. [63]
Interestingly, the true feedback is consistently weaker than the constant relative humidity value, implying a small but robust reduction in relative humidity in all models on average clouds appear to provide a positive feedback in all models
Cloud feedback is a type of climate change feedback that has been difficult to quantify in climate models. Clouds can either amplify or dampen the effects of climate change by influencing Earth's energy balance. This is because clouds can affect the magnitude of climate change resulting from external radiative forcings. [1] On the other hand, clouds can affect the magnitude of internally generated climate variability. [2] [3] Climate models represent clouds in different ways, and small changes in cloud cover in the models have a large impact on the predicted climate. [4] [5] Changes in cloud cover are closely coupled with other feedbacks, including the water vapor feedback and ice–albedo feedback.
Climate change is expected to change the distribution and type of clouds. This can relate to "the spectrum of cloud types, the cloud fraction and height, the radiative properties of clouds, and finally the Earth’s radiation budget". [6]: 2224 If cloud cover increases, more sunlight will be reflected back into space, cooling the planet. If clouds become higher and thinner, they act as an insulator, reflecting heat from below back downwards and warming the planet. [7]
Seen from below, clouds emit infrared radiation back to the surface, and so exert a warming effect. But seen from above, clouds reflect sunlight and emit infrared radiation to space, and so exert a cooling effect. [8] Differences in planetary boundary layer cloud modeling can lead to large differences in calculated values of climate sensitivity. A model that decreases boundary layer clouds in response to global warming has a climate sensitivity twice that of a model that does not include this feedback. [9] However, satellite data shows that cloud optical thickness actually increases with increasing temperature. [10] Whether the net effect is warming or cooling depends on details such as the type and altitude of the cloud; details that are difficult to represent in climate models.
In preparation for the 2021 IPCC Sixth Assessment Report, a new generation of climate models have been developed by scientific groups around the world. [11] [12] The average estimated climate sensitivity has increased in Coupled Model Intercomparison Project Phase 6 (CMIP6) compared to the previous generation. Values range from 1.8 to 5.6 °C (3.2 to 10.1 °F) across 27 global climate models. [13] [14] The cause of the increased equilibrium climate sensitivity (ECS) lies mainly in improved modelling of clouds. Temperature rises are now believed to cause sharper decreases in the number of low clouds, and fewer low clouds means more sunlight is absorbed by the planet and less reflected to space. [13] [15] [16]
According to the IPCC Sixth Assessment Report, cloud feedback is "a climate feedback involving changes in any of the properties of clouds as a response to a change in the local or global surface temperature". [6]: 2224
Changes in climate may "affect the spectrum of cloud types, the cloud fraction and height, the radiative properties of clouds, and finally the Earth’s radiation budget". [6]: 2224 All of these factors have an impact on the magnitude of cloud feedback and whether it is positive (amplifying) or negative (reducing).
Global warming is expected to change the distribution and type of clouds. Seen from below, clouds emit infrared radiation back to the surface, and so exert a warming effect; seen from above, clouds reflect sunlight and emit infrared radiation to space, and so exert a cooling effect. Whether the net effect is warming or cooling depends on details such as the type and altitude of the cloud. Low clouds are brighter and optically thicker, while high clouds are optically thin (transparent) in the visible and trap IR. Reduction of low clouds tends to increase incoming solar radiation and therefore have a positive feedback, while a reduction in high clouds (since they mostly just trap IR) would result in a negative feedback. These details were poorly observed before the advent of satellite data and are difficult to represent in climate models. [20] Global climate models were showing a near-zero to moderately strong positive net cloud feedback, but the effective climate sensitivity has increased substantially in the latest generation of global climate models. Differences in the physical representation of clouds in models drive this enhanced climate sensitivity relative to the previous generation of models. [21] [22] [23]
A 2019 simulation predicts that if greenhouse gases reach three times the current level of atmospheric carbon dioxide that stratocumulus clouds could abruptly disperse, contributing to additional global warming. [24] [25]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, [26] 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. [27] 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. [28] 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. [29]
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. [30] 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, [31] it was later suggested that this finding was confounded by counteracting changes in humidity. [30]
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%. [32] 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. [33] 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. [34]
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. [36] [37] 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. [38] 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. [39] 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. [40] 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. [41] [37] [42] [43]
In meteorology, cloud forcing, cloud radiative forcing (CRF) or cloud radiative effect (CRE) is the difference between the radiation budget components for average cloud conditions and cloud-free conditions. Much of the interest in cloud forcing relates to its role as a feedback process in the present period of climate change. [44]
All global climate models used for climate change projections include the effects of water vapor and cloud forcing. The models include the effects of clouds on both incoming (solar) and emitted (terrestrial) radiation.
Clouds increase the global reflection of solar radiation from 15% to 30%, reducing the amount of solar radiation absorbed by the Earth by about 44 W/m2. This cooling is offset somewhat by the greenhouse effect of clouds which reduces the outgoing longwave radiation by about 31 W/m2. Thus the net cloud forcing of the radiation budget is a loss of about 13 W/m2. [45] If the clouds were removed with all else remaining the same, the Earth would gain this last amount in net radiation and begin to warm up.
These numbers should not be confused with the usual radiative forcing concept, which is for the change in forcing related to climate change.
Without the inclusion of clouds, water vapor alone contributes 36% to 70% of the greenhouse effect on Earth. When water vapor and clouds are considered together, the contribution is 66% to 85%. The ranges come about because there are two ways to compute the influence of water vapor and clouds: the lower bounds are the reduction in the greenhouse effect if water vapor and clouds are removed from the atmosphere leaving all other greenhouse gases unchanged, while the upper bounds are the greenhouse effect introduced if water vapor and clouds are added to an atmosphere with no other greenhouse gases. [46] The two values differ because of overlap in the absorption and emission by the various greenhouse gases. Trapping of the long-wave radiation due to the presence of clouds reduces the radiative forcing of the greenhouse gases compared to the clear-sky forcing. However, the magnitude of the effect due to clouds varies for different greenhouse gases. Relative to clear skies, clouds reduce the global mean radiative forcing due to CO2 by about 15%, [47] that due to CH4 and N2O by about 20%, [47] and that due to the halocarbons by up to 30%. [48] [49] [50] Clouds remain one of the largest uncertainties in future projections of climate change by global climate models, owing to the physical complexity of cloud processes and the small scale of individual clouds relative to the size of the model computational grid.
The following equation calculates this change in the radiation budget at the top of the atmosphere [51]
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
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
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
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
Changes in cloud cover is one of several contributors to climate change and climate sensitivity.
The radiative forcing caused by a doubling of atmospheric CO2 levels (from the pre-industrial 280 ppm) is approximately 3.7 watts per square meter (W/m2). In the absence of feedbacks, the energy imbalance would eventually result in roughly 1 °C (1.8 °F) of global warming. That figure is straightforward to calculate by using the Stefan–Boltzmann law [52] [53] and is undisputed. [54]
A further contribution arises from climate feedbacks, both self-reinforcing and balancing. [55] [56] The uncertainty in climate sensitivity estimates is entirely from the modelling of feedbacks in the climate system, including water vapour feedback, ice–albedo feedback, cloud feedback, and lapse rate feedback. [54] Balancing feedbacks tend to counteract warming by increasing the rate at which energy is radiated to space from a warmer planet. Exacerbating feedbacks increase warming; for example, higher temperatures can cause ice to melt, which reduces the ice area and the amount of sunlight the ice reflects, which in turn results in less heat energy being radiated back into space. Climate sensitivity depends on the balance between those feedbacks. [53]When the IPCC began to produce its IPCC Sixth Assessment Report in 2020, many climate models began to show a higher climate sensitivity. The estimates for Equilibrium Climate Sensitivity changed from 3.2 °C to 3.7 °C and the estimates for the Transient climate response from 1.8 °C, to 2.0 °C. That is probably because of better understanding of the role of clouds and aerosols. [57]
In preparation for the 2021 IPCC Sixth Assessment Report, a new generation of climate models have been developed by scientific groups around the world. [11] [12] The average estimated climate sensitivity has increased in Coupled Model Intercomparison Project Phase 6 (CMIP6) compared to the previous generation, with values spanning 1.8 to 5.6 °C (3.2 to 10.1 °F) across 27 global climate models and exceeding 4.5 °C (8.1 °F) in 10 of them. [13] [14] The cause of the increased equilibrium climate sensitivity (ECS) lies mainly in improved modelling of clouds. Temperature rises are now believed to cause sharper decreases in the number of low clouds, and fewer low clouds means more sunlight is absorbed by the planet and less reflected to space. [13] [15] [16] Models with the highest ECS values, however, are not consistent with observed warming. [58]
A 2019 simulation predicts that if greenhouse gases reach three times the current level of atmospheric carbon dioxide that stratocumulus clouds could abruptly disperse, contributing to additional global warming. [59]
In addition to how clouds themselves will respond to increased temperatures, other feedbacks affect clouds properties and formation. The amount and vertical distribution of water vapor is closely linked to the formation of clouds. Ice crystals have been shown to largely influence the amount of water vapor. [60] Water vapor in the subtropical upper troposphere has been linked to the convection of water vapor and ice. Changes in subtropical humidity could provide a negative feedback that decreases the amount of water vapor which in turn would act to mediate global climate transitions. [61]
Changes in cloud cover are closely coupled with other feedback, including the water vapor feedback and ice–albedo feedback. Changing climate is expected to alter the relationship between cloud ice and supercooled cloud water, which in turn would influence the microphysics of the cloud which would result in changes in the radiative properties of the cloud. Climate models suggest that a warming will increase fractional cloudiness. The albedo of increased cloudiness cools the climate, resulting in a negative feedback; while the reflection of infrared radiation by clouds warms the climate, resulting in a positive feedback. [62] Increasing temperatures in the polar regions is expected in increase the amount of low-level clouds, whose stratification prevents the convection of moisture to upper levels. This feedback would partially cancel the increased surface warming due to the cloudiness. This negative feedback has less effect than the positive feedback. The upper atmosphere more than cancels negative feedback that causes cooling, and therefore the increase of CO2 is actually exacerbating the positive feedback as more CO2 enters the system. [63]
Interestingly, the true feedback is consistently weaker than the constant relative humidity value, implying a small but robust reduction in relative humidity in all models on average clouds appear to provide a positive feedback in all models