Английская Википедия:Cloud feedback
Cloud feedback is a type of climate change feedback that has been difficult to quantify in contemporary climate models. It can affect the magnitude of internally generated climate variability[1][2] or they can affect the magnitude of climate change resulting from external radiative forcings.[3] Cloud representations vary among global climate models, and small changes in cloud cover have a large impact on the climate.[4][5]
Global warming is expected to change the distribution and type of clouds.[6][7] 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.[8] Differences in planetary boundary layer cloud modeling schemes can lead to large differences in derived 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 show 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.
The closely related 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 sensitivity relative to the previous generation of models.[11][12][13]
Mechanisms
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,[17] 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.[18] 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.[19] 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.[20]
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.[21] 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,[22] it was later suggested that this finding was confounded by counteracting changes in humidity.[21]
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%.[23] 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.[24] 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.[25]
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.[27][28] 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.[29] 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.[30] 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.[31] 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.[32][28][33][34]
Role as contributor to climate sensitivity
Changes in cloud cover is one of several contributors to climate change and climate sensitivity. Шаблон:Excerpt
Current understanding in climate models
Шаблон:Further When the IPCC began to produce its IPCC Sixth Assessment Report, 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.[35]
In preparation for the 2021 IPCC Sixth Assessment Report, a new generation of climate models have been developed by scientific groups around the world.[36][37] The average estimated climate sensitivity has increased in Coupled Model Intercomparison Project Phase 6 (CMIP6) compared to the previous generation, with values spanning Шаблон:Convert across 27 global climate models and exceeding Шаблон:Convert in 10 of them.[38][39] 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.[38][40][41] Models with the highest ECS values, however, are not consistent with observed warming.[42]
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.[43]
Relationship with other feedbacks
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.[44] 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.[45]
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.[46] 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.[47]
See also
References
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite book
- ↑ Шаблон:Cite news
- ↑ Шаблон:Cite news
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite book
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite web
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite web
- ↑ Fig. TS.17, Technical Summary, Sixth Assessment Report (AR6), Working Group I, IPCC, 2021, p. 96. Archived from the original on July 21, 2022.
- ↑ Шаблон:Cite book See esp. TFE.6: Climate Sensitivity and Feedbacks at p. 82.
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ 21,0 21,1 Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite web
- ↑ 28,0 28,1 Шаблон:Cite journal
- ↑ Шаблон:Cite web
- ↑ IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 3–32, Шаблон:Doi.
- ↑ Шаблон:Cite web
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite web
- ↑ 38,0 38,1 Шаблон:Cite journal
- ↑ Шаблон:Cite web
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite news
- ↑ Шаблон:Cite web
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal
- ↑ Шаблон:Cite journal