Editing Cloud feedback (section)

== Representation in climate models ==
[[File:20220726_Feedbacks_affecting_global_warming_and_climate_change_-_block_diagram.svg|right|thumb|Examples of some [[Effects of climate change|effects of global warming]] that can amplify ([[positive feedback]]s) or reduce ([[negative feedback]]s) global warming<ref name="NASA_IntegratedSystem2">{{cite web |date=2016 |title=The Study of Earth as an Integrated System |url=https://climate.nasa.gov/nasa_science/science/ |url-status=live |archive-url=https://web.archive.org/web/20161102022200/https://climate.nasa.gov/nasa_science/science/ |archive-date=November 2, 2016 |website=nasa.gov |publisher=NASA}}</ref>]][[Climate model]]s 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.<ref name="Wetherald1988" /><ref name="Cess1990" /><ref name="Fowler1996" /> 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.<ref name="Cess1990" /> [[Climate scientist]]s 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 [[error bar|uncertainty range]] regarding cloud feedback strength became 50% smaller since the time of the [[IPCC Fifth Assessment Report|AR5]] in 2014.<ref name="IPCC_AR6_WG1_TS" />{{rp|95}} 
[[File:McKim 2024 tropical clouds.jpg|thumb|Tropical clouds are known to have a cooling effect, but it is uncertain whether it would become stronger or weaker in the future<ref name="McKim2024" />]]
{| class="wikitable"
|+Remaining uncertainty about cloud feedbacks in [[IPCC Sixth Assessment Report]]<ref name="IPCC AR6 WG1 CH7" />{{rp|975}}
! Feedback !! Direction !! Confidence		
|-		
| High-cloud altitude feedback || Positive || High 	
|- 						
| Tropical high-cloud amount feedback || Negative || Low 	
|- 		
| Subtropical marine low-cloud feedback || Positive || High
|- 		
| Land cloud feedback || Positive || Low 	 	
|-		
| Mid-latitude cloud amount feedback  || Positive || Medium 	
|- 		
| Extratropical cloud optical depth feedback || Small negative || Medium 		
|- 		
| Arctic cloud feedback || Small positive || Low 	
|- 		
| Net cloud feedback || Positive || High 	
|}

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).<ref name="IPCC_AR6_WG1_TS" />{{rp|95}} The AR6 value for cloud feedback is +0.42 [–0.10 to 0.94] W m–2 per every {{convert|1|C-change|F-change}} in warming. This estimate is derived from multiple lines of evidence, including both models and observations.<ref name="IPCC_AR6_WG1_TS" />{{rp|95}} 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%.<ref name="IPCC AR6 WG1 CH7" />{{rp|975}} As of 2024, most recent observations from the [[CALIPSO]] satellite instead indicate that the tropical cloud feedback is very weak.<ref>{{cite journal |last1=Raghuraman |first1=Shiv Priyam |last2=Medeiros |first2=Brian |last3=Gettelman |first3=Andrew |date=30 March 2024 |title=Observational quantification of tropical high cloud changes and feedbacks |journal=Journal of Geophysical Research: Atmospheres |volume=129 |issue=7 |page=e2023JD039364 |doi=10.1029/2023JD039364 |doi-access=free |bibcode=2024JGRD..12939364R }}</ref><ref name="McKim2024" />

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 {{CO2}}-equivalent greenhouse gas concentrations: if the future emissions are not low, it also becomes the most important factor for determining 21st century temperatures.<ref name="IPCC_AR6_WG1_TS" />{{rp|95}} In general, the current generation of gold-standard climate models, [[CMIP6]], operates with larger climate sensitivity than the previous generation, and this is largely because cloud feedback is about 20% more positive than it was in CMIP5.<ref name="IPCC_AR6_WG1_TS" />{{rp|93}}<ref name="Zelinka2020" />

However, the ''median'' cloud feedback is only slightly larger in CMIP6 than it was in CMIP5;<ref name="IPCC_AR6_WG1_TS" />{{rp|95}} the average is so much higher only because several [[Hot model|"hot" models]] have much stronger cloud feedback and higher sensitivity than the rest.<ref name="IPCC_AR6_WG1_TS" />{{rp|93}}<ref name="VoosenSciMag2022" /> Those models have a sensitivity of {{cvt|5|C|F}} and their presence had increased the median model sensitivity from {{cvt|3.2|C|F}} in CMIP5 to {{cvt|3.7|C|F}} in CMIP6.<ref name="SD2020" /> 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.<ref name="NClimate2019" /><ref name="Fr242020" /> 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 {{cvt|3|C|F}}, as this is in a better agreement with observations and paleoclimate findings.<ref name="IPCC_AR6_WG1_TS" />{{rp|93}}<ref name="Zhu2020" /><ref name="EricksonPhys2020" />