Draft:High cloud feedback
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The high cloud feedback is defined as the change in radiative flux due to the response of high altitude clouds to warming[1]. High clouds refer to clouds with a top pressure lower than 440 hPa (i.e. cloud tops above ~6500m) and include cirrus type clouds as well as cumulonimbus[2]. The high cloud feedback is one part of the total cloud feedback which is an important variable in the climate system[1]. The cloud feedback is the reason for a large part of the uncertainty in todays climate models and has a larger intermodel spread than any other radiative feedback.[3]
The cloud feedback, and therefore also the high cloud feedback, has a longwave and a shortwave part which are summed up to get the total feedback. In the current climate the CRE is positive in the longwave and negative in the shortwave regime.[4] The longwave part includes the interaction of the clouds with the longwave radiation coming from the earths surface. The longwave feedback is dominated by the altitude and temperature of the cloud top, leading currently to a positive feedback.[1][5]The shortwave CRE on the other hand include the interaction of the clouds with the shortwave radiation coming directly from the sun. The shortwave feedback is dominated by cloud amount and the optical thickness leading currently to a weak negative shortwave feedback.[1] Since the feedback strengths are depending on temperature, it is not clear that the longwave part will stay positive and the shortwave part negative as our climate changes.[1]
For high clouds the feedback is currently positive in total, as the shortwave feedback is near zero and the longwave feedback is positive.[1] It is together with the mid-level cloud feedback a larger contributor to the total cloud feedback than low clouds.[3]
The calculation and modeling of high cloud feedback states a challenge and is an active field of research.[1]
Physical Background
[edit]The high cloud feedback describes the change of radiation at the top of the atmosphere that is due to a change of high cloud properties.[1]
A negative feedback reduces the effect of a forcing back towards an equilibrium state. The shortwave part of the high cloud feedback is negative, but very close to zero.[1] It can be influenced e.g. by changes in the reflection of solar radiation by the high cloud tops and their amount.[1] A positive feedback amplifies the effect of a forcing. The longwave part of the high cloud feedback is positive.[1] This is due to the increased reduction of outgoing longwave radiation with rising temperatures, triggered by the changing amount of high clouds that absorb and reflect the terrestrial radiation.[1] The total high cloud feedback is the sum of the longwave and shortwave feedback and is positive.[4]
The high cloud properties which mainly influence the high cloud feedback are the cloud area fraction, the cloud top height and the optical depth.[1] These cloud attributes, and therefore also the cloud feedback, are not spatially homogeneous.[1] Hence the cloud feedback is mostly expressed as a global mean.[1]
The cloud feedback is quantified by measuring the difference of the radiative flux between all-sky (with clouds) and clear-sky (without clouds).[1] It remains a challenge to model the various radiative interactions and their effects on clouds without introducing biases or unwanted dependencies.[3] To gain insight to the connections between a feedback parameter and a cloud property, the model would have to realistically represent all the physical processes influencing the clouds.[3] Because of the coarse resolution of most climate models, they need to rely on cloud parameterizations, which brings about large uncertainties.[3]
Longwave Feedback
[edit]The total longwave (LW) part of the high cloud feedback is positive.[3] Contributions to the LW feedback stem from changes in cloud altitude, optical depth and cloud amount.
Cloud Altitude
[edit]The longwave feedback is dominated by the positive cloud altitude feedback[5] which is mainly found in the tropics with the mechanisms being identical in the extra tropics.[1] The LW radiation emitted by the high cloud tops is proportional to the temperature at the cloud top.[1] The altitude of the high clouds changes with rising temperatures, due to the following mechanisms:[1] Higher temperatures on the surface force the moisture to rise, which is fundamentally described by the Clausius Clapeyron equation.[1][5] The altitude at which the radiative cooling is still effective is closely tied to the humidity and rises equally.[1][5] The altitude, at which the radiative cooling becomes inefficient due to a lack of moisture, then determines the detrainment height of deep convection due to the mass conservation.[1][5] The could top height therefore strongly depends on the surface temperature.[1]
There are three theories on how the altitude and thus temperature depends on surface warming.[1] The FAT (Fixed Anvil Temperature) hypothesis argues, that the isotherms shift upwards with global warming and the temperature at the cloud top stays therefore constant.[6] This results in a positive feedback, since no more radiation is emitted while the surface temperature is rising.[6] According to the FAT hypothesis this leads to a feedback of 0,27 W m K[5]. The second hypothesis called PHAT (Proportionally Higher Anvil Temperature) claims a smaller cloud feedback of 0.20 W m K[5], due to a slight warming of the cloud tops which agrees better with observations.[5] The static stability increases with higher surface temperatures in the upper troposphere and lets the clouds shift slightly to warmer temperatures.[1] The third hypothesis is FAP (Fixed Anvil Pressure) which assumes a constant cloud top pressure with a warming climate, as if the cloud top does not move upwards.[5] This results in a negative LW feedback, which does not agree with observations.[5] It can be used to calculate the impact of the cloud height change on the LW feedback.[5] Most models agree with the PHAT hypothesis which also agrees the most with observations.[5]
Optical Depth
[edit]The optical depth feedback is determined by the increasing optical depth of the high clouds with rising temperatures.[7] The optical depth increases the LW emission of the cloud, so that the contribution of the optical depth to the LW feedback is positive.[7] At the same time, the shortwave contribution of increasing optical depth is negative and, because it is larger than the LW component, dominates. The overall optical depth feedback for high clouds is just below zero.[1]
Cloud Amount
[edit]The area fraction of high clouds is also an important part of the LW feedback. A decrease in the area fraction would lead to a more negative feedback.[1] Two mechanisms can lead to a decrease in the area fraction and therefore a negative feedback.[1] The warming at the surface decreases the moist adiabat which leads to a decrease of the clear sky subsidence.[8] Since the convective mass flux has to be equal to the clear sky subsidence it decreases as well and with it potentially the cloud area fraction.[8] Another argument for a smaller area fraction is that the self-aggregation of clouds increases at higher temperatures.[1] This would lead to smaller convective areas and larger dry areas which increase the radiative longwave cooling, resulting in a negative feedback.[1] How the area fraction will change is however a topic of ongoing research and discussion.[1] Since the area fraction of high clouds in models is sensitive, among others to cloud micro physics[1], there are also models which predict an increase in high cloud area fraction[5] which would lead to a positive feedback.
Shortwave Feedback
[edit]The total shortwave (SW) part of the high cloud feedback is negative.
The impact of cloud area fraction on the shortwave feedback with warming is a topic of discussion, similar to the LW feedback.[3] The SW high cloud feedback depends on the shot cloud area fraction due to its control of SW reflection. With a larger cloud area fraction more solar radiation can be reflected.[5] A decreasing cloud fraction would lead to a positive SW feedback.[3] It was found that the high cloud SW feedback is anticorrelated to the lapse rate feedback (the change of the temperature profile of the atmosphere with warming) which influences the cloud coverage.[5] Therefore the high cloud SW feedback could be computed together with the lapse rate feedback to simplify the calculations in climate models. It is important to note, that this is a topic of ongoing discussion.[5]
The impact of the cloud height and optical thickness on the SW feedback is negative. A higher optical thickness due to warming, changes fore example the cloud particle size and density which then changes the reflectivity of the cloud and therefore impacts the SW feedback.[1]
Challenges
[edit]It is difficult to detect the reason for a change in the SW and LW radiation due to cloud feedback, because there are a lot of cloud responses which could be the cause for a specific radiation feedback.[3] Furthermore is it difficult to not count in clear sky effects[3]. There are techniques to decompose the cloud feedbacks in models and their triggers in detail by showing the cloud fraction as a function of cloud-top pressure and the optical depth of the cloud. In the GCM, which are mostly used, the main challenge is the parametrization of clouds, especially in coarse-resolution models. The characteristics of clouds need to be parametrized in such a way, that the different feedbacks and physical interactions are as correct as possible in order to decrease the uncertainty of the models.[3]
Another challenge when dealing with (high) cloud feedbacks, is that the LW and SW part often cancel each other out, so that only a small total feedback is left.[3] The positive and negative feedback parts are not neglectable, since they can change independent of one another with rising temperature.[3]
References
[edit]- ^ a b c d e f g h i j k l m n o p q r s t u v w x y z aa ab ac ad ae af ag Ceppi, Paulo; Brient, Florent; Zelinka, Mark D.; Hartmann, Dennis L. (2017). "Cloud feedback mechanisms and their representation in global climate models". WIREs Climate Change. 8 (4). Bibcode:2017WIRCC...8E.465C. doi:10.1002/wcc.465. ISSN 1757-7780.
- ^ Ohno, Tomoki; Noda, Akira T.; Seiki, Tatsuya; Satoh, Masaki (2021). "Importance of Pressure Changes in High Cloud Area Feedback Due to Global Warming". Geophysical Research Letters. 48 (18): e2021GL093646. Bibcode:2021GeoRL..4893646O. doi:10.1029/2021GL093646. ISSN 1944-8007.
- ^ a b c d e f g h i j k l m Zelinka, Mark D.; Klein, Stephen A.; Hartmann, Dennis L. (2012-06-01). "Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels". Journal of Climate. 25 (11): 3715–3735. Bibcode:2012JCli...25.3715Z. doi:10.1175/JCLI-D-11-00248.1. ISSN 0894-8755.
- ^ a b Colman, R. A. (2015-04-27). "Climate radiative feedbacks and adjustments at the Earth's surface". Journal of Geophysical Research: Atmospheres. 120 (8): 3173–3182. Bibcode:2015JGRD..120.3173C. doi:10.1002/2014JD022896. ISSN 2169-897X.
- ^ a b c d e f g h i j k l m n o p Zelinka, Mark D.; Hartmann, Dennis L. (2010-08-27). "Why is longwave cloud feedback positive?". Journal of Geophysical Research: Atmospheres. 115 (D16). Bibcode:2010JGRD..11516117Z. doi:10.1029/2010JD013817. ISSN 0148-0227.
- ^ a b Hartmann, Dennis L.; Larson, Kristin (2002). "An important constraint on tropical cloud - climate feedback". Geophysical Research Letters. 29 (20): 1951. Bibcode:2002GeoRL..29.1951H. doi:10.1029/2002GL015835. ISSN 0094-8276.
- ^ a b Stephens, G. L. (1978-11-01). "Radiation Profiles in Extended Water Clouds. II: Parameterization Schemes". Journal of the Atmospheric Sciences. 35 (11): 2123–2132. Bibcode:1978JAtS...35.2123S. doi:10.1175/1520-0469(1978)035<2123:RPIEWC>2.0.CO;2. ISSN 0022-4928.
- ^ a b Jeevanjee, Nadir (November 2022). "Three Rules for the Decrease of Tropical Convection With Global Warming". Journal of Advances in Modeling Earth Systems. 14 (11). Bibcode:2022JAMES..1403285J. doi:10.1029/2022MS003285. ISSN 1942-2466.