Editing IPCC:AR6/WGI/Chapter-7 (section)

==== 7.4.2.8 Climate Feedbacks in ESMs ====

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Since AR5, many modelling groups have newly participated in CMIP experiments, leading to an increase in the number of models in CMIP6 [[IPCC:Wg1:Chapter:Chapter-1#1.5.4|Section 1.5.4]] ). Other modelling groups that contributed to CMIP5 also updated their ESMs for carrying out CMIP6 experiments. While some of the CMIP6 models share components and are therefore not independent, they are analysed independently when calculating climate feedbacks. This, and more subtle forms of model inter-dependence, creates challenges when determining appropriate model weighting schemes ( [[IPCC:Wg1:Chapter:Chapter-1#1.5.4|Section 1.5.4]] ). Additionally, it must be kept in mind that the ensemble sizes of the CMIP5 and CMIP6 models are not sufficiently large to sample the full range of model uncertainty.

The multi-model mean values of all physical climate feedbacks are calculated using the radiative kernel method ( [[#7.4.1|Section 7.4.1]] ) and compared with the assessment in the previous sections (Figure 7.10). For CMIP models, there is a discrepancy between the net climate feedback calculated directly using the time evolutions of Δ ''T'' and Δ ''N'' in each model and the accumulation of individual feedbacks, but it is negligibly small (Supplementary Material 7.SM.4). Feedbacks due to biogeophysical and non-CO <sub>2</sub> biogeochemical processes are included in some models but neglected in the kernel analysis. In AR6, biogeophysical and non-CO <sub>2</sub> biogeochemical feedbacks are explicitly assessed ( [[#7.4.2.5|Section 7.4.2.5]] ).

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'''Table 7.10''' '''|''' '''Synthesis assessment of climate feedbacks (central estimate shown in bold).''' The mean values and their 90% ranges in CMIP5/6 models, derived using multiple radiative kernels ( [[#Zelinka--2020|Zelinka et al., 2020]] ) are also presented for comparison.

{| class="wikitable"
|-
| rowspan="2"| Feedback Parameter α x (W m <sup>–2</sup> °C <sup>–1</sup> )

| CMIP5 GCMs

| CMIP6 ESMs

| colspan="4"| AR6 Assessed Ranges

|-
| Mean and

5–95% Interval

| Mean and

5–95% Interval

| Central Estimate

| Very likely Interval

| Likely Interval

| Level of Confidence

|-
| Planck

| –3.20 [–3.3 to –3.1]

| –3.22 [–3.3 to –3.1]

| '''–3.22'''

| –3.4 to –3.0

| –3.3 to –3.1

| ''high''

|-
| WV+LR

| 1.24 [1.08 to 1.35]

| 1.25 [1.14 to 1.45]

| '''1.30'''

| 1.1 to 1.5

| 1.2 to 1.4

| ''high''

|-
| Surface albedo

| 0.41 [0.25 to 0.56]

| 0.39 [0.26 to 0.53]

| '''0.35'''

| 0.10 to 0.60

| 0.25 to 0.45

| ''medium''

|-
| Clouds

| 0.41 [–0.09 to 1.1]

| 0.49 [–0.08 to 1.1]

| '''0.42'''

| –0.10 to 0.94

| 0.12 to 0.72

| ''high''

|-
| Biogeophysical and non-CO <sub>2</sub> biogeochemical

| Not evaluated

| Not evaluated

| '''–0.01'''

| –0.27 to 0.25

| –0.16 to 0.14

| ''low''

|-
| Residual of kernel estimates

| 0.06 [–0.17 to 0.29]

| 0.05 [–0.18 to 0.28 ]

|
|-
| '''Net''' (i.e., relevant for ECS)

| –1.08 [–1.61 to –0.68]

| –1.03 [–1.54 to –0.62]

| '''–1.16'''

| –1.81 to –0.51

| –1.54 to –0.78

| ''medium''

|-
| Long-term ice-sheet feedbacks (millennial scale)

|
| &gt;0.0

|
| ''high''

|}

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[[File:abad03bd326a3f3e49cb28d9d362a7d5 IPCC_AR6_WGI_Figure_7_10.png]]

'''Figure 7.10''' '''|''' '''Global mean climate feedbacks estimated in''' ''abrupt 4xCO2'' '''simulations of 29 CMIP5 models (light blue) and 49 CMIP6 models (orange), compared with those assessed in this Report (red).''' Individual feedbacks for CMIP models are averaged across six radiative kernels as computed in [[#Zelinka--2020|Zelinka et al. (2020)]] . The white line, black box and vertical line indicate the mean, 66% and 90% ranges, respectively. The shading represents the probability distribution across the full range of GCM/ESM values and for the 2.5–97.5 percentile range of the AR6 normal distribution. The unit is W m <sup>–2</sup> °C <sup>–1</sup> . Feedbacks associated with biogeophysical and non-CO <sub>2</sub> biogeochemical processes are assessed in AR6, but they are not explicitly estimated from general circulation models (GCMs)/Earth system models (ESMs) in CMIP5 and CMIP6. Further details on data sources and processing are available in the chapter data table (Table 7.SM.14).

All the physical climate feedbacks apart from clouds are very similar in the CMIP5 and CMIP6 model ensembles (see also Table 7.10). These values, where possible supported by other lines of evidence, are used for assessing feedbacks in Sections 7.4.2.1–7.4.2.3. A difference found between CMIP5 and CMIP6 models is the net cloud feedback, which is larger in CMIP6 by about 20%. This change is the major cause of less-negative values of the net climate feedback in CMIP6 than in CMIP5 and hence an increase in modelled ECs ( [[#7.5.1|Section 7.5.1]] ).

A remarkable improvement of cloud representation in some CMIP6 models is the reduced error of the too-weak negative shortwave CRE over the Southern Ocean ( [[#Bodas-Salcedo--2019|Bodas-Salcedo et al., 2019]] ; [[#Gettelman--2019|Gettelman et al., 2019]] ) due to a more realistic simulation of supercooled liquid droplets and associated cloud optical depths that were biased low commonly in CMIP5 models ( [[#McCoy--2014a|McCoy et al., 2014a]] , b). Because the negative cloud optical depth feedback occurs due to ‘brightening’ of clouds via phase change from ice to liquid cloud particles in response to surface warming ( [[#Cesana--2017|Cesana and]] [[#Storelvmo--2017|Storelvmo, 2017]] ), the extratropical cloud shortwave feedback tends to be less negative or even slightly positive in models with reduced errors ( [[#Bjordal--2020|Bjordal et al., 2020]] ; [[#Zelinka--2020|Zelinka et al., 2020]] ). The assessment of cloud feedbacks in ( [[#7.4.2.4|Section 7.4.2.4]] incorporates estimates from these improved ESMs. Yet, there still remain other shared model errors, such as in the subtropical low-clouds ( [[#Calisto--2014|Calisto et al., 2014]] ) and tropical anvil clouds ( [[#Mauritsen--2015|Mauritsen and]] [[#Stevens--2015|Stevens, 2015]] ), hampering an assessment of feedbacks associated with these cloud regimes based only on ESMs ( [[#7.4.2.4|Section 7.4.2.4]] ).

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