scholarly journals Evaluating climate models' cloud feedbacks against expert judgement

2021 ◽  
Author(s):  
Mark D. Zelinka ◽  
Stephen A. Klein ◽  
Yi Qin
Keyword(s):  
Climate Models ◽  
Expert Judgement ◽  
Cloud Feedbacks

scholarly journals Evaluating climate models’ cloud feedbacks against expert judgement

2022 ◽  
Author(s):  
Mark D. Zelinka ◽  
Stephen A. Klein ◽  
Yi Qin ◽  
Timothy A. Myers
Keyword(s):  
Climate Models ◽  
Expert Judgement ◽  
Cloud Feedbacks

scholarly journals Evaluating climate models' cloud feedbacks against expert judgement

2021 ◽  
Author(s):  
Mark D. Zelinka ◽  
Stephen A. Klein ◽  
Yi Qin
Keyword(s):  
Climate Models ◽  
Expert Judgement ◽  
Cloud Feedbacks

scholarly journals The Cloud Feedback Model Intercomparison Project (CFMIP) Diagnostic Codes Catalogue – metrics, diagnostics and methodologies to evaluate, understand and improve the representation of clouds and cloud feedbacks in climate models

2017 ◽  
Author(s):  
Yoko Tsushima ◽  
Florent Brient ◽  
Stephen A. Klein ◽  
Dimitra Konsta ◽  
Christine Nam ◽  
...  
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Evaluation Studies ◽  
Circulation Model ◽  
Community Analysis ◽  
Model Intercomparison ◽  
Cloud Feedbacks ◽  
Diagnostic Codes ◽  
Feedback Model ◽  
Intercomparison Project

Abstract. The CFMIP Diagnostic Codes Catalogue assembles cloud metrics, diagnostics and methodologies, together with programs to diagnose them from General Circulation Model (GCM) outputs written by various members of the CFMIP community. This aims to facilitate use of the diagnostics by the wider community studying climate and climate change. This paper describes the diagnostics and metrics which are currently in the catalogue, together with examples of their application to model evaluation studies and a summary of some of the insights these diagnostics have provided on the main shortcomings in current GCMs. Analysis of outputs from CFMIP and CMIP6 experiments will also be facilitated by the sharing of diagnostic codes via this catalogue. Any code which implements diagnostics relevant to analysing clouds – including cloud-circulation interactions and the contribution of clouds to estimates of climate sensitivity in models – and which is documented in peer-reviewed studies can be included in the catalogue. We very much welcome additional contributions to further support community analysis of CMIP6 outputs.

scholarly journals On the Potential for Abrupt Arctic Winter Sea Ice Loss

2016 ◽  
Vol 29 (7) ◽  
pp. 2703-2719 ◽  
Author(s):  
S. Bathiany ◽  
D. Notz ◽  
T. Mauritsen ◽  
G. Raedel ◽  
V. Brovkin
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Climate Models ◽  
Climate Model ◽  
Multiple Steady States ◽  
Cloud Feedbacks ◽  
Ice Coverage ◽  
Threshold Mechanism ◽  
Co2 Levels ◽  
Perennial Ice

Abstract The authors examine the transition from a seasonally ice-covered Arctic to an Arctic Ocean that is sea ice free all year round under increasing atmospheric CO2 levels. It is shown that in comprehensive climate models, such loss of Arctic winter sea ice area is faster than the preceding loss of summer sea ice area for the same rate of warming. In two of the models, several million square kilometers of winter sea ice are lost within only one decade. It is shown that neither surface albedo nor cloud feedbacks can explain the rapid winter ice loss in the climate model MPI-ESM by suppressing both feedbacks in the model. The authors argue that the large sensitivity of winter sea ice area in the models is caused by the asymmetry between melting and freezing: an ice-free summer requires the complete melt of even the thickest sea ice, which is why the perennial ice coverage decreases only gradually as more and more of the thinner ice melts away. In winter, however, sea ice areal coverage remains high as long as sea ice still forms, and then drops to zero wherever the ocean warms sufficiently to no longer form ice during winter. The loss of basinwide Arctic winter sea ice area, however, is still gradual in most models since the threshold mechanism proposed here is reversible and not associated with the existence of multiple steady states. As this occurs in every model analyzed here and is independent of any specific parameterization, it is likely to be relevant in the real world.

scholarly journals The impact of parametrized convection on cloud feedback

2015 ◽  
Vol 373 (2054) ◽  
pp. 20140414 ◽  
Author(s):  
Mark J. Webb ◽  
Adrian P. Lock ◽  
Christopher S. Bretherton ◽  
Sandrine Bony ◽  
Jason N. S. Cole ◽  
...  
Keyword(s):  
Climate Models ◽  
Correction Method ◽  
Cloud Feedback ◽  
Temperature Perturbation ◽  
Cloud Feedbacks ◽  
Stratocumulus Clouds ◽  
Shallow Clouds ◽  
Convection Schemes ◽  
The Individual ◽  
The Impact

We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback is discussed.

scholarly journals Does Antarctic glaciation cool the world?

2012 ◽  
Vol 8 (4) ◽  
pp. 2645-2693 ◽  
Author(s):  
A. Goldner ◽  
M. Huber ◽  
R. Caballero
Keyword(s):  
Surface Temperature ◽  
Radiative Forcing ◽  
Climate Models ◽  
Ice Sheet ◽  
Cloud Feedback ◽  
Modern World ◽  
Antarctic Ice Sheet ◽  
Cloud Feedbacks ◽  
Wide Range ◽  
The Antarctic

Abstract. In this study we compare the simulated climatic impact of adding the Antarctic Ice Sheet to the "Greenhouse World" of the Eocene and removing the Antarctic Ice Sheet from the Modern world. The Modern surface temperature anomaly (ΔT) induced by Antarctic Glaciation ranges from −1.22 to −0.18 K when CO2 is dropped from 2240 to 560 ppm, whereas the Eocene ΔT is nearly constant at −0.3 K. We calculate the climate sensitivity parameter S[Antarctica] which is defined as the change in surface temperature (ΔT) divided by the change in radiative forcing (ΔQAntarctica) imposed by prescribing the glacial properties of Antarctica. While the ΔT associated with the imposed Antarctic properties is relatively consistent across the Eocene cases, the radiative forcing is not. This leads to a wide range of S[Antarctica], with Eocene values systematically smaller than Modern. This differing temperature response in Eocene and Modern is partially due to the smaller surface area of the imposed forcing over Antarctica in the Eocene and partially due to the presence of strong positive sea-ice feedbacks in the Modern. The system's response is further mediated by differing shortwave cloud feedbacks which are large and of opposite sign operating in Modern and Eocene configurations. A negative cloud feedback warms much of the Earth's surface as a large ice sheet is introduced in Antarctica in the Eocene, whereas in the Modern this cloud feedback is positive and acts to enhance cooling introduced by adding an ice sheet. Because of the importance of cloud feedbacks in determining the final temperature sensitivity of the Antarctic Ice Sheet our results are likely to be model dependent. Nevertheless, these model results show that the radiative forcing and feedbacks induced by the Antarctic Ice Sheet did not significantly decrease global mean surface temperature across the Eocene-Oligocene transition (EOT) and that other factors like declining atmospheric CO2 are more important for cooling across the EOT. The results indicate that climate transitions associated with glaciation depend on the climate background state. This means that using paleoclimate proxy data by itself, from the EOT to estimate Earth System Sensitivity, into the future, is made difficult without relying on climate models and consequently these modelling estimates will have large uncertainty, largely due to low clouds.

scholarly journals Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels

2012 ◽  
Vol 25 (11) ◽  
pp. 3715-3735 ◽  
Author(s):  
Mark D. Zelinka ◽  
Stephen A. Klein ◽  
Dennis L. Hartmann
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Grid Point ◽  
Cloud Fraction ◽  
Cloud Feedback ◽  
Global Climate Models ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Cloud Feedbacks ◽  
Low Clouds

This study proposes a novel technique for computing cloud feedbacks using histograms of cloud fraction as a joint function of cloud-top pressure (CTP) and optical depth (τ). These histograms were generated by the International Satellite Cloud Climatology Project (ISCCP) simulator that was incorporated into doubled-CO2 simulations from 11 global climate models in the Cloud Feedback Model Intercomparison Project. The authors use a radiative transfer model to compute top of atmosphere flux sensitivities to cloud fraction perturbations in each bin of the histogram for each month and latitude. Multiplying these cloud radiative kernels with histograms of modeled cloud fraction changes at each grid point per unit of global warming produces an estimate of cloud feedback. Spatial structures and globally integrated cloud feedbacks computed in this manner agree remarkably well with the adjusted change in cloud radiative forcing. The global and annual mean model-simulated cloud feedback is dominated by contributions from medium thickness (3.6 < τ ≤ 23) cloud changes, but thick (τ > 23) cloud changes cause the rapid transition of cloud feedback values from positive in midlatitudes to negative poleward of 50°S and 70°N. High (CTP ≤ 440 hPa) cloud changes are the dominant contributor to longwave (LW) cloud feedback, but because their LW and shortwave (SW) impacts are in opposition, they contribute less to the net cloud feedback than do the positive contributions from low (CTP > 680 hPa) cloud changes. Midlevel (440 < CTP ≤ 680 hPa) cloud changes cause positive SW cloud feedbacks that are 80% as large as those due to low clouds. Finally, high cloud changes induce wider ranges of LW and SW cloud feedbacks across models than do low clouds.

scholarly journals Insights into low-latitude cloud feedbacks from high-resolution models

2015 ◽  
Vol 373 (2054) ◽  
pp. 20140415 ◽  
Author(s):  
Christopher S. Bretherton
Keyword(s):  
Boundary Layer ◽  
Climate Models ◽  
Global Climate ◽  
Cloud Feedback ◽  
Global Climate Models ◽  
Limited Area ◽  
Slight Reduction ◽  
Low Latitude ◽  
Cloud Feedbacks ◽  
Cloud Regimes

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: ‘thermodynamic’ cloudiness reduction from warming of the atmosphere–ocean column, ‘radiative’ cloudiness reduction from CO 2 - and H 2 O-induced increase in atmospheric emissivity aloft, ‘stability-induced’ cloud increase from increased lower tropospheric stratification, and ‘dynamical’ cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes.

scholarly journals The Cloud Feedback Model Intercomparison Project (CFMIP) Diagnostic Codes Catalogue – metrics, diagnostics and methodologies to evaluate, understand and improve the representation of clouds and cloud feedbacks in climate models

2017 ◽  
Vol 10 (11) ◽  
pp. 4285-4305 ◽  
Author(s):  
Yoko Tsushima ◽  
Florent Brient ◽  
Stephen A. Klein ◽  
Dimitra Konsta ◽  
Christine C. Nam ◽  
...  
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Evaluation Studies ◽  
Circulation Model ◽  
Community Analysis ◽  
Model Intercomparison ◽  
Cloud Feedbacks ◽  
Diagnostic Codes ◽  
Feedback Model ◽  
Intercomparison Project

Abstract. The CFMIP Diagnostic Codes Catalogue assembles cloud metrics, diagnostics and methodologies, together with programs to diagnose them from general circulation model (GCM) outputs written by various members of the CFMIP community. This aims to facilitate use of the diagnostics by the wider community studying climate and climate change. This paper describes the diagnostics and metrics which are currently in the catalogue, together with examples of their application to model evaluation studies and a summary of some of the insights these diagnostics have provided into the main shortcomings in current GCMs. Analysis of outputs from CFMIP and CMIP6 experiments will also be facilitated by the sharing of diagnostic codes via this catalogue.Any code which implements diagnostics relevant to analysing clouds – including cloud–circulation interactions and the contribution of clouds to estimates of climate sensitivity in models – and which is documented in peer-reviewed studies, can be included in the catalogue. We very much welcome additional contributions to further support community analysis of CMIP6 outputs.

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