scholarly journals Quantifying the Sources of Intermodel Spread in Equilibrium Climate Sensitivity

2016 ◽  
Vol 29 (2) ◽  
pp. 513-524 ◽  
Author(s):  
Peter M. Caldwell ◽  
Mark D. Zelinka ◽  
Karl E. Taylor ◽  
Kate Marvel
Keyword(s):  
Climate Sensitivity ◽  
Temperature Response ◽  
Cloud Feedback ◽  
Lapse Rate ◽  
Specific Humidity ◽  
New Approach ◽  
Cloud Feedbacks ◽  
Equilibrium Climate Sensitivity ◽  
Dominant Source ◽  
Average Temperature

Abstract This study clarifies the causes of intermodel differences in the global-average temperature response to doubled CO2, commonly known as equilibrium climate sensitivity (ECS). The authors begin by noting several issues with the standard approach for decomposing ECS into a sum of forcing and feedback terms. This leads to a derivation of an alternative method based on linearizing the effect of the net feedback. Consistent with previous studies, the new method identifies shortwave cloud feedback as the dominant source of intermodel spread in ECS. This new approach also reveals that covariances between cloud feedback and forcing, between lapse rate and longwave cloud feedbacks, and between albedo and shortwave cloud feedbacks play an important and previously underappreciated role in determining model differences in ECS. Defining feedbacks based on fixed relative rather than specific humidity (as suggested by Held and Shell) reduces the covariances between processes and leads to more straightforward interpretations of results.

scholarly journals The Strength of Low-Cloud Feedbacks and Tropical Climate: A CESM Sensitivity Study

2019 ◽  
Vol 32 (9) ◽  
pp. 2497-2516 ◽  
Author(s):  
Ehsan Erfani ◽  
Natalie J. Burls
Keyword(s):  
Climate Sensitivity ◽  
Cloud Cover ◽  
Hydrological Cycle ◽  
Tropical Climate ◽  
Cloud Feedback ◽  
Cloud Feedbacks ◽  
Feedback Strength ◽  
Low Cloud ◽  
Low Cloud Cover ◽  
The Impact

Abstract Variability in the strength of low-cloud feedbacks across climate models is the primary contributor to the spread in their estimates of equilibrium climate sensitivity (ECS). This raises the question: What are the regional implications for key features of tropical climate of globally weak versus strong low-cloud feedbacks in response to greenhouse gas–induced warming? To address this question and formalize our understanding of cloud controls on tropical climate, we perform a suite of idealized fully coupled and slab-ocean climate simulations across which we systematically scale the strength of the low-cloud-cover feedback under abrupt 2 × CO2 forcing within a single model, thereby isolating the impact of low-cloud feedback strength. The feedback strength is varied by modifying the stratus cloud fraction so that it is a function of not only local conditions but also global temperature in a series of abrupt 2 × CO2 sensitivity experiments. The unperturbed decrease in low cloud cover (LCC) under 2 × CO2 is greatest in the mid- and high-latitude oceans, and the subtropical eastern Pacific and Atlantic, a pattern that is magnified as the feedback strength is scaled. Consequently, sea surface temperature (SST) increases more in these regions as well as the Pacific cold tongue. As the strength of the low-cloud feedback increases this results in not only increased ECS, but also an enhanced reduction of the large-scale zonal and meridional SST gradients (structural climate sensitivity), with implications for the atmospheric Hadley and Walker circulations, as well as the hydrological cycle. The relevance of our results to simulating past warm climate is also discussed.

Spatial Decomposition of Climate Feedbacks in the Community Earth System Model

2013 ◽  
Vol 26 (11) ◽  
pp. 3544-3561 ◽  
Author(s):  
A. Gettelman ◽  
J. E. Kay ◽  
J. T. Fasullo
Keyword(s):  
Climate Sensitivity ◽  
Earth System Model ◽  
Cloud Feedback ◽  
System Model ◽  
Storm Tracks ◽  
Cloud Base ◽  
Earth System ◽  
Cloud Feedbacks ◽  
Stratiform Clouds ◽  
Community Earth System Model

Abstract An ensemble of simulations from different versions of the Community Atmosphere Model in the Community Earth System Model (CESM) is used to investigate the processes responsible for the intermodel spread in climate sensitivity. In the CESM simulations, the climate sensitivity spread is primarily explained by shortwave cloud feedbacks on the equatorward flank of the midlatitude storm tracks. Shortwave cloud feedbacks have been found to explain climate sensitivity spread in previous studies, but the location of feedback differences was in the subtropics rather than in the storm tracks as identified in CESM. The cloud-feedback relationships are slightly stronger in the winter hemisphere. The spread in climate sensitivity in this study is related both to the cloud-base state and to the cloud feedbacks. Simulated climate sensitivity is correlated with cloud-fraction changes on the equatorward side of the storm tracks, cloud condensate in the storm tracks, and cloud microphysical state on the poleward side of the storm tracks. Changes in the extent and water content of stratiform clouds (that make up cloud feedback) are regulated by the base-state vertical velocity, humidity, and deep convective mass fluxes. Within the storm tracks, the cloud-base state affects the cloud response to CO2-induced temperature changes and alters the cloud feedbacks, contributing to climate sensitivity spread within the CESM ensemble.

scholarly journals On the Emergent Constraints of Climate Sensitivity

2018 ◽  
Vol 31 (2) ◽  
pp. 863-875 ◽  
Author(s):  
Xin Qu ◽  
Alex Hall ◽  
Anthony M. DeAngelis ◽  
Mark D. Zelinka ◽  
Stephen A. Klein ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Climate Models ◽  
Selection Process ◽  
Temperature Response ◽  
Cloud Feedback ◽  
Emergent Constraints ◽  
Low Cloud ◽  
Model Ensembles ◽  
Statistical Connection ◽  
Emergent Constraint

Differences among climate models in equilibrium climate sensitivity (ECS; the equilibrium surface temperature response to a doubling of atmospheric CO2) remain a significant barrier to the accurate assessment of societally important impacts of climate change. Relationships between ECS and observable metrics of the current climate in model ensembles, so-called emergent constraints, have been used to constrain ECS. Here a statistical method (including a backward selection process) is employed to achieve a better statistical understanding of the connections between four recently proposed emergent constraint metrics and individual feedbacks influencing ECS. The relationship between each metric and ECS is largely attributable to a statistical connection with shortwave low cloud feedback, the leading cause of intermodel ECS spread. This result bolsters confidence in some of the metrics, which had assumed such a connection in the first place. Additional analysis is conducted with a few thousand artificial metrics that are randomly generated but are well correlated with ECS. The relationships between the contrived metrics and ECS can also be linked statistically to shortwave cloud feedback. Thus, any proposed or forthcoming ECS constraint based on the current generation of climate models should be viewed as a potential constraint on shortwave cloud feedback, and physical links with that feedback should be investigated to verify that the constraint is real. In addition, any proposed ECS constraint should not be taken at face value since other factors influencing ECS besides shortwave cloud feedback could be systematically biased in the models.

scholarly journals Equilibrium Climate Sensitivity: Is It Accurate to Use a Slab Ocean Model?

2009 ◽  
Vol 22 (9) ◽  
pp. 2494-2499 ◽  
Author(s):  
Gokhan Danabasoglu ◽  
Peter R. Gent
Keyword(s):  
Carbon Dioxide ◽  
Climate Sensitivity ◽  
Climate Model ◽  
Temperature Response ◽  
Accurate Estimate ◽  
Ocean Model ◽  
Climate System Model ◽  
Equilibrium Climate Sensitivity ◽  
Model Version ◽  
Slab Ocean

Abstract The equilibrium climate sensitivity of a climate model is usually defined as the globally averaged equilibrium surface temperature response to a doubling of carbon dioxide. This is virtually always estimated in a version with a slab model for the upper ocean. The question is whether this estimate is accurate for the full climate model version, which includes a full-depth ocean component. This question has been answered for the low-resolution version of the Community Climate System Model, version 3 (CCSM3). The answer is that the equilibrium climate sensitivity using the full-depth ocean model is 0.14°C higher than that using the slab ocean model, which is a small increase. In addition, these sensitivity estimates have a standard deviation of nearly 0.1°C because of interannual variability. These results indicate that the standard practice of using a slab ocean model does give a good estimate of the equilibrium climate sensitivity of the full CCSM3. Another question addressed is whether the effective climate sensitivity is an accurate estimate of the equilibrium climate sensitivity. Again the answer is yes, provided that at least 150 yr of data from the doubled carbon dioxide run are used.

scholarly journals Climate Feedbacks in CCSM3 under Changing CO2 Forcing. Part II: Variation of Climate Feedbacks and Sensitivity with Forcing

2013 ◽  
Vol 26 (9) ◽  
pp. 2784-2795 ◽  
Author(s):  
Alexandra K. Jonko ◽  
Karen M. Shell ◽  
Benjamin M. Sanderson ◽  
Gokhan Danabasoglu
Keyword(s):  
Water Vapor ◽  
Temperature Change ◽  
Climate Sensitivity ◽  
General Circulation ◽  
Coupled Model ◽  
Lapse Rate ◽  
Climate Feedbacks ◽  
Cloud Feedbacks ◽  
Response To Temperature ◽  
Fully Coupled

Abstract Are equilibrium climate sensitivity and the associated radiative feedbacks a constant property of the climate system, or do they change with forcing magnitude and base climate? Using the radiative kernel technique, feedbacks and climate sensitivity are evaluated in a fully coupled general circulation model (GCM) for three successive doublings of carbon dioxide starting from present-day concentrations. Climate sensitivity increases by 23% between the first and third CO2 doublings. Increases in the positive water vapor and cloud feedbacks are partially balanced by a decrease in the positive surface albedo feedback and an increase in the negative lapse rate feedback. Feedbacks can be decomposed into a radiative flux change and a climate variable response to temperature change. The changes in water vapor and Planck feedbacks are due largely to changes in the radiative response with climate state. Higher concentrations of greenhouse gases and higher temperatures lead to more absorption and emission of longwave radiation. Changes in cloud feedbacks are dominated by the climate response to temperature change, while the lapse rate and albedo feedbacks combine elements of both. Simulations with a slab ocean model (SOM) version of the GCM are used to verify whether an SOM-GCM accurately reproduces the behavior of the fully coupled model. Although feedbacks differ in magnitude between model configurations (with differences as large as those between CO2 doublings for some feedbacks), changes in feedbacks between CO2 doublings are consistent in sign and magnitude in the SOM-GCM and the fully coupled model.

scholarly journals Evaluating Emergent Constraints on Equilibrium Climate Sensitivity

2018 ◽  
Vol 31 (10) ◽  
pp. 3921-3942 ◽  
Author(s):  
Peter M. Caldwell ◽  
Mark D. Zelinka ◽  
Stephen A. Klein
Keyword(s):  
Surface Temperature ◽  
Climate Sensitivity ◽  
Temperature Response ◽  
Complex Nature ◽  
Physical Processes ◽  
Physical Explanation ◽  
Equilibrium Climate Sensitivity ◽  
Geographical Regions ◽  
Emergent Constraints ◽  
Emergent Constraint

Emergent constraints are quantities that are observable from current measurements and have skill predicting future climate. This study explores 19 previously proposed emergent constraints related to equilibrium climate sensitivity (ECS; the global-average equilibrium surface temperature response to CO2 doubling). Several constraints are shown to be closely related, emphasizing the importance for careful understanding of proposed constraints. A new method is presented for decomposing correlation between an emergent constraint and ECS into terms related to physical processes and geographical regions. Using this decomposition, one can determine whether the processes and regions explaining correlation with ECS correspond to the physical explanation offered for the constraint. Shortwave cloud feedback is generally found to be the dominant contributor to correlations with ECS because it is the largest source of intermodel spread in ECS. In all cases, correlation results from interaction between a variety of terms, reflecting the complex nature of ECS and the fact that feedback terms and forcing are themselves correlated with each other. For 4 of the 19 constraints, the originally proposed explanation for correlation is borne out by our analysis. These four constraints all predict relatively high climate sensitivity. The credibility of six other constraints is called into question owing to correlation with ECS coming mainly from unexpected sources and/or lack of robustness to changes in ensembles. Another six constraints lack a testable explanation and hence cannot be confirmed. The fact that this study casts doubt upon more constraints than it confirms highlights the need for caution when identifying emergent constraints from small ensembles.

The Evolution of Climate Sensitivity and Climate Feedbacks in the Community Atmosphere Model

2012 ◽  
Vol 25 (5) ◽  
pp. 1453-1469 ◽  
Author(s):  
A. Gettelman ◽  
J. E. Kay ◽  
K. M. Shell
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Ocean Model ◽  
Lapse Rate ◽  
Shallow Convection ◽  
Climate Feedbacks ◽  
Cloud Feedbacks ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
The Difference

The major evolution of the National Center for Atmospheric Research Community Atmosphere Model (CAM) is used to diagnose climate feedbacks, understand how climate feedbacks change with different physical parameterizations, and identify the processes and regions that determine climate sensitivity. In the evolution of CAM from version 4 to version 5, the water vapor, temperature, surface albedo, and lapse rate feedbacks are remarkably stable across changes to the physical parameterization suite. However, the climate sensitivity increases from 3.2 K in CAM4 to 4.0 K in CAM5. The difference is mostly due to (i) more positive cloud feedbacks and (ii) higher CO2 radiative forcing in CAM5. The intermodel differences in cloud feedbacks are largest in the tropical trade cumulus regime and in the midlatitude storm tracks. The subtropical stratocumulus regions do not contribute strongly to climate feedbacks owing to their small area coverage. A “modified Cess” configuration for atmosphere-only model experiments is shown to reproduce slab ocean model results. Several parameterizations contribute to changes in tropical cloud feedbacks between CAM4 and CAM5, but the new shallow convection scheme causes the largest midlatitude feedback differences and the largest change in climate sensitivity. Simulations with greater cloud forcing in the mean state have lower climate sensitivity. This work provides a methodology for further analysis of climate sensitivity across models and a framework for targeted comparisons with observations that can help constrain climate sensitivity to radiative forcing.

scholarly journals Equilibrium climate sensitivity above 5 °C plausible due to state-dependent cloud feedback

2020 ◽  
Vol 13 (11) ◽  
pp. 718-721
Author(s):  
Jenny Bjordal ◽  
Trude Storelvmo ◽  
Kari Alterskjær ◽  
Tim Carlsen
Keyword(s):  
Climate Sensitivity ◽  
Cloud Feedback ◽  
Equilibrium Climate Sensitivity ◽  
State Dependent

scholarly journals Cloud Feedbacks from CanESM2 to CanESM5.0 and their influence on climate sensitivity

2021 ◽  
Vol 14 (9) ◽  
pp. 5355-5372
Author(s):  
John G. Virgin ◽  
Christopher G. Fletcher ◽  
Jason N. S. Cole ◽  
Knut von Salzen ◽  
Toni Mitovski
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Surface Albedo ◽  
Coupled Model ◽  
Cloud Feedback ◽  
Surface Temperature Change ◽  
Cloud Optical Depth ◽  
Cloud Feedbacks ◽  
Low Cloud ◽  
Underlying Causes

Abstract. The newest iteration of the Canadian Earth System Model (CanESM5.0.3) has an effective climate sensitivity (EffCS) of 5.65 K, which is a 54 % increase relative to the model's previous version (CanESM2 – 3.67 K), and the highest sensitivity of all current models participating in the sixth phase of the coupled model inter-comparison project (CMIP6). Here, we explore the underlying causes behind CanESM5's increased EffCS via comparison of forcing and feedbacks between CanESM2 and CanESM5. We find only modest differences in radiative forcing as a response to CO2 between model versions. We find small increases in the surface albedo and longwave cloud feedback, as well as a substantial increase in the SW cloud feedback in CanESM5. Through the use of cloud area fraction output and cloud radiative kernels, we find that more positive low and non-low shortwave cloud feedbacks – particularly with regards to low clouds across the equatorial Pacific, as well as subtropical and extratropical free troposphere cloud optical depth – are the dominant contributors to CanESM5's increased climate sensitivity. Additional simulations with prescribed sea surface temperatures reveal that the spatial pattern of surface temperature change exerts controls on the magnitude and spatial distribution of low-cloud fraction response but does not fully explain the increased EffCS in CanESM5. The results from CanESM5 are consistent with increased EffCS in several other CMIP6 models, which has been primarily attributed to changes in shortwave cloud feedbacks.

Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity

2021 ◽  
Author(s):  
Timothy A. Myers ◽  
Ryan C. Scott ◽  
Mark D. Zelinka ◽  
Stephen A. Klein ◽  
Joel R. Norris ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Cloud Feedback ◽  
Observational Constraints ◽  
Low Cloud
Sign in / Sign up

Export Citation Format

Share Document