scholarly journals On the Increase of Climate Sensitivity and Cloud Feedback With Warming in the Community Atmosphere Models

2020 ◽  
Vol 47 (18) ◽  
Author(s):  
Jiang Zhu ◽  
Christopher J. Poulsen
Keyword(s):  
Climate Sensitivity ◽  
Cloud Feedback

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

scholarly journals Observations of Local Positive Low Cloud Feedback Patterns and Their Role in Internal Variability and Climate Sensitivity

2018 ◽  
Vol 45 (9) ◽  
pp. 4438-4445 ◽  
Author(s):  
Tianle Yuan ◽  
Lazaros Oreopoulos ◽  
Steven E. Platnick ◽  
Kerry Meyer
Keyword(s):  
Climate Sensitivity ◽  
Internal Variability ◽  
Cloud Feedback ◽  
Low Cloud

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 The importance of mixed-phase and ice clouds for climate sensitivity in the global aerosol–climate model ECHAM6-HAM2

2018 ◽  
Vol 18 (12) ◽  
pp. 8807-8828 ◽  
Author(s):  
Ulrike Lohmann ◽  
David Neubauer
Keyword(s):  
Climate Sensitivity ◽  
Liquid Water ◽  
Climate Model ◽  
Supercooled Liquid ◽  
Cloud Feedback ◽  
Mixed Phase ◽  
Shortwave Radiation ◽  
Ice Clouds ◽  
Cloud Optical Depth ◽  
Mixed Phase Clouds

Abstract. How clouds change in a warmer climate remains one of the largest uncertainties for the equilibrium climate sensitivity (ECS). While a large spread in the cloud feedback arises from low-level clouds, it was recently shown that mixed-phase clouds are also important for ECS. If mixed-phase clouds in the current climate contain too few supercooled cloud droplets, too much ice will change to liquid water in a warmer climate. As shown by Tan et al. (2016), this overestimates the negative cloud-phase feedback and underestimates ECS in the CAM global climate model (GCM). Here we use the newest version of the ECHAM6-HAM2 GCM to investigate the importance of mixed-phase and ice clouds for ECS. Although we also considerably underestimate the fraction of supercooled liquid water globally in the reference version of the ECHAM6-HAM2 GCM, we do not obtain increases in ECS in simulations with more supercooled liquid water in the present-day climate, different from the findings by Tan et al. (2016). We hypothesize that it is not the global supercooled liquid water fraction that matters, but only how well low- and mid-level mixed-phase clouds with cloud-top temperatures in the mixed-phase temperature range between 0 and −35 ∘C that are not shielded by higher-lying ice clouds are simulated. These occur most frequently in midlatitudes, in particular over the Southern Ocean where they determine the amount of absorbed shortwave radiation. In ECHAM6-HAM2 the amount of absorbed shortwave radiation over the Southern Ocean is only significantly overestimated if all clouds below 0 ∘C consist exclusively of ice. Only in this simulation is ECS significantly smaller than in all other simulations and the cloud optical depth feedback is the dominant cloud feedback. In all other simulations, the cloud optical depth feedback is weak and changes in cloud feedbacks associated with cloud amount and cloud-top pressure dominate the overall cloud feedback. However, apart from the simulation with only ice below 0 ∘C, differences in the overall cloud feedback are not translated into differences in ECS in our model. This insensitivity to the cloud feedback in our model is explained with compensating effects in the clear sky.

Climate Sensitivity of a One-Dimensional Radiative-Convective Model with Cloud Feedback

1981 ◽  
Vol 38 (6) ◽  
pp. 1167-1178 ◽  
Author(s):  
Wei-Chyung Wang ◽  
William B. Rossow ◽  
Mao-Sung Yao ◽  
Marilyn Wolfson
Keyword(s):  
Climate Sensitivity ◽  
Cloud Feedback ◽  
One Dimensional ◽  
Convective Model

A Test of Emergent Constraints on Cloud Feedback and Climate Sensitivity Using a Calibrated Single-Model Ensemble

2018 ◽  
Vol 31 (18) ◽  
pp. 7515-7532 ◽  
Author(s):  
Benjamin M. Wagman ◽  
Charles S. Jackson
Keyword(s):  
Relative Humidity ◽  
Climate Sensitivity ◽  
Threshold Value ◽  
Cloud Feedback ◽  
Hadley Cell ◽  
Model Ensemble ◽  
Single Model ◽  
Community Atmosphere Model ◽  
Emergent Constraints ◽  
Out Of Sample

A calibrated single-model ensemble (SME) derived from the NCAR Community Atmosphere Model, version 3.1, is used to test two hypothesized emergent constraints on cloud feedback and equilibrium climate sensitivity (ECS). The Fasullo and Trenberth relative humidity (RH) metric and the Sherwood et al. lower-tropospheric mixing (LTMI) metric are computed for the present-day climate of the SME, and the relationships between the metrics, ECS, and cloud and other climate feedbacks are examined. The tropical convergence zone relative humidity (RH M) and the parameterized lower-tropospheric mixing (LTMI S) are positively correlated to ECS, and each is associated with a different spatial pattern of tropical shortwave cloud feedback in the SME. However, neither of those metrics is linked to the type of cloud response hypothesized by its authors. The resolved lower-tropospheric mixing (LTMI D) is positively correlated to ECS for a subset of the SME having LTMI D over a threshold value. LTMI and the RH for the dry, descending branch of the Hadley cell (RH D) narrow and shift upward the posterior estimates of ECS in the SME, but the SME bias in RH D and concerns over poorly understood physical mechanisms suggest the narrowing could be spurious for both constraints. While calibrated SME results may not generalize to multimodel ensembles, they can enhance the process understanding of emergent constraints and serve as out-of-sample tests of robustness.

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