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 Potential Problems Measuring Climate Sensitivity from the Historical Record

2020 ◽  
Vol 33 (6) ◽  
pp. 2237-2248 ◽  
Author(s):  
Andrew E. Dessler
Keyword(s):  
Climate Sensitivity ◽  
Internal Variability ◽  
Historical Record ◽  
Cloud Feedback ◽  
Historical Period ◽  
Pattern Effect ◽  
Surface Warming ◽  
Two Factors ◽  
Low Cloud ◽  
The Impact

AbstractThis study investigates potential biases between equilibrium climate sensitivity inferred from warming over the historical period (ECShist) and the climate system’s true ECS (ECStrue). This paper focuses on two factors that could contribute to differences between these quantities. First is the impact of internal variability over the historical period: our historical climate record is just one of an infinity of possible trajectories, and these different trajectories can generate ECShist values 0.3 K below to 0.5 K above (5%–95% confidence interval) the average ECShist. Because this spread is due to unforced variability, I refer to this as the unforced pattern effect. This unforced pattern effect in the model analyzed here is traced to unforced variability in loss of sea ice, which affects the albedo feedback, and to unforced variability in warming of the troposphere, which affects the shortwave cloud feedback. There is also a forced pattern effect that causes ECShist to depart from ECStrue due to differences between today’s transient pattern of warming and the pattern of warming at 2×CO2 equilibrium. Changes in the pattern of warming lead to a strengthening low-cloud feedback as equilibrium is approached in regions where surface warming is delayed: the Southern Ocean, eastern Pacific, and North Atlantic near Greenland. This forced pattern effect causes ECShist to be on average 0.2 K lower than ECStrue (~8%). The net effect of these two pattern effects together can produce an estimate of ECShist as much as 0.5 K below ECStrue.

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 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.

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 Recent progress toward reducing the uncertainty in tropical low cloud feedback and climate sensitivity: a review

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Youichi Kamae ◽  
Tomoo Ogura ◽  
Hideo Shiogama ◽  
Masahiro Watanabe
Keyword(s):  
Climate Sensitivity ◽  
Recent Progress ◽  
Cloud Feedback ◽  
Low Cloud

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.

Mechanisms of Low Cloud–Climate Feedback in Idealized Single-Column Simulations with the Community Atmospheric Model, Version 3 (CAM3)

2008 ◽  
Vol 21 (18) ◽  
pp. 4859-4878 ◽  
Author(s):  
Minghua Zhang ◽  
Christopher Bretherton
Keyword(s):  
Dynamic Effect ◽  
Atmospheric Model ◽  
Cloud Feedback ◽  
Climate Feedback ◽  
Stratus Clouds ◽  
Model Version ◽  
Boundary Layer Turbulence ◽  
Thermodynamic Effect ◽  
Single Column ◽  
Low Cloud

Abstract This study investigates the physical mechanism of low cloud feedback in the Community Atmospheric Model, version 3 (CAM3) through idealized single-column model (SCM) experiments over the subtropical eastern oceans. Negative cloud feedback is simulated from stratus and stratocumulus that is consistent with previous diagnostics of cloud feedbacks in CAM3 and its predecessor versions. The feedback occurs through the interaction of a suite of parameterized processes rather than from any single process. It is caused by the larger amount of in-cloud liquid water in stratus clouds from convective sources, and longer lifetimes of these clouds in a warmer climate through their interaction with boundary layer turbulence. Thermodynamic effects are found to dominate the negative cloud feedback in the model. The dynamic effect of weaker subsidence in a warmer climate also contributes to the negative cloud feedback, but with about one-quarter of the magnitude of the thermodynamic effect, owing to increased low-level convection in a warmer climate.

scholarly journals Low‐Cloud Feedback in CAM5‐CLUBB: Physical Mechanisms and Parameter Sensitivity Analysis

2018 ◽  
Vol 10 (11) ◽  
pp. 2844-2864 ◽  
Author(s):  
Haipeng Zhang ◽  
Minghuai Wang ◽  
Zhun Guo ◽  
Chen Zhou ◽  
Tianjun Zhou ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Parameter Sensitivity ◽  
Cloud Feedback ◽  
Parameter Sensitivity Analysis ◽  
Physical Mechanisms ◽  
Low Cloud

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.

Sign in / Sign up

Export Citation Format

Share Document