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Satellite measurements show that the Northern and Southern hemispheres reflect equal amounts of shortwave radiation (“albedo symmetry”), but no theory exists on if, how, and why the symmetry is established and maintained. Ambiguously, climate models are strongly biased in albedo symmetry but agree in the sign of the response to CO2. We find that mean‐state biases in albedo symmetry and hemispheric surface temperature asymmetry correlate negatively. Similarly, the response of albedo asymmetry to CO2forcing correlates negatively with the magnitude of the asymmetry in surface warming. This is true across many and within single climate model simulations: a too warm or stronger warming hemisphere is darker or darkens more than its counterpart. In the 21 years of observations we find the same tendency and hypothesize (a) albedo symmetry is a function of the current climate state and (b) we will observe an evolution toward albedo asymmetry in coming decades. 

In the equatorial and subtropical east Pacific Ocean, strong ocean‐atmosphere coupling results in large‐amplitude interannual variability. Recent literature debates whether climate models reproduce observed short and long‐term surface temperature trends in this region. We reconcile the debate by reevaluating a large range of trends in initial condition ensembles of 15 climate models. We confirm that models fail to reproduce long‐term trends, but also find that many models do not reproduce the observed decadal‐scale swings in the East to West gradient of the equatorial Pacific. Models with high climate sensitivity are less likely to reproduce observed decadal‐scale swings than models with a modest climate sensitivity, possibly due to an incorrect balance of cloud feedbacks driven by changing inversion strength versus surface warming. Our findings suggest that two not well understood problems of the current generation of climate models are connected and we highlight the need to increase understanding of decadal‐scale variability.

 

The atmospheric Green's function method is a technique for modeling the response of the atmosphere to changes in the spatial field of surface temperature. While early studies applied this method to changes in atmospheric circulation, it has also become an important tool to understand changes in radiative feedbacks due to evolving patterns of warming, a phenomenon called the “pattern effect.” To better study this method, this paper presents a protocol for creating atmospheric Green's functions to serve as the basis for a model intercomparison project, GFMIP. The protocol has been developed using a series of sensitivity tests performed with the HadAM3 atmosphere‐only general circulation model, along with existing and new simulations from other models. Our preliminary results have uncovered nonlinearities in the response of the atmosphere to surface temperature changes, including an asymmetrical response to warming versus cooling patch perturbations, and a change in the dependence of the response on the magnitude and size of the patches. These nonlinearities suggest that the pattern effect may depend on the heterogeneity of warming as well as its location. These experiments have also revealed tradeoffs in experimental design between patch size, perturbation strength, and the length of control and patch simulations. The protocol chosen on the basis of these experiments balances scientific utility with the simulation time and setup required by the Green's function approach. Running these simulations will further our understanding of many aspects of atmospheric response, from the pattern effect and radiative feedbacks to changes in circulation, cloudiness, and precipitation.

 

Effective climate sensitivity (EffCS), commonly estimated from model simulations with abrupt 4×CO₂for 150 years, has been shown to depend on the CO₂forcing level. To understand this dependency systematically, we performed a series of simulations with a range of abrupt CO₂forcing in two climate models. Our results indicate that normalized EffCS values in these simulations are a non‐monotonic function of the CO₂forcing, decreasing between 3× and 4×CO₂in CESM1‐LE (2× and 3×CO₂in GISS‐E2.1‐G) and increasing at higher CO₂levels. The minimum EffCS value, caused by anomalously negative radiative feedbacks, arises mainly from sea‐surface temperature (SST) relative cooling in the tropical and subtropical North Atlantic. This cooling is associated with the formation of the North Atlantic Warming Hole and Atlantic Meridional Overturning Circulation collapse under CO₂forcing. Our findings imply that understanding changes in North Atlantic SST patterns is important for constraining near‐future and equilibrium global warming.

 

The realization that atmospheric radiative feedbacks depend on the underlying patterns of surface warming and global temperature, and thus, change over time has lead to a proliferation of feedback definitions and methods to estimate equilibrium climate sensitivity (ECS). We contrast three flavors of radiative feedbacks – equilibrium, effective, and differential feedback – and discuss their physical interpretations and applications. We show that their values at any given time can differ more than 1 and their implied equilibrium or effective climate sensitivity can differ several degrees. With ten (quasi) equilibrated climate models, we show that 400 years might be enough to estimate the true ECS within a 5% error using a simple regression method utilizing the differential feedback parameter. We argue that a community‐wide agreement on the interpretation of the different feedback definitions would advance the quest to narrow the estimate of climate sensitivity.

 

Earth system modeling of climate geoengineering proposals suggests that the physical outcomes of such interventions will depend on the particulars of the implementation. Here, we present a first attempt to “geoengineer” a well‐known teleconnection between sea surface temperatures (SSTs) and Sahelian precipitation. Using idealized earth system model simulations, we show that selectively cooling the Indian Ocean efficiently increases precipitation in the Sahel region, widening the seasonally migrating rainband over Africa. Applying the SST perturbations derived from the idealized experiments to observationally constrained historical ones, we find that our intervention can reverse conditions as extreme as the mid‐20th century Sahelian drought, albeit less efficiently than in the idealized simulations. Side effects include changes in the seasonal distribution of Sahelian precipitation and substantial precipitation reductions in sub‐Saharan East Africa. This work represents a proof‐of‐concept illustration of effects that might be expected with a tailored, regional approach to climate intervention.

 

The sensitivity of the climate to CO₂forcing depends on spatially varying radiative feedbacks that act both locally and nonlocally. We assess whether a method employing multiple regression can be used to estimate local and nonlocal radiative feedbacks from internal variability. We test this method on millennial-length simulations performed with six coupled atmosphere–ocean general circulation models (AOGCMs). Given the spatial pattern of warming, the method does quite well at recreating the top-of-atmosphere flux response for most regions of Earth, except over the Southern Ocean where it consistently overestimates the change, leading to an overestimate of the sensitivity. For five of the six models, the method finds that local feedbacks are positive due to cloud processes, balanced by negative nonlocal shortwave cloud feedbacks associated with regions of tropical convection. For four of these models, the magnitudes of both are comparable to the Planck feedback, so that changes in the ratio between them could lead to large changes in climate sensitivity. The positive local feedback explains why observational studies that estimate spatial feedbacks using only local regressions predict an unstable climate. The method implies that sensitivity in these AOGCMs increases over time due to a reduction in the share of warming occurring in tropical convecting regions and the resulting weakening of associated shortwave cloud and longwave clear-sky feedbacks. Our results provide a step toward an observational estimate of time-varying climate sensitivity by demonstrating that many aspects of spatial feedbacks appear to be the same between internal variability and the forced response.

 

Recent climate change is characterized by rapid global warming, but the goal of the Paris Agreement is to achieve a stable climate where global temperatures remain well below 2°C above pre‐industrial levels. Inferences about conditions at or below 2°C are usually made based on transient climate projections. To better understand climate change impacts on natural and human systems under the Paris Agreement, we must understand how a stable climate may differ from transient conditions at the same warming level. Here we examine differences between transient and quasi‐equilibrium climates using a statistical framework applied to greenhouse gas‐only model simulations. This allows us to infer climate change patterns at 1.5°C and 2°C global warming in both transient and quasi‐equilibrium climate states. We find substantial local differences between seasonal‐average temperatures dependent on the rate of global warming, with mid‐latitude land regions in boreal summer considerably warmer in a transient climate than a quasi‐equilibrium state at both 1.5°C and 2°C global warming. In a rapidly warming world, such locations may experience a temporary emergence of a local climate change signal that weakens if the global climate stabilizes and the Paris Agreement goals are met. Our research demonstrates that the rate of global warming must be considered in regional projections.