Spatial variations in sea surface temperature (SST) and rainfall changes over the tropics are investigated based on ensemble simulations for the first half of the 21st century under the greenhouse gas (GHG) emission scenario A1B with coupled ocean-atmosphere general circulation models at the Geophysical Fluid Dynamics Laboratory (GFDL) and National Center for Atmospheric Research (NCAR). Despite a GHG increase that is nearly uniform in space, pronounced patterns emerge in both SST and precipitation. Regional differences in SST warming can be as large as the tropical mean warming. Specifically, the tropical Pacific warming features a conspicuous maximum along the equator and a minimum in the southeast subtropics. The former is associated with westerly wind anomalies while the latter is linked to intensified southeast trade winds, suggestive of wind-evaporation-SST feedback. There is a tendency for a greater warming in the northern than southern subtropics in accordance with asymmetries in trade wind changes. Over the equatorial Indian Ocean, surface wind anomalies are easterly, the thermocline shoals and the warming is reduced in the east, indicative of Bjerknes feedback. In the midlatitudes, ocean circulation changes generate narrow banded structures in SST warming. The warming is negatively correlated with wind speed change over

Recent coordinated efforts, in which numerous general circulation climate models have been run for a common set of experiments, have produced large datasets of projections of future climate for various sce-narios. Those multimodel ensembles sample initial conditions, parameters, and structural uncertainties in the model design, and they have prompted a variety of approaches to quantifying uncertainty in future climate change. International climate change assessments also rely heavily on these models. These assessments often provide equal-weighted averages as best-guess results, assuming that individual model biases will at least partly cancel and that a model average prediction is more likely to be correct than a prediction from a single model based on the result that a multimodel average of present-day climate generally outperforms any in-dividual model. This study outlines the motivation for using multimodel ensembles and discusses various challenges in interpreting them. Among these challenges are that the number of models in these ensembles is usually small, their distribution in the model or parameter space is unclear, and that extreme behavior is often not sampled. Model skill in simulating present-day climate conditions is shown to relate only weakly to the magnitude of predicted change. It is thus unclear by how much the confidence in future projections should increase based on improvements in simulating present-day conditions, a reduction of intermodel

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Climate feedbacks are estimated from fluctuations in the outgoing radiation budget from the latest version of Earth Radiation Budget Experiment (ERBE) nonscanner data. It appears, for the entire tropics, the observed outgoing radiation fluxes increase with the increase in sea surface temperatures (SSTs). The observed behavior of radiation fluxes implies negative feedback processes associated with relatively low climate sensitivity. This is the opposite of the behavior of 11 atmospheric models forced by the same SSTs. Therefore, the models display much higher climate sensitivity than is inferred from ERBE, though it is difficult to pin down such high sensitivities with any precision. Results also show, the feedback in ERBE is mostly from shortwave radiation while the feedback in the models is mostly from longwave radiation. Although such a test does not distinguish the mechanisms, this is important since the inconsistency of climate feedbacks constitutes a very fundamental problem in climate prediction.

Climate models differ in their responses to imposed forcings, such as increased greenhouse gas concentrations, due to different climate feedback strengths. Feed-backs in NCAR’s Community Atmospheric Model (CAM) are separated into two components: the change in climate components in response to an imposed forcing and the “radiative kernel, ” the effect that climate changes have on the top-of-the-atmosphere (TOA) radiative budget. This technique’s usefulness depends on the linearity of the feedback processes. For the case of CO2 doubling, the sum of the effects of water vapor, temperature, and surface albedo changes on the TOA clear-sky flux is similar to the clear-sky flux changes directly calculated by CAM. When monthly averages are used rather than values from every time step, the global av-erage TOA shortwave change is underestimated by a quarter partially as a result of intra-month correlations of surface albedo with the radiative kernel. The TOA longwave flux changes do not depend on the averaging period. The longwave zonal averages are within 10 % of the model-calculated values, while the global average differs by only 2%. Cloud radiative forcing (∆CRF) is often used as a diagnostic of cloud feedback strength. The net effect of the water vapor, temperature, and sur-face albedo changes on ∆CRF is-1.6 Wm−2, based on the kernel technique, while the total ∆CRF from CAM is-1.3 Wm−2, indicating these components contribute significantly to∆CRF and make it more negative. Assuming linearity of the∆CRF contributions, these results indicate that the net cloud feedback in CAM is positive. 1 1.

Quantifying the equilibrium response of global temperatures to an increase in atmospheric carbon dioxide concentrations is one of the cornerstones of climate research. Components of the Earth’s climate system that vary over long timescales, such as ice sheets and vegetation, could have an important effect on this temperature sensitivity, but have often been neglected. Here we use a coupled atmosphere–ocean general circulation model to simulate the climate of the mid-Pliocene warm period (about three million years ago), and analyse the forcings and feedbacks that contributed to the relatively warm temperatures. Furthermore, we compare our simulation with proxy records of mid-Pliocene sea surface temperature. Taking these lines of evidence together, we estimate that the response of the Earth system to elevated atmospheric carbon dioxide concentrations is 30–50 % greater than the response based on those fast-adjusting components of the climate system that are used traditionally to estimate climate sensitivity. We conclude that targets for the long-term stabilization of atmospheric greenhouse-gas concentrations aimed at preventing a dangerous human interference with the climate system should take into account this higher sensitivity of the Earth system. Since the 1979 National Research Council report 1, the concept of climate sensitivity has been discussed extensively (see, for example, refs 2–4). It is usually defined as the increase in global mean temperature owing to a doubling of CO2 after the

There is large uncertainty about the magnitude of warming and how rainfall patterns will change in response to any given scenario of future changes in atmospheric composition and land use. The models used for future climate projections were developed and calibrated using climate observations from the past 40 years. The geologic record of environmental responses to climate changes provides a unique opportunity to test model performance outside this limited climate range. Evaluation of model simulations against palaeodata shows that models reproduce the direction and large-scale patterns of past changes in climate, but tend to underestimate the magnitude of regional changes. As part of the effort to reduce model-related uncertainty and produce more reliable estimates of twenty-first century climate, the Palaeoclimate Modelling Intercomparison Project is systematically applying palaeoevaluation techniques to simulations of the past run with the models used to make future projections. This evaluation will provide assessments of model performance, including whether a model is sufficiently sensitive to changes in atmospheric composition, as well as providing estimates of the strength of biosphere and other feedbacks that could amplify the model response to these changes and modify the characteristics of climate variability. The fifth phase of the Coupled Model Intercomparison Project (CMIP5) is at present running simulations using state-of-theart models to provide information about the likely evolution of climate over the twenty-first century, with additional experiments

Spatial patterns of local climate feedback and equilibrium partial temperature responses are produced from eight general circulation models with slab oceans forced by doubling carbon dioxide (CO 2). The analysis is extended to other forcing mechanisms with the Met Office Hadley Centre slab ocean climate model version 3 (HadSM3). In agreement with previous studies, the greatest intermodel differences are in the tropical cloud feedbacks. However, the greatest intermodel spread in the equilibrium temperature response comes from the water vapor plus lapse rate feedback, not clouds, disagreeing with a previous study. Although the surface albedo feedback contributes most in the annual mean to the greater warming of high latitudes, compared to the tropics (polar amplification), its effect is significantly ameliorated by shortwave cloud feedback. In different seasons the relative importance of the contributions varies considerably, with longwave cloudy-sky feedback and horizontal heat transport plus ocean heat release playing a major role during winter and autumn when polar amplification is greatest. The greatest intermodel spread in annual mean polar amplification is due to variations in horizontal heat transport and shortwave cloud feedback. Spatial patterns of local climate feedback for HadSM3 forced with 2 3 CO 2, 12 % solar, low-level scattering aerosol and high-level absorbing aerosol are more similar than those for different models forced with 2 3 CO2. However, the equilibrium temperature response to high-level absorbing aerosol shows considerably enhanced polar amplification compared to the other forcing mechanisms, largely due to differences in horizontal heat transport and water vapor plus lapse rate feedback, with the forcing itself acting to reduce amplification. Such variations in highlatitude response between models and forcing mechanisms make it difficult to infer specific causes of recent Arctic temperature change. 1.

regional precipitation

A persistent feature of empirical climate sensitivity estimates is their heavy tailed probability distribution indicating a sizeable probability of high sensitivities. Previous studies make general claims that this upper heavy tail is an unavoidable feature of (i) the Earth system, or of (ii) limitations in our observational capabilities. Here we show that reducing the uncertainty about (i) oceanic heat uptake and (ii) aerosol climate forcing can — in principle — cut off this heavy upper tail of climate sensitivity estimates. Observations of oceanic heat uptake result in a negatively correlated joint likelihood function of climate sensitivity and ocean vertical diffusivity. This correlation is opposite to the positive correlation resulting from observations of surface air temperatures. As a result, the two observational constraints can rule out complementary regions in the climate sensitivity-vertical diffusivity space, and cut off the heavy upper tail of the marginal climate sensitivity estimate. 1.