An unprecedentedly large ensemble of climate simulations with a 60-km atmospheric general circulation model and dynamical downscaling with a 20-km regional climate model has been performed to obtain probabilistic future projections of low-frequency local-scale events. The climate of the latter half of the twentieth century, the climate 4 K warmer than the preindustrial climate, and the climate of the latter half of the twentieth century without historical trends associated with the anthropogenic effect are each simulated for more than 5,000 years. From large ensemble simulations, probabilistic future changes in extreme events are available directly without using any statistical models. The atmospheric models are highly skillful in representing localized extreme events, such as heavy precipitation and tropical cyclones. Moreover, mean climate changes in the models are consistent with those in phase 5 of the Coupled Model Intercomparison Project (CMIP5) ensembles. Therefore, the results enable the assessment of probabilistic change in localized severe events that have large uncertainty from internal variability. The simulation outputs are open to the public as a database called “Database for Policy Decision Making for Future Climate Change” (d4PDF), which is intended to be utilized for impact assessment studies and adaptation planning for global warming.

Climate and environments of the mid-Pliocene warm period (3.264 to 3.025 Ma) have been extensively studied. Whilst numerical models have shed light on the nature of climate at the time, uncertainties in their predictions have not been systematically examined. The Pliocene Model Intercomparison Project quantifies uncertainties in model outputs through a coordinated multi-model and multi-model/data intercomparison. Whilst commonalities in model outputs for the Pliocene are clearly evident, we show substantial variation in the sensitivity of models to the implementation of Pliocene boundary conditions. Models appear able to reproduce many regional changes in temperature reconstructed from geological proxies. However, data/model comparison highlights that models potentially underestimate polar amplification. To assert this conclusion with greater confidence, limitations in the time-averaged proxy data currently available must be addressed. Furthermore, sensitivity tests exploring the known unknowns in modelling Pliocene climate specifically relevant to the high latitudes are essential (e.g. palaeogeography, gateways, orbital forcing and trace gasses). Estimates of longer-term sensitivity to CO₂ (also known as Earth System Sensitivity; ESS), support previous work suggesting that ESS is greater than Climate Sensitivity (CS), and suggest that the ratio of ESS to CS is between 1 and 2, with a "best" estimate of 1.5.

The Pliocene epoch has great potential to improve our understanding of the long-term climatic and environmental consequences of an atmospheric CO₂ concentration near ∼400 parts per million by volume. Here we present the large-scale features of Pliocene climate as simulated by a new ensemble of climate models of varying complexity and spatial resolution based on new reconstructions of boundary conditions (the Pliocene Model Intercomparison Project Phase 2; PlioMIP2). As a global annual average, modelled surface air temperatures increase by between 1.7 and 5.2 ^∘C relative to the pre-industrial era with a multi-model mean value of 3.2 ^∘C. Annual mean total precipitation rates increase by 7 % (range: 2 %–13 %). On average, surface air temperature (SAT) increases by 4.3 ^∘C over land and 2.8 ^∘C over the oceans. There is a clear pattern of polar amplification with warming polewards of 60^∘ N and 60^∘ S exceeding the global mean warming by a factor of 2.3. In the Atlantic and Pacific oceans, meridional temperature gradients are reduced, while tropical zonal gradients remain largely unchanged. There is a statistically significant relationship between a model's climate response associated with a doubling in CO₂ (equilibrium climate sensitivity; ECS) and its simulated Pliocene surface temperature response. The mean ensemble Earth system response to a doubling of CO₂ (including ice sheet feedbacks) is 67 % greater than ECS; this is larger than the increase of 47 % obtained from the PlioMIP1 ensemble. Proxy-derived estimates of Pliocene sea surface temperatures are used to assess model estimates of ECS and give an ECS range of 2.6–4.8 ^∘C. This result is in general accord with the ECS range presented by previous Intergovernmental Panel on Climate Change (IPCC) Assessment Reports.

The mid-Piacenzian climate represents the most geologically recent interval of long-term average warmth relative to the last million years, and shares similarities with the climate projected for the end of the 21^st century. As such, it represents a natural experiment from which we can gain insight into potential climate change impacts, enabling more informed policy decisions for mitigation and adaptation. Here, we present the first systematic comparison of Pliocene sea surface temperature (SST) between an ensemble of eight climate model simulations produced as part of PlioMIP (Pliocene Model Intercomparison Project) with the PRISM (Pliocene Research, Interpretation and Synoptic Mapping) Project mean annual SST field. Our results highlight key regional and dynamic situations where there is discord between the palaeoenvironmental reconstruction and the climate model simulations. These differences have led to improved strategies for both experimental design and temporal refinement of the palaeoenvironmental reconstruction.

The rate of increase of global‐mean surface air temperature (SAT_g) has apparently slowed during the last decade. We investigated the extent to which state‐of‐the‐art general circulation models (GCMs) can capture this hiatus period by using multimodel ensembles of historical climate simulations. While the SAT_g linear trend for the last decade is not captured by their ensemble means regardless of differences in model generation and external forcing, it is barely represented by an 11‐member ensemble of a GCM, suggesting an internal origin of the hiatus associated with active heat uptake by the oceans. Besides, we found opposite changes in ocean heat uptake efficiency (κ), weakening in models and strengthening in nature, which explain why the models tend to overestimate the SAT_g trend. The weakening of κ commonly found in GCMs seems to be an inevitable response of the climate system to global warming, suggesting the recovery from hiatus in coming decades.