ALBERT

Description: The Pliocene Model Intercomparison Project is the first coordinated climate model comparison for a warmer palaeoclimate with atmospheric CO2 significantly higher than pre-industrial concentrations. The simulations of the mid-Pliocene warm period show global warming of between 1.8 and 3.6 °C above pre-industrial surface air temperatures, with significant polar amplification. Here we perform energy balance calculations on all eight of the coupled ocean–atmosphere simulations within PlioMIP Experiment 2 to evaluate the causes of the increased temperatures and differences between the models. In the tropics simulated warming is dominated by greenhouse gas increases, with cloud albedo feedbacks enhancing the warming in most of the models, but by widely varying amounts. The responses to mid-Pliocene climate forcing in the Northern Hemisphere mid-latitudes are substantially different between the climate models, with the only consistent response being a warming due to increased greenhouse gases. In the high latitudes all the energy balance components become important, but the dominant warming influence comes from the clear sky albedo. This demonstrates the importance of specified ice sheet and high latitude vegetation boundary conditions and simulated sea ice and snow albedo feedbacks. The largest components in the overall uncertainty are associated with cloud albedo feedbacks in the tropics and polar clear sky albedo, particularly in sea ice regions. These simulations show that high latitude albedo feedbacks provide the most significant enhancements to Pliocene greenhouse warming.

Description: Based on simulations with 15 climate models in the Pliocene Model Intercomparison Project (PlioMIP), the regional climate of East Asia (focusing on China) during the mid-Pliocene is investigated in this study. Compared to the pre-industrial, the multi-model ensemble mean (MMM) of all models shows the East Asian summer winds (EASWs) largely strengthen in monsoon China, and the East Asian winter winds (EAWWs) strengthen in south monsoon China but slightly weaken in north monsoon China in the mid-Pliocene. The MMM of all models also illustrates a warmer and wetter mid-Pliocene climate in China. The simulated weakened mid-Pliocene EAWWs in north monsoon China and intensified EASWs in monsoon China agree well with geological reconstructions. However, there is a large model–model discrepancy in simulating mid-Pliocene EAWW, which should be further addressed in the future work of PlioMIP.

Description: The last interglaciation (~130 to 116 ka) is a time period with a strong astronomically induced seasonal forcing of insolation compared to the present. Proxy records indicate a significantly different climate to that of the modern, in particular Arctic summer warming and higher eustatic sea level. Because the forcings are relatively well constrained, it provides an opportunity to test numerical models which are used for future climate prediction. In this paper we compile a set of climate model simulations of the early last interglaciation (130 to 125 ka), encompassing a range of model complexities. We compare the simulations to each other and to a recently published compilation of last interglacial temperature estimates. We show that the annual mean response of the models is rather small, with no clear signal in many regions. However, the seasonal response is more robust, and there is significant agreement amongst models as to the regions of warming vs cooling. However, the quantitative agreement of the model simulations with data is poor, with the models in general underestimating the magnitude of response seen in the proxies. Taking possible seasonal biases in the proxies into account improves the agreement, but only marginally. However, a lack of uncertainty estimates in the data does not allow us to draw firm conclusions. Instead, this paper points to several ways in which both modelling and data could be improved, to allow a more robust model–data comparison.

Description: The Last Interglacial period (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models' representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 16 climate models in terms of Arctic sea ice. The multi-model mean reduction in minimum sea ice area from the pre industrial period (PI) to the LIG reaches 50 % (multi-model mean LIG area is 3.20×106 km2, compared to 6.46×106 km2 for the PI). On the other hand, there is little change for the maximum sea ice area (which is 15–16×106 km2 for both the PI and the LIG. To evaluate the model results we synthesise LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. The reconstructions for the northern North Atlantic show year-round ice-free conditions, and most models yield results in agreement with these reconstructions. Model–data disagreement appear for the sites in the Nordic Seas close to Greenland and at the edge of the Arctic Ocean. The northernmost site with good chronology, for which a sea ice concentration larger than 75 % is reconstructed even in summer, discriminates those models which simulate too little sea ice. However, the remaining models appear to simulate too much sea ice over the two sites south of the northernmost one, for which the reconstructed sea ice cover is seasonal. Hence models either underestimate or overestimate sea ice cover for the LIG, and their bias does not appear to be related to their bias for the pre-industrial period. Drivers for the inter-model differences are different phasing of the up and down short-wave anomalies over the Arctic Ocean, which are associated with differences in model albedo; possible cloud property differences, in terms of optical depth; and LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally, we note that inter-comparisons between the LIG simulations and simulations for future climate with moderate (1 % yr−1) CO2 increase show a relationship between LIG sea ice and sea ice simulated under CO2 increase around the years of doubling CO2. The LIG may therefore yield insight into likely 21st century Arctic sea ice changes using these LIG simulations.

Description: In the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2), coupled climate models have been used to simulate an interglacial climate during the mid-Piacenzian warm period (mPWP; 3.264 to 3.025 Ma). Here, we compare the Atlantic Meridional Overturning Circulation (AMOC), poleward ocean heat transport and sea surface warming in the Atlantic simulated with these models. In PlioMIP2, all models simulate an intensified mid-Pliocene AMOC. However, there is no consistent response in the simulated Atlantic ocean heat transport nor in the depth of the Atlantic overturning cell. The models show a large spread in the simulated AMOC maximum, the Atlantic ocean heat transport and the surface warming in the North Atlantic. Although a few models simulate a surface warming of ∼ 8–12 ∘C in the North Atlantic, similar to the reconstruction from Pliocene Research, Interpretation and Synoptic Mapping (PRISM) version 4, most models appear to underestimate this warming. The large model spread and model–data discrepancies in the PlioMIP2 ensemble do not support the hypothesis that an intensification of the AMOC, together with an increase in northward ocean heat transport, is the dominant mechanism for the mid-Pliocene warm climate over the North Atlantic.

Description: The Last Glacial Maximum (LGM, 21 000 years ago) is one of the suite of paleoclimate simulations included in the current phase of the Coupled Model Intercomparison Project (CMIP6). It is an interval when insolation was similar to the present, but global ice volume was at a maximum, eustatic sea level was at or close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. The LGM has been a focus for the Paleoclimate Modelling Intercomparison Project (PMIP) since its inception, and thus many of the problems that might be associated with simulating such a radically different climate are well documented. The LGM state provides an ideal case study for evaluating climate model performance because the changes in forcing and temperature between the LGM and pre-industrial are of the same order of magnitude as those projected for the end of the 21st century. Thus, the CMIP6 LGM experiment could provide additional information that can be used to constrain estimates of climate sensitivity. The design of the Tier 1 LGM experiment (lgm) includes an assessment of uncertainties in boundary conditions, in particular through the use of different reconstructions of the ice sheets and of the change in dust forcing. Additional (Tier 2) sensitivity experiments have been designed to quantify feedbacks associated with land-surface changes and aerosol loadings, and to isolate the role of individual forcings. Model analysis and evaluation will capitalize on the relative abundance of paleoenvironmental observations and quantitative climate reconstructions already available for the LGM.

Description: Two interglacial epochs are included in the suite of Paleoclimate Modeling Intercomparison Project (PMIP4) simulations in the Coupled Model Intercomparison Project (CMIP6). The experimental protocols for simulations of the mid-Holocene (midHolocene, 6000 years before present) and the Last Interglacial (lig127k, 127 000 years before present) are described here. These equilibrium simulations are designed to examine the impact of changes in orbital forcing at times when atmospheric greenhouse gas levels were similar to those of the preindustrial period and the continental configurations were almost identical to modern ones. These simulations test our understanding of the interplay between radiative forcing and atmospheric circulation, and the connections among large-scale and regional climate changes giving rise to phenomena such as land–sea contrast and highlatitude amplification in temperature changes, and responses of the monsoons, as compared to today. They also provide an opportunity, through carefully designed additional sensitivity experiments, to quantify the strength of atmosphere, ocean, cryosphere, and land-surface feedbacks. Sensitivity experiments are proposed to investigate the role of freshwater forcing in triggering abrupt climate changes within interglacial epochs. These feedback experiments naturally lead to a focus on climate evolution during interglacial periods, which will be examined through transient experiments. Analyses of the sensitivity simulations will also focus on interactions between extratropical and tropical circulation, and the relationship between changes in mean climate state and climate variability on annual to multi-decadal timescales. The comparative abundance of paleoenvironmental data and of quantitative climate reconstructions for the Holocene and Last Interglacial make these two epochs ideal candidates for systematic evaluation of model performance, and such comparisons will shed new light on the importance of external feedbacks (e.g., vegetation, dust) and the ability of state-of-the-art models to simulate climate changes realistically.

Description: Eight general circulation models have simulated the mid-Pliocene warm period (mid-Pliocene, 3.264 to 3.025 Ma) as part of the Pliocene Modelling Intercomparison Project (PlioMIP). Here, we analyse and compare their simulation of Arctic sea ice for both the pre-industrial period and the mid-Pliocene. Mid-Pliocene sea ice thickness and extent is reduced, and the model spread of extent is more than twice the pre-industrial spread in some summer months. Half of the PlioMIP models simulate ice-free conditions in the mid-Pliocene. This spread amongst the ensemble is in line with the uncertainties amongst proxy reconstructions for mid-Pliocene sea ice extent. Correlations between mid-Pliocene Arctic temperatures and sea ice extents are almost twice as strong as the equivalent correlations for the pre-industrial simulations. The need for more comprehensive sea ice proxy data is highlighted, in order to better compare model performances.

Description: During an interval of the Late Pliocene, referred to here as the mid-Pliocene Warm Period (mPWP; 3.264 to 3.025 million years ago), global mean temperature was similar to that predicted for the end of this century, and atmospheric carbon dioxide concentrations were higher than pre-industrial levels. Sea level was also higher than today, implying a significant reduction in the extent of the ice sheets. Thus, the mPWP provides a natural laboratory in which to investigate the long-term response of the Earth's ice sheets and sea level in a warmer-than-present-day world. At present, our understanding of the Greenland ice sheet during the mPWP is generally based upon predictions using single climate and ice sheet models. Therefore, it is essential that the model dependency of these results is assessed. The Pliocene Model Intercomparison Project (PlioMIP) has brought together nine international modelling groups to simulate the warm climate of the Pliocene. Here we use the climatological fields derived from the results of the 15 PlioMIP climate models to force an offline ice sheet model. We show that mPWP ice sheet reconstructions are highly dependent upon the forcing climatology used, with Greenland reconstructions ranging from an ice-free state to a near-modern ice sheet. An analysis of the surface albedo variability between the climate models over Greenland offers insights into the drivers of inter-model differences. As we demonstrate that the climate model dependency of our results is high, we highlight the necessity of data-based constraints of ice extent in developing our understanding of the mPWP Greenland ice sheet.