The PMIP4 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3 simulations

Abstract

Abstract. The Last Glacial Maximum (LGM, ∼ 21 000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models has been used to generate LGM simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here, we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4, most of which are PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3, most of which are PMIP3-CMIP5). We show that the global averages of the PMIP4 simulations span a larger range in terms of mean annual surface air temperature and mean annual precipitation compared to the PMIP3-CMIP5 simulations, with some PMIP4 simulations reaching a globally colder and drier state. However, the multi-model global cooling average is similar for the PMIP4 and PMIP3 ensembles, while the multi-model PMIP4 mean annual precipitation average is drier than the PMIP3 one. There are important differences in both atmospheric and oceanic circulations between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large. Therefore, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land–sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the paleoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. These results point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.

Warming‐Induced Northwestward Migration of the Asian Summer Monsoon in the Geological Past: Evidence From Climate Simulations and Geological Reconstructions

“…LGM Pre-Industrial Mid-Holocene Mid-Pliocene References Atmospheric CO 2 concentrations ∼185 ppmv 280 ppmv ∼280 ppmv 400-450 ppmv Lüthi et al, 2008;Lunt et al, 2012;Pagani et al, 2010;Yang et al, 2018 Global mean air temperature compared with today ∼5°C lower ∼0.8°C-1.2°C lower ∼0.7°C higher ∼1.9°C-3.6°C higher Chang, 2018;Hansen et al, 2006;Intergovernmental Panel on Climate Change, 2013;Marcott et al, 2013 (Yan et al, 2018), and has been widely used to analyze climate changes (Kageyama et al, 2021;Saito et al, 2013;Yan et al, 2018). In this study, all analyses were performed using the multi-model ensemble mean (MME).…”

Climate and ice sheet evolutions from the last glacial maximum to the pre-industrial period with an ice-sheet–climate coupled model

“…It has also been used to study Heinrich events during the last glacial period (Roche et al, 2014b) or to investigate the processes responsible for changes in the carbon cycle during the last eight interglacial periods (Bouttes et al, 2018). With a similar model configuration to the one used in this work, iLOVECLIM results were included in the fourth phase of the Palaeoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP) (Kageyama et al, 2021).…”

“…During the last deglaciation (∼ 21-7 ka), the sea level rose by about 120 metres to reach approximately its presentday level (Waelbroeck et al, 2002;Lambeck et al, 2014). This rise is mostly explained by the disintegration of the North American and Eurasian ice sheets, while Greenland and Antarctica together probably contributed less than 20 m (Whitehouse et al, 2012;Briggs et al, 2014;Lecavalier et al, 2014;Simms et al, 2019).…”

Impact of Southern Ocean surface conditions on deep ocean circulation during the LGM: a model analysis

“…Density gradients between this water mass and others -such as its counterpart, the northern-sourced North Atlantic Deep Water (NADW) -determine the water mass distribution and F. Lhardy et al: LGM surface conditions and deep ocean circulation the large-scale circulation. Rearrangement of water masses explains part of past changes in the carbon storage capacity of the oceans (Buchanan et al, 2016;Khatiwala et al, 2019;Yu et al, 2016), which stresses the importance of correctly simulating the processes affecting the deep ocean circulation.…”