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: As ice sheets grow or decay, the net flux of freshwater into the ocean changes and the bedrock adjusts due to isostatic adjustments, leading to variations in the bottom topography and the oceanic boundaries. This process was particularly intense during the last deglaciation due to the high rates of ice-sheet melting. It is, therefore, necessary to consider transient ocean bathymetry and coastlines when attempting to simulate the last deglaciation with Earth system models (ESMs). However, in most standard ESMs the land-sea mask is fixed throughout simulations because the generation of a new ocean model bathymetry implies several levels of manual corrections, a procedure that is hardly doable very often for long runs. This is one of the main technical problems towards simulating a complete glacial cycle with general circulation models. For the first time, we present a tool allowing for an automatic computation of bathymetry and land-sea mask changes in the Max Planck Institute Earth System Model (MPI-ESM). The algorithms developed in this paper can easily be adapted to any free-surface ocean model that uses the Arakawa-C grid in the horizontal and z-grid in the vertical including partial bottom cells. The strategy applied is described in detail and the algorithms are tested in a long-term simulation demonstrating the reliable behaviour. Our approach guarantees the conservation of mass and tracers at global and regional scales; that is, changes in a single grid point are only propagated regionally. The procedures presented here are an important contribution to the development of a fully coupled ice sheet–solid Earth–climate model system with time-varying topography and will allow for transient simulations of the last deglaciation considering interactive bathymetry and land-sea mask.

Description: The continually evolving large ice sheets present in the Northern Hemisphere during the last glacial cycle caused significant changes to river pathways both through directly blocking rivers and through glacial isostatic adjustment. Studies have shown these river pathway changes had a significant impact on the ocean circulation through changing the pattern of freshwater discharge into the oceans. A coupled Earth system model (ESM) simulation of the last glacial cycle thus requires a hydrological discharge model that uses a set of river pathways that evolve with Earth's changing orography while being able to reproduce the known present-day river network given the present-day orography. Here, we present a method for dynamically modelling river pathways that meets such requirements by applying predefined corrections to an evolving fine-scale orography (accounting for the changing ice sheets and isostatic rebound) each time the river directions are recalculated. The corrected orography thus produced is then used to create a set of fine-scale river pathways and these are then upscaled to a coarser scale on which an existing present-day hydrological discharge model within the JSBACH land surface model simulates the river flow. Tests show that this procedure reproduces the known present-day river network to a sufficient degree of accuracy and is able to simulate plausible paleo-river networks. It has also been shown this procedure can be run successfully multiple times as part of a transient coupled climate model simulation.

Description: We investigate the changes in terrestrial natural methane emissions between the Last Glacial Maximum (LGM) and preindustrial (PI) periods by performing time-slice experiments with a methane-enabled version of MPI-ESM, the Max Planck Institute Earth System Model. We consider all natural sources of methane except for emissions from wild animals and geological sources, i.e. emissions from wetlands, fires, and termites. Changes are dominated by changes in tropical wetland emissions, with mid-to-high-latitude wetlands playing a secondary role, and all other natural sources being of minor importance. The emissions are determined by the interplay of vegetation productivity, a function of CO2 and temperature; source area size, affected by sea level and ice sheet extent; and the state of the West African monsoon, with increased emissions from northern Africa during strong monsoon phases. We show that it is possible to explain the difference in atmospheric methane between LGM and PI purely by changes in emissions. As emissions more than double between LGM and PI, changes in the atmospheric lifetime of CH4, as proposed in other studies, are not required.

Description: Publications on temperate deciduous tree refugia in Europe are abundant, but little is known about the patterns of temperate tree refugia in eastern Asia, an area where biodiversity survived Quaternary glaciations and which has the world's most diverse temperate flora. Our goal is to compare climate model simulations with pollen data in order to establish the location of glacial refugia during the Last Glacial Maximum (LGM). Limits in which temperate deciduous trees can survive are taken from the literature. The model outputs are first tested for the present by comparing climate models with published modern pollen data. As this method turned out to be satisfactory for the present, the same approach was used for the LGM. Climate model simulations (ECHAM5 T106), statistically further downscaled, are used to infer the temperate deciduous tree distribution during the LGM. These were compared with available fossil temperate tree pollen occurrences. The impact of the LGM on the eastern Asian climate was much weaker than on the European climate. The area of possible tree growth shifts only by about 2∘ to the south between the present and the LGM. This contributes to explaining the greater biodiversity of forests in eastern Asia compared to Europe. Climate simulations and the available, although fractional, fossil pollen data agree. Therefore, climate estimations can safely be used to fill areas without pollen data by mapping potential refugia distributions. The results show two important areas with population connectivity: the Yellow Sea emerged shelf and the southern Himalayas. These two areas were suitable for temperate deciduous tree growth, providing corridors for population migration and connectivity (i.e. less population fragmentation) in glacial periods. Many tree populations live in interglacial refugia, not glacial ones. The fact that the model simulation for the LGM fits so well with observed pollen distribution is another indication that the model used is good enough to also simulate the LGM period.

Description: In this paper we introduce a Bayesian framework, which is explicit about prior assumptions, for using model ensembles and observations together to constrain future climate change. The emergent constraint approach has seen broad application in recent years, including studies constraining the equilibrium climate sensitivity (ECS) using the Last Glacial Maximum (LGM) and the mid-Pliocene Warm Period (mPWP). Most of these studies were based on ordinary least squares (OLS) fits between a variable of the climate state, such as tropical temperature, and climate sensitivity. Using our Bayesian method, and considering the LGM and mPWP separately, we obtain values of ECS of 2.7 K (0.6–5.2, 5th–95th percentiles) using the PMIP2, PMIP3, and PMIP4 datasets for the LGM and 2.3 K (0.5–4.4) with the PlioMIP1 and PlioMIP2 datasets for the mPWP. Restricting the ensembles to include only the most recent version of each model, we obtain 2.7 K (0.7–5.2) using the LGM and 2.3 K (0.4–4.5) using the mPWP. An advantage of the Bayesian framework is that it is possible to combine the two periods assuming they are independent, whereby we obtain a tighter constraint of 2.5 K (0.8–4.0) using the restricted ensemble. We have explored the sensitivity to our assumptions in the method, including considering structural uncertainty, and in the choice of models, and this leads to 95 % probability of climate sensitivity mostly below 5 K and only exceeding 6 K in a single and most uncertain case assuming a large structural uncertainty. The approach is compared with other approaches based on OLS, a Kalman filter method, and an alternative Bayesian method. An interesting implication of this work is that OLS-based emergent constraints on ECS generate tighter uncertainty estimates, in particular at the lower end, an artefact due to a flatter regression line in the case of lack of correlation. Although some fundamental challenges related to the use of emergent constraints remain, this paper provides a step towards a better foundation for their potential use in future probabilistic estimations of climate sensitivity.

Description: A realistic simulation of the surface mass balance (SMB) is essential for simulating past and future ice-sheet changes. As most state-of-the-art Earth system models (ESMs) are not capable of realistically representing processes determining the SMB, most studies of the SMB are limited to observations and regional climate models and cover the last century and near future only. Using transient simulations with the Max Planck Institute ESM in combination with an energy balance model (EBM), we extend previous research and study changes in the SMB and equilibrium line altitude (ELA) for the Northern Hemisphere ice sheets throughout the last deglaciation. The EBM is used to calculate and downscale the SMB onto a higher spatial resolution than the native ESM grid and allows for the resolution of SMB variations due to topographic gradients not resolved by the ESM. An evaluation for historical climate conditions (1980–2010) shows that derived SMBs compare well with SMBs from regional modeling. Throughout the deglaciation, changes in insolation dominate the Greenland SMB. The increase in insolation and associated warming early in the deglaciation result in an ELA and SMB increase. The SMB increase is caused by compensating effects of melt and accumulation: the warming of the atmosphere leads to an increase in melt at low elevations along the ice-sheet margins, while it results in an increase in accumulation at higher levels as a warmer atmosphere precipitates more. After 13 ka, the increase in melt begins to dominate, and the SMB decreases. The decline in Northern Hemisphere summer insolation after 9 ka leads to an increasing SMB and decreasing ELA. Superimposed on these long-term changes are centennial-scale episodes of abrupt SMB and ELA decreases related to slowdowns of the Atlantic meridional overturning circulation (AMOC) that lead to a cooling over most of the Northern Hemisphere.

Description: 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 have been used to generate LGM simulations as part of the Palaeoclimate 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-CMIP6) and compare them with the previous generation of simulations (PMIP3-CMIP5). We show that the PMIP4-CMIP6 are globally less cold and less dry than the PMIP3-CMIP5 simulations, most probably because of the use of a more realistic specification of the northern hemisphere ice sheets in the latest simulations although changes in model configuration may also contribute to this. There are important differences in both atmospheric and ocean circulation 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 so, 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 palaeoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. The spatial patterns of increased precipitation associated with changes in the jet streams are also poorly captured. However, changes in the tropics are more realistic, particularly the changes in tropical temperatures over the oceans. Although these results are preliminary in nature, because of the limited number of LGM simulations currently available, they nevertheless point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.

Description: The Greenland Ice Sheet (GrIS) mass loss has been accelerating at a rate of about 20 ± 10 Gt/yr2 since the end of the 1990's, with around 60 % of this mass loss directly attributed to enhanced surface meltwater runoff. However, in the climate and glaciology communities, different approaches exist on how to model the different surface mass balance (SMB) components using: (1) complex physically-based climate models which are computationally expensive; (2) intermediate complexity energy balance models; (3) simple and fast positive degree day models which base their inferences on statistical principles and are computationally highly efficient. Additionally, many of these models compute the SMB components based on different spatial and temporal resolutions, with different forcing fields as well as different ice sheet topographies and extents, making inter-comparison difficult. In the GrIS SMB model intercomparison project (GrSMBMIP) we address these issues by forcing each model with the same data (i.e., the ERA-Interim reanalysis) except for two global models for which this forcing is limited to the oceanic conditions, and at the same time by interpolating all modelled results onto a common ice sheet mask at 1 km horizontal resolution for the common period 1980–2012. The SMB outputs from 13 models are then compared over the GrIS to (1) SMB estimates using a combination of gravimetric remote sensing data from GRACE and measured ice discharge, (2) ice cores, snow pits, in-situ SMB observations, and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Our results reveal that the mean GrIS SMB of all 13 models has been positive between 1980 and 2012 with an average of 340 ± Gt/yr, but has decreased at an average rate of −7.3 Gt/yr2 (with a significance of 96 %), mainly driven by an increase of 8.0 Gt/yr2 (with a significance of 98 %) in meltwater runoff. Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting the need for accurate representation of the GrIS ablation zone extent and processes driving the surface melt. In addition, a higher density of in-situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 mWE/yr due to large discrepancies in modelled snowfall accumulation. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of same order than RCMs with observations and remain then useful tools for long-term simulations. Finally, it is interesting to note that the ensemble mean of the 13 models produces the best estimate of the present day SMB relative to observations, suggesting that biases are not systematic among models.

Description: 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.