Sea ice feedbacks influence the isotopic signature of Greenland ice sheet elevation changes: Last interglacial HadCM3 simulations

Changes in the Greenland ice sheet (GIS) affect global sea level. Greenland stable water isotope (δ18O) records from ice cores offer information on past changes in the surface of the GIS. Here, we use the isotope-enabled Hadley Centre Coupled Model version 3 (HadCM3) climate model to simulate a set of last interglacial (LIG) idealised GIS surface elevation change scenarios focusing on GIS ice core sites. We investigate how δ18O depends on the magnitude and sign of GIS elevation change and evaluate how the response is altered by sea ice changes. We find that modifying GIS elevation induces changes in Northern Hemisphere atmospheric circulation, sea ice and precipitation patterns. These climate feedbacks lead to ice-core-averaged isotopic lapse rates of 0.49 ‰ (100 m)−1 for the lowered GIS states and 0.29 ‰ (100 m)−1 for the enlarged GIS states. This is lower than the spatially derived Greenland lapse rates of 0.62–0.72 ‰ (100 m)−1. These results thus suggest non-linearities in the isotope–elevation relationship and have consequences for the interpretation of past elevation and climate changes across Greenland. In particular, our results suggest that winter sea ice changes may significantly influence isotope–elevation gradients: winter sea ice effect can decrease (increase) modelled core-averaged isotopic lapse rate values by about −19 % (and +28 %) for the lowered (enlarged) GIS states, respectively. The largest influence of sea ice on δ18O changes is found in coastal regions like the Camp Century site

The Impact of CO2 and Climate State on Whether Dansgaard–Oeschger Type Oscillations Occur in Climate Models

Greenland ice core records feature Dansgaard–Oeschger (D-O) events, which are abrupt warming episodes followed by gradual cooling during ice age climate. The three climate models used in this study (CCSM4, MPI-ESM, and HadCM3) show spontaneous self-sustained D-O-like oscillations (albeit with differences in amplitude, duration, and shape) in a remarkably similar, narrow window of carbon dioxide (CO2) concentration, roughly 185–230 ppm. This range matches atmospheric CO2 during Marine Isotopic Stage 3 (MIS 3: between 27.8 and 59.4 thousand of years BP, hereafter ka), a period when D-O events were most frequent. Insights from the three climate models point to North Atlantic (NA) sea-ice coverage as a key ingredient behind D-O type oscillations, which acts as a “tipping element.” Other climate state properties such as Mean Atlantic Meridional Overturning Circulation strength, global mean temperature and salinity gradient in the Atlantic Ocean do not determine whether D-O type behavior can occur in all three models

CMIP6/PMIP4 simulations of the mid-Holocene and Last Interglacial using HadGEM3: comparison to the pre-industrial era, previous model versions and proxy data

Results for these simulations are assessed firstly against the same model's pre-industrial control simulation (a simulation comparison, to describe and understand the differences between the pre-industrial – PI – and the two palaeo simulations) and secondly against previous versions of the same model relative to newly available proxy data (a model–data comparison, to compare all available simulations from the same model with proxy data to assess any improvements due to model advances). The introduction of this newly available proxy data adds further novelty to this study. Globally, for metrics such as 1.5 m temperature and surface rainfall, whilst both the recent palaeoclimate simulations are mostly capturing the expected sign and, in some places, magnitude of change relative to the pre-industrial, this is geographically and seasonally dependent. Compared to newly available proxy data (including sea surface temperature – SST – and rainfall) and also incorporating data from previous versions of the model shows that the relative accuracy of the simulations appears to vary according to metric, proxy reconstruction used for comparison and geographical location. In some instances, such as mean rainfall in the mid-Holocene, there is a clear and linear improvement, relative to proxy data, from the oldest to the newest generation of the model. When zooming into northern Africa, a region known to be problematic for models in terms of rainfall enhancement, the behaviour of the West African monsoon in both recent palaeoclimate simulations is consistent with current understanding, suggesting a wetter monsoon during the mid-Holocene and (more so) the Last Interglacial, relative to the pre-industrial era. However, regarding the well-documented “Saharan greening” during the mid-Holocene, results here suggest that the most recent version of the UK's physical model is still unable to reproduce the increases suggested by proxy data, consistent with all other previous models to date

A multi-model CMIP6-PMIP4 study of Arctic sea ice at 127 ka: sea ice data compilation and model differences

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

Dansgaard–Oeschger events in climate models: review and baseline Marine Isotope Stage 3 (MIS3) protocol

Dansgaard–Oeschger (D–O) events, millennial-scale climate oscillations between stadial and interstadial conditions (of up to 10–15 ∘C in amplitude at high northern latitudes), occurred throughout the Marine Isotope Stage 3 (MIS3; 27.8–59.4 ka) period. The climate modelling community up to now has not been able to answer the question of whether our climate models are too stable to simulate D–O events. To address this, this paper lays the ground-work for a MIS3 D–O protocol for general circulation models which are used in the International Panel for Climate Change (IPCC) assessments. We review the following: D–O terminology, community progress on simulating D–O events in these IPCC-class models (processes and published examples), and evidence about the boundary conditions under which D–O events occur. We find that no model exhibits D–O-like behaviour under pre-industrial conditions. Some, but not all, models exhibit D–O-like oscillations under MIS3 and/or full glacial conditions. Greenhouse gases and ice sheet configurations are crucial. However most models have not run simulations of long enough duration to be sure which models show D–O-like behaviour, under either MIS3 or full glacial states. We propose a MIS3 baseline protocol at 34 ka, which features low obliquity values, medium to low MIS3 greenhouse gas values, and the intermediate ice sheet configuration, which our review suggests are most conducive to D–O-like behaviour in models. We also provide a protocol for a second freshwater (Heinrich-event-preconditioned) experiment, since previous work suggests that this variant may be helpful in preconditioning a state in models which is conducive to D–O events. This review provides modelling groups investigating MIS3 D–O oscillations with a common framework, which is aimed at (1) maximising the chance of the occurrence of D–O-like events in the simulations, (2) allowing more precise model–data evaluation, and (3) providing an adequate central point for modellers to explore model stability

Dansgaard-Oeschger events in climate models: Review and baseline MIS3 protocol [in review]

Dansgaard-Oeschger (D-O) events, millennial-scale climate oscillations between stadial and interstadial conditions (of up to 10–15 °C in amplitude at high northern latitudes), occurred throughout the Marine Isotope Stage 3 (MIS3; 27.8–59.4 ka) period. The climate modelling community up to now has not been able to answer the question: Are our climate models too stable to simulate D-O events? To address this, this manuscript lays the ground-work for a MIS3 D-O protocol for general circulation models which are used in the International Panel for Climate Change (IPCC) assessments. We review: D-O terminology, community progress on simulating D-O events in these IPCC-class models (processes and published examples), and evidence about the boundary conditions under which D-O events occur. We find that no model exhibits D-O like behaviour under pre-industrial conditions. Some, but not all, models exhibit D-O like oscillations under MIS3 and/or full glacial conditions. Greenhouse gases and ice-sheet configurations are crucial. However most models have not run simulations of long enough duration to be sure which models show D-O like behaviour, under either MIS3 or full glacial states. We propose a MIS3 baseline protocol at 38 ky (38 to 32 ky) period, which (1) shows a regular sequence of D-O events, and (2) features the intermediate ice-sheet configuration and medium-to-low MIS3 greenhouse gas values which our review suggests are most conducive to D-O like behaviour in models. We also provide a protocol for a second "kicked Heinrich meltwater" experiment, since previous work suggests that this variant may be helpful in preconditioning a state in models which is conducive to D-O events. This review and protocol is intended to provide modelling groups investigating MIS3 D-O oscillations with a common framework

Summer surface air temperature proxies point to near sea-ice-free conditions in the Arctic at 127 ka [in review]

The Last Interglacial (LIG) period, which had higher summer solar insolation than today, has been suggested as the last time that Arctic summers were ice-free. However, the latest suite of Coupled Modelling Intercomparison Project 6 Paleoclimate (CMIP6-PMIP4) simulations of the LIG produce a wide range of Arctic summer minimum sea ice area (SIA) results, ranging from a 30 % to 96 % reduction from the pre-industrial (PI). Sea ice proxies are also currently neither abundant nor consistent enough to determine the most realistic state. Here we estimate LIG minimum SIA indirectly through the use of 21 proxy records for LIG Summer Surface Air Temperature (SSAT) and 11 CMIP6-PMIP4 models for the LIG. We use two approaches. First, we use two tests to determine how skilful models are at simulating observed proxies for ΔSSAT (where Δ refers to LIG-PI). This identifies a positive correlation between model skill and the magnitude of ΔSIA: the most reliable models simulate a larger sea ice reduction. Averaging the most skilful two models yields an average SIA of 1.3 mill. km2 for the LIG. This equates to a 4.5 mill. km2, or a 79 %, SIA reduction from the PI to the LIG. Second, across the 11 models, the averaged ΔSSAT at the 21 proxy locations is inversely correlated with ΔSIA (r = -0.86). In other words, the models show that a larger Arctic warming is associated with a greater sea ice reduction. Using the proxy record-averaged ΔSSAT of 4.5 ± 1.7 K and the relationship between ΔSSAT and ΔSIA, suggests an estimated ΔSIA of 4.4 mill. km2 or 77 % less than the PI. The mean proxy-location ΔSSAT is well-correlated with the Arctic-wide ΔSSAT north of 60° N (r=0.97) and this relationship is used to show that the mean proxy record ΔSSAT is equivalent to an Arctic-wide warming of 3.7±0.1 K at the LIG compared to the PI. Applying this Arctic-wide ΔSSAT and its modelled relationship to ΔSIA, results in a similar estimate of LIG sea ice reduction of 4.5 mill. km2. The LIG climatological minimum SIA of 1.3 mill. km2 is close to the definition of a summer ice-free Arctic, which is a maximum sea ice extent less than 1 mill. km2. The results of this study thus suggest that the Arctic likely experienced a mixture of ice-free and near ice-free summers during the LIG