ALBERT

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: There is a growing number of proxy-based reconstructions detailing the climatic changes that occurred during the last interglacial period (LIG). This period is of special interest, because large parts of the globe were characterized by a warmer-than-present-day climate, making this period an interesting test bed for climate models in light of projected global warming. However, mainly because synchronizing the different palaeoclimatic records is difficult, there is no consensus on a global picture of LIG temperature changes. Here we present the first model inter-comparison of transient simulations covering the LIG period. By comparing the different simulations, we aim at investigating the common signal in the LIG temperature evolution, investigating the main driving forces behind it and at listing the climate feedbacks which cause the most apparent inter-model differences. The model inter-comparison shows a robust Northern Hemisphere July temperature evolution characterized by a maximum between 130–125 ka BP with temperatures 0.3 to 5.3 K above present day. A Southern Hemisphere July temperature maximum, −1.3 to 2.5 K at around 128 ka BP, is only found when changes in the greenhouse gas concentrations are included. The robustness of simulated January temperatures is large in the Southern Hemisphere and the mid-latitudes of the Northern Hemisphere. For these regions maximum January temperature anomalies of respectively −1 to 1.2 K and −0.8 to 2.1 K are simulated for the period after 121 ka BP. In both hemispheres these temperature maxima are in line with the maximum in local summer insolation. In a number of specific regions, a common temperature evolution is not found amongst the models. We show that this is related to feedbacks within the climate system which largely determine the simulated LIG temperature evolution in these regions. Firstly, in the Arctic region, changes in the summer sea-ice cover control the evolution of LIG winter temperatures. Secondly, for the Atlantic region, the Southern Ocean and the North Pacific, possible changes in the characteristics of the Atlantic meridional overturning circulation are crucial. Thirdly, the presence of remnant continental ice from the preceding glacial has shown to be important when determining the timing of maximum LIG warmth in the Northern Hemisphere. Finally, the results reveal that changes in the monsoon regime exert a strong control on the evolution of LIG temperatures over parts of Africa and India. By listing these inter-model differences, we provide a starting point for future proxy-data studies and the sensitivity experiments needed to constrain the climate simulations and to further enhance our understanding of the temperature evolution of the LIG period.

Description: The Last Interglaciation (∼130 to 116 ka) is a time period with a strong astronomically-induced seasonal forcing of insolation compared to modern. 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 complexity. We compare the models 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 models 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 marginally, but the agreement is still far from perfect. 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: There is a growing number of proxy-based reconstructions detailing the climatic changes during the Last Interglacial period. This period is of special interest because large parts of the globe were characterized by a warmer-than-present-day climate, making this period an interesting test bed for climate models in the light of projected global warming. However, mainly because synchronizing the different records is difficult, there is no consensus on a global picture of Last Interglacial temperature changes. Here we present the first model inter-comparison of transient simulations covering the Last Interglacial period. By comparing the different simulations we aim at investigating the robustness of the simulated surface air temperature evolution. The model inter-comparison shows a robust Northern Hemisphere July temperature evolution characterized by a maximum between 130–122 ka BP with temperatures 0.4 to 6.8 K above pre-industrial values. This temperature evolution is in line with the changes in June insolation and greenhouse-gas concentrations. For the evolution of July temperatures in the Southern Hemisphere, the picture emerging from the inter-comparison is less clear. However, it does show that including greenhouse-gas concentration changes is critical. The simulations that include this forcing show an early, 128 ka BP July temperature anomaly maximum of 0.5 to 2.6 K. The robustness of simulated January temperatures is large in the Southern Hemisphere and the mid-latitudes of the Northern Hemisphere. In these latitudes maximum January temperature anomalies of respectively −2.5 to 2 K and 0 to 2 K are simulated for the period after 118 ka BP. The inter-comparison is inconclusive on the evolution of January temperatures in the high-latitudes of the Northern Hemisphere. Further investigation of regional anomalous patterns and inter-model differences indicate that in specific regions, feedbacks within the climate system are important for the simulated temperature evolution. Firstly in the Arctic region, changes in the summer sea-ice cover control the evolution of Last Interglacial winter temperatures. Secondly, for the Atlantic region, the Southern Ocean and the North Pacific, possible changes in the characteristics of the Atlantic meridional overturning circulation are critical. The third important feedback, having an impact on the temperature evolution of the Northern Hemisphere, is shown to be the presence of remnant continental ice from the preceding glacial period. Another important feedback are changes in the monsoon regime which controls the evolution of temperatures over parts of Africa and India. Finally, the simulations reveal an important land-sea contrast, with temperature changes over the oceans lagging continental temperatures by up to several thousand years. The aforementioned feedback mechanisms tend to be highly model-dependent, indicating that specific proxy-data is needed to constrain future climate simulations and to further enhance our understanding of the evolution of the climate during the Last Interglacial period.

Description: Though primarily driven by insolation changes associated with well-known variations in Earth's astronomical parameters, the response of the climate system during interglacials includes a diversity of feedbacks involving the atmosphere, ocean, sea ice, vegetation and land ice. A thorough multi-model-data comparison is essential to assess the ability of climate models to resolve interglacial temperature trends and to help in understanding the recorded climatic signal and the underlying climate dynamics. We present the first multi-model-data comparison of transient millennial-scale temperature changes through two intervals of the Present Interglacial (PIG; 8-1.2 ka) and the Last Interglacial (LIG; 123-116.2 ka) periods. We include temperature trends simulated by 9 different climate models, alkenone-based temperature reconstructions from 117 globally distributed locations (about 45% of them within the LIG) and 12 ice-core-based temperature trends from Greenland and Antarctica (50% of them within the LIG). The definitions of these specific interglacial intervals enable a consistent inter-comparison of the two intervals because both are characterised by minor changes in atmospheric greenhouse gas concentrations and more importantly by insolation trends that show clear similarities. Our analysis shows that in general the reconstructed PIG and LIG Northern Hemisphere mid-to-high latitude cooling compares well with multi-model, mean-temperature trends for the warmest months and that these cooling trends reflect a linear response to the warmest-month insolation decrease over the interglacial intervals. The most notable exception is the strong LIG cooling trend reconstructed from Greenland ice cores that is not simulated by any of the models. A striking model-data mismatch is found for both the PIG and the LIG over large parts of the mid-to-high latitudes of the Southern Hemisphere where the data depicts negative temperature trends that are not in agreement with near zero trends in the simulations. In this area, the positive local summer insolation trend is counteracted in climate models by an enhancement of the Southern Ocean summer sea-ice cover and/or an increase in Southern Ocean upwelling. If the general picture emerging from reconstructions is realistic, then the model-data mismatch in mid and high Southern Hemisphere latitudes implies that none of the models is able to resolve the correct balance of these feedbacks, or, alternatively, that interglacial Southern Hemisphere temperature trends are driven by mechanisms which are not included in the transient simulations, such as changes in the Antarctic ice sheet or meltwater-induced changes in the overturning circulation

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: Surface melting of the Greenland Ice Sheet contributes a large amount to current and future sea level rise. Increased surface melt may lower the reflectivity of the ice sheet surface and thereby increase melt rates: the so-called melt–albedo feedback describes this self-sustaining increase in surface melting. In order to test the effect of the melt– albedo feedback in a prognostic ice sheet model, we imple- ment dEBM-simple, a simplified version of the diurnal En- ergy Balance Model dEBM, in the Parallel Ice Sheet Model (PISM). The implementation includes a simple representation of the melt–albedo feedback and can thereby replace the positive-degree-day melt scheme. Using PISM-dEBM- simple, we find that this feedback increases ice loss through surface warming by 60 % until 2300 for the high-emission scenario RCP8.5 when compared to a scenario in which the albedo remains constant at its present-day values. With an increase of 90 % compared to a fixed-albedo scenario, the effect is more pronounced for lower surface warming under RCP2.6. Furthermore, assuming an immediate darkening of the ice surface over all summer months, we estimate an up- per bound for this effect to be 70 % in the RCP8.5 scenario and a more than 4-fold increase under RCP2.6. With dEBM- simple implemented in PISM, we find that the melt–albedo feedback is an essential contributor to mass loss in dynamic simulations of the Greenland Ice Sheet under future warming.

Description: It is virtually certain that Antarctica’s contribution to sea-level rise will increase with future warming, although competing mass balance processes hamper accurate quantification of the exact magnitudes. Today, ocean-induced melting un- derneath the floating ice shelves dominates mass losses, but melting at the surface will gain importance as global warming continues. Meltwater at the ice surface has crucial implications for the ice sheet’s stability, as it increases the risk of hydrofrac- turing and ice-shelf collapse that could cause enhanced glacier outflow into the ocean. Simultaneously, positive feedbacks5 between ice and atmosphere can accelerate mass losses and increase the ice sheet’s sensitivity to warming. However, due to long response times it may take hundreds to thousands of years until the ice sheet fully adjusts to the environmental changes. Therefore, ice sheet model simulations must be computationally fast and capture the relevant feedbacks, including the ones at the ice–atmosphere interface. Here we use the novel surface melt module dEBM-simple, coupled to the Parallel Ice Sheet Model (PISM), to estimate the impact of 21st-century atmospheric warming on Antarctic surface melt and ice dynamics. As an enhancement compared to the widely adopted positive degree-day (PDD) scheme, dEBM-simple includes an implicit diurnal cycle and computes melt not only from the temperature, but also from the influence of solar radiation and changes in ice albedo, thus accounting for the melt–albedo feedback. We calibrate PISM-dEBM-simple to reproduce historical and present-day Antarctic surface melt rates given by the regional climate model RACMO2.3p2 and use the calibrated model to assess the range of possible future surface melt trajectories under SSP5-8.5 warming projections until the year 2100. To investigate the committed impacts of the enhanced surface melting on the ice-sheet dynamics, we extend the simulations under fixed climatological conditions until the ice sheet has reached a state close to equilibrium with its environment. Our findings reveal a substantial surface melt-induced speed-up in ice flow associated with large-scale elevation reductions in sensitive ice-sheet regions, underscoring the critical role of self-reinforcing ice-sheet–atmosphere feedbacks on future mass losses and sea-level contribution from the Antarctic Ice Sheet on centennial to millennial timescales.