The importance of snow albedo for ice sheet evolution over the last glacial cycle

The surface energy and mass balance of ice sheets strongly depends on the amount of solar radiation absorbed at the surface, which is mainly controlled by the albedo of snow and ice. Here, using an Earth system model of intermediate complexity, we explore the role played by surface albedo for the simulation of glacial cycles. We show that the evolution of the Northern Hemisphere ice sheets over the last glacial cycle is very sensitive to the representation of snow albedo in the model. It is well known that the albedo of snow depends strongly on snow grain size and the content of light-absorbing impurities. Excluding either the snow aging effect or the dust darkening effect on snow albedo leads to an excessive ice build-up during glacial times and consequently to a failure in simulating deglaciation. While the effect of snow grain growth on snow albedo is well constrained, the albedo reduction due to the presence of dust in snow is much more uncertain because the light-absorbing properties of dust vary widely as a function of dust mineral composition. We also show that assuming slightly different optical properties of dust leads to very different ice sheet and climate evolutions in the model. Conversely, ice sheet evolution is less sensitive to the choice of ice albedo in the model. We conclude that a proper representation of snow albedo is a fundamental prerequisite for a successful simulation of glacial cycles

The importance of snow albedo for ice sheet evolution over the last glacial cycle

The surface energy and mass balance of ice sheets strongly depends on the amount of solar radiation absorbed at the surface, which is mainly controlled by the albedo of snow and ice. Here, using an Earth system model of intermediate complexity, we explore the role played by surface albedo for the simulation of glacial cycles. We show that the evolution of the Northern Hemisphere ice sheets over the last glacial cycle is very sensitive to the representation of snow albedo in the model. It is well known that the albedo of snow depends strongly on snow grain size and the content of light-absorbing impurities. Excluding either the snow aging effect or the dust darkening effect on snow albedo leads to an excessive ice build-up during glacial times and consequently to a failure in simulating deglaciation. While the effect of snow grain growth on snow albedo is well constrained, the albedo reduction due to the presence of dust in snow is much more uncertain because the light-absorbing properties of dust vary widely as a function of dust mineral composition. We also show that assuming slightly different optical properties of dust leads to very different ice sheet and climate evolutions in the model. Conversely, ice sheet evolution is less sensitive to the choice of ice albedo in the model. We conclude that a proper representation of snow albedo is a fundamental prerequisite for a successful simulation of glacial cycles

SEMIC: an efficient surface energy and mass balance model applied to the Greenland ice sheet

We present SEMIC, a Surface Energy and Mass balance model of Intermediate Complexity for snow-and ice-covered surfaces such as the Greenland ice sheet. SEMIC is fast enough for glacial cycle applications, making it a suitable replacement for simpler methods such as the positive degree day (PDD) method often used in ice sheet modelling. Our model explicitly calculates the main processes involved in the surface energy and mass balance, while maintaining a simple interface and requiring minimal data input to drive it. In this novel approach, we parameterise diurnal temperature variations in order to more realistically capture the daily thaw-freeze cycles that characterise the ice sheet mass balance. We show how to derive optimal model parameters for SEMIC specifically to reproduce surface characteristics and day-to-day variations similar to the regional climate model MAR (Modele Atmospherique Regional, version 2) and its incorporated multilayer snowpack model SISVAT (Soil Ice Snow Vegetation Atmosphere Transfer). A validation test shows that SEMIC simulates future changes in surface temperature and surface mass balance in good agreement with the more sophisticated multilayer snowpack model SISVAT included in MAR. With this paper, we present a physically based surface model to the ice sheet modelling community that is general enough to be used with in situ observations, climate model, or reanalysis data, and that is at the same time computationally fast enough for long-term integrations, such as glacial cycles or future climate change scenarios

The impact of the temperature-CO2 decoupling on the state-dependency of paleo climate sensitivity during the late Pleistocene

Climate change projections for the future are uncertain, also due to inter-model differences. The application of these models to paleo times, which can be constrained by reconstructions, is therefore essential, not only to gain a better understanding of past climate changes, but also for model validation purposes. In this respect both data- and model-based approaches have been used to generate time series of global temperature changes, ∆Tg. The ratio of ∆Tg over radiative forcing, ∆R, defines the specific equilibrium climate sensitivity S, and has been suggested to be state-dependent, potentially increasing towards warming climates, and therefore suggesting climate sensitivity for the future to be at the upper end of the range of published results (Köhler et al., 2015, 2017). Here we reanalyse existing time series of ∆Tg and ∆R for the last 800,000 years and show that this proposed state-dependency of S is only found if ∆Tg is based on data (reconstructions), and not if ∆Tg is based on models (simulations). We furthermore identify that in data-based reconstructions ∆Tg is decoupled from atmospheric CO2 predominantely during times of decreasing obliquity (identical to periods of land-ice sheet growth and sea level fall), while in model simulations ∆Tg and CO2 vary in phase throughout. This multi-millennial decoupling of CO2 and temperature has been suggested to be partially caused by a sea level-induced surge in magma and CO2 fluxes from oceanic hotspot volcanoes and mid ocean ridges (Hasenclever et al., 2017). The neglection of these feedbacks between the solid Earth and the climate system in recent Earth system models is partly responsible for the data/model misfit, and illustrates our current limitation in the model-based interpretation of the paleo records. Paleo-based estimates of S might be restricted to data without this ∆Tg-CO2-decoupling leading to a 20% smaller quantification of S for interglacial conditions of the late Pleistocene

Simulation of climate, ice sheets and CO2 evolution during the last four glacial cycles with an Earth system model of intermediate complexity

In spite of significant progress in paleoclimate reconstructions and modelling of different aspects of the past glacial cycles, the mechanisms which transform regional and seasonal variations in solar insolation into long-term and global-scale glacial–interglacial cycles are still not fully understood – in particular, in relation to CO2 variability. Here using the Earth system model of intermediate complexity CLIMBER-2 we performed simulations of the co-evolution of climate, ice sheets, and carbon cycle over the last 400000 years using the orbital forcing as the only external forcing. The model simulates temporal dynamics of CO2, global ice volume, and other climate system characteristics in good agreement with paleoclimate reconstructions. These results provide strong support for the idea that long and strongly asymmetric glacial cycles of the late Quaternary represent a direct but strongly nonlinear response of the Northern Hemisphere ice sheets to orbital forcing. This response is strongly amplified and globalised by the carbon cycle feedbacks. Using simulations performed with the model in different configurations, we also analyse the role of individual processes and sensitivity to the choice of model parameters. While many features of simulated glacial cycles are rather robust, some details of CO2 evolution, especially during glacial terminations, are sensitive to the choice of model parameters. Specifically, we found two major regimes of CO2 changes during terminations: in the first one, when the recovery of the Atlantic meridional overturning circulation (AMOC) occurs only at the end of the termination, a pronounced overshoot in CO2 concentration occurs at the beginning of the interglacial and CO2 remains almost constant during the interglacial or even declines towards the end, resembling Eemian CO2 dynamics. However, if the recovery of the AMOC occurs in the middle of the glacial termination, CO2 concentration continues to rise during the interglacial, similar to the Holocene. We also discuss the potential contribution of the brine rejection mechanism for the CO2 and carbon isotopes in the atmosphere and the ocean during the past glacial termination

PALADYN v1.0, a comprehensive land surface–vegetation–carbon cycle model of intermediate complexity

PALADYN is presented; it is a new comprehensive and computationally efficient land surface–vegetation–carbon cycle model designed to be used in Earth system models of intermediate complexity for long-term simulations and paleoclimate studies. The model treats in a consistent manner the interaction between atmosphere, terrestrial vegetation and soil through the fluxes of energy, water and carbon. Energy, water and carbon are conserved. PALADYN explicitly treats permafrost, both in physical processes and as an important carbon pool. It distinguishes nine surface types: five different vegetation types, bare soil, land ice, lake and ocean shelf. Including the ocean shelf allows the treatment of continuous changes in sea level and shelf area associated with glacial cycles. Over each surface type, the model solves the surface energy balance and computes the fluxes of sensible, latent and ground heat and upward shortwave and longwave radiation. The model includes a single snow layer. Vegetation and bare soil share a single soil column. The soil is vertically discretized into five layers where prognostic equations for temperature, water and carbon are consistently solved. Phase changes of water in the soil are explicitly considered. A surface hydrology module computes precipitation interception by vegetation, surface runoff and soil infiltration. The soil water equation is based on Darcy's law. Given soil water content, the wetland fraction is computed based on a topographic index. The temperature profile is also computed in the upper part of ice sheets and in the ocean shelf soil. Photosynthesis is computed using a light use efficiency model. Carbon assimilation by vegetation is coupled to the transpiration of water through stomatal conductance. PALADYN includes a dynamic vegetation module with five plant functional types competing for the grid cell share with their respective net primary productivity. PALADYN distinguishes between mineral soil carbon, peat carbon, buried carbon and shelf carbon. Each soil carbon type has its own soil carbon pools generally represented by a litter, a fast and a slow carbon pool in each soil layer. Carbon can be redistributed between the layers by vertical diffusion and advection. For the vegetated macro surface type, decomposition is a function of soil temperature and soil moisture. Carbon in permanently frozen layers is assigned a long turnover time which effectively locks carbon in permafrost. Carbon buried below ice sheets and on flooded ocean shelves is treated differently. The model also includes a dynamic peat module. PALADYN includes carbon isotopes 13C and 14C, which are tracked through all carbon pools. Isotopic discrimination is modelled only during photosynthesis. A simple methane module is implemented to represent methane emissions from anaerobic carbon decomposition in wetlands (including peatlands) and flooded ocean shelf. The model description is accompanied by a thorough model evaluation in offline mode for the present day and the historical perio

Comparison of surface mass balance of ice sheets simulated by positive-degree-day method and energy balance approach

Glacial cycles of the late Quaternary are controlled by the asymmetrically varying mass balance of continental ice sheets in the Northern Hemisphere. Surface mass balance is governed by processes of ablation and accumulation. Here two ablation schemes, the positive-degree-day (PDD) method and the surface energy balance (SEB) approach, are compared in transient simulations of the last glacial cycle with the Earth system model of intermediate complexity CLIMBER-2. The standard version of the CLIMBER-2 model incorporates the SEB approach and simulates ice volume variations in reasonable agreement with paleoclimate reconstructions during the entire last glacial cycle. Using results from the standard CLIMBER-2 model version, we simulated ablation with the PDD method in offline mode by applying different combinations of three empirical parameters of the PDD scheme. We found that none of the parameter combinations allow us to simulate a surface mass balance of the American and European ice sheets that is similar to that obtained with the standard SEB method. The use of constant values for the empirical PDD parameters led either to too much ablation during the first phase of the last glacial cycle or too little ablation during the final phase. We then substituted the standard SEB scheme in CLIMBER-2 with the PDD scheme and performed a suite of fully interactive (online) simulations of the last glacial cycle with different combinations of PDD parameters. The results of these simulations confirmed the results of the offline simulations: no combination of PDD parameters realistically simulates the evolution of the ice sheets during the entire glacial cycle. The use of constant parameter values in the online simulations leads either to a buildup of too much ice volume at the end of glacial cycle or too little ice volume at the beginning. Even when the model correctly simulates global ice volume at the last glacial maximum (21 ka), it is unable to simulate complete deglaciation during the Holocene. According to our simulations, the SEB approach proves superior for simulations of glacial cycles

The role of CO2 decline for the onset of Northern Hemisphere glaciation

The Pliocene–Pleistocene Transition (PPT), from around 3.2 to 2.5 million years ago (Ma), represented a major shift in the climate system and was characterized by a gradual cooling trend and the appearance of large continental ice sheets over northern Eurasia and North America. Paleo evidence indicates that the PPT was accompanied and possibly caused by a decrease in atmospheric CO2, but the temporal resolution of CO2 reconstructions is low for this period of time and uncertainties remain large. Therefore, instead of applying existent CO2 reconstructions we solved an ‘inverse’ problem by finding a schematic CO2 concentration scenario that allows us to simulate the temporal evolution of key climate characteristics in agreement with paleoclimate records. To this end, we performed an ensemble of transient simulations with an Earth system model of intermediate complexity from which we derived a best guess transient CO2 scenario for the interval from 3.2 to 2.4 Ma that gives the best fit between the simulated and reconstructed benthic δ18O and global sea surface temperature evolution. Our data-constrained CO2 scenarios are consistent with recent CO2 reconstructions and suggest a gradual CO2 decline from 375–425 to 275–300 ppm, between 3.2 and 2.4 Ma. In addition to a gradual decline, the best fit to paleoclimate data requires the existence of pronounced CO2 variability coherent with the 41-kyr (1 kyr = 1000 years) obliquity cycle. In our simulations the long-term CO2 decline is accompanied by a relatively abrupt intensification of Northern Hemisphere glaciation at around 2.7 Ma. This is the result of a threshold behaviour of the ice sheets response to gradual CO2 decrease and orbital forcing. The simulated Northern Hemisphere ice sheets during the early Pleistocene glacial cycles reach a maximum volume equivalent to a sea level drop of about 40 m. Both ice volume and benthic δ18O are dominated by 41-kyr cyclicity. Our simulations suggest that before 2.7 Ma Greenland was ice free during summer insolation maxima and only partly ice covered during periods of minimum summer insolation. A fully glaciated Greenland comparable to its present-day ice volume is modelled only during glacial maxima after 2.7 Ma and more continuously after 2.5 Ma

Nonlinear climate sensitivity and its implications for future greenhouse warming

Global mean surface temperatures are rising in response to anthropogenic greenhouse gas emissions. The magnitude of this warming at equilibrium for a given radiative forcing—referred to as specific equilibrium climate sensitivity (S)—is still subject to uncertainties. We estimate global mean temperature variations and S using a 784,000-year-long field reconstruction of sea surface temperatures and a transient paleoclimate model simulation. Our results reveal that S is strongly dependent on the climate background state, with significantly larger values attained during warm phases. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, we find that the range of paleo-based estimates of Earth’s future warming by 2100 CE overlaps with the upper range of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Furthermore, we find that within the 21st century, global mean temperatures will very likely exceed maximum levels reconstructed for the last 784,000 years. On the basis of temperature data from eight glacial cycles, our results provide an independent validation of the magnitude of current CMIP5 warming projections

Nonlinear climate sensitivity and its implications for future greenhouse warming

Global mean surface temperatures are rising in response to anthropogenic greenhouse gas emissions. The magnitude of this warming at equilibrium for a given radiative forcing-referred to as specific equilibrium climate sensitivity (S)-is still subject to uncertainties. We estimate global mean temperature variations and S using a 784,000-year-long field reconstruction of sea surface temperatures and a transient paleoclimate model simulation. Our results reveal that S is strongly dependent on the climate background state, with significantly larger values attained during warm phases. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, we find that the range of paleo-based estimates of Earth's future warming by 2100 CE overlaps with the upper range of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Furthermore, we find that within the 21st century, global mean temperatures will very likely exceed maximum levels reconstructed for the last 784,000 years. On the basis of temperature data from eight glacial cycles, our results provide an independent validation of the magnitude of current CMIP5 warming projections