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

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

Global warming due to loss of large ice masses and Arctic summer sea ice

Several large-scale cryosphere elements such as the Arctic summer sea ice, the mountain glaciers, the Greenland and West Antarctic Ice Sheet have changed substantially during the last century due to anthropogenic global warming. However, the impacts of their possible future disintegration on global mean temperature (GMT) and climate feedbacks have not yet been comprehensively evaluated. Here, we quantify this response using an Earth system model of intermediate complexity. Overall, we find a median additional global warming of 0.43 °C (interquartile range: 0.39−0.46 °C) at a CO2 concentration of 400 ppm. Most of this response (55%) is caused by albedo changes, but lapse rate together with water vapour (30%) and cloud feedbacks (15%) also contribute significantly. While a decay of the ice sheets would occur on centennial to millennial time scales, the Arctic might become ice-free during summer within the 21st century. Our findings imply an additional increase of the GMT on intermediate to long time scales

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

Modeling the response of Greenland outlet glaciers to global warming using a coupled flow line-plume model

In recent decades, the Greenland Ice Sheet has experienced an accelerated mass loss, contributing to approximately 25 % of contemporary sea level rise (SLR). This mass loss is caused by increased surface melt over a large area of the ice sheet and by the thinning, retreat and acceleration of numerous Greenland outlet glaciers. The latter is likely connected to enhanced submarine melting that, in turn, can be explained by ocean warming and enhanced subglacial discharge. The mechanisms involved in submarine melting are not yet fully understood and are only simplistically incorporated in some models of the Greenland Ice Sheet. Here, we investigate the response of 12 representative Greenland outlet glaciers to atmospheric and oceanic warming using a coupled line–plume glacier–flow line model resolving one horizontal dimension. The model parameters have been tuned for individual outlet glaciers using present-day observational constraints. We then run the model from present to the year 2100, forcing the model with changes in surface mass balance and surface runoff from simulations with a regional climate model for the RCP8.5 scenario, and applying a linear ocean temperature warming with different rates of changes representing uncertainties in the CMIP5 model experiments for the same climate change scenario. We also use different initial temperature–salinity profiles obtained from direct measurements and from ocean reanalysis data. Using different combinations of submarine melting and calving parameters that reproduce the present-day state of the glaciers, we estimate uncertainties in the contribution to global SLR for individual glaciers. We also perform a sensitivity analysis of the three forcing factors (changes in surface mass balance, ocean temperature and subglacial discharge), which shows that the roles of the different forcing factors are diverse for individual glaciers. We find that changes in ocean temperature and subglacial discharge are of comparable importance for the cumulative contribution of all 12 glaciers to global SLR in the 21st century. The median range of the cumulative contribution to the global SLR for all 12 glaciers is about 18 mm (the glaciers' dynamic response to changes of all three forcing factors). Neglecting changes in ocean temperature and subglacial discharge (which control submarine melt) and investigating the response to changes in surface mass balance only leads to a cumulative contribution of 5 mm SLR. Thus, from the 18 mm we associate roughly 70 % with the glaciers' dynamic response to increased subglacial discharge and ocean temperature and the remaining 30 % (5 mm) to the response to increased surface mass loss. We also find a strong correlation (correlation coefficient 0.74) between present-day grounding line discharge and their future contribution to SLR in 2100. If the contribution of the 12 glaciers is scaled up to the total present-day discharge of Greenland, we estimate the midrange contribution of all Greenland glaciers to 21st-century SLR to be approximately 50 mm. This number adds to SLR derived from a stand-alone ice sheet model (880 mm) that does not resolve outlet glaciers and thus increases SLR by over 50 %. This result confirms earlier studies showing that the response of the outlet glaciers to global warming has to be taken into account to correctly assess the total contribution of Greenland to sea level change

Simulation of the future sea level contribution of Greenland with a new glacial system model

We introduce the coupled model of the Green- land glacial system IGLOO 1.0, including the polythermal ice sheet model SICOPOLIS (version 3.3) with hybrid dy- namics, the model of basal hydrology HYDRO and a param- eterization of submarine melt for marine-terminated outlet glaciers. The aim of this glacial system model is to gain a better understanding of the processes important for the future contribution of the Greenland ice sheet to sea level rise under future climate change scenarios. The ice sheet is initialized via a relaxation towards observed surface elevation, impos- ing the palaeo-surface temperature over the last glacial cycle. As a present-day reference, we use the 1961–1990 standard climatology derived from simulations of the regional atmo- sphere model MAR with ERA reanalysis boundary condi- tions. For the palaeo-part of the spin-up, we add the temper- ature anomaly derived from the GRIP ice core to the years 1961–1990 average surface temperature field. For our pro- jections, we apply surface temperature and surface mass bal- ance anomalies derived from RCP 4.5 and RCP 8.5 scenar- ios created by MAR with boundary conditions from simula- tions with three CMIP5 models. The hybrid ice sheet model is fully coupled with the model of basal hydrology. With this model and the MAR scenarios, we perform simulations to estimate the contribution of the Greenland ice sheet to future sea level rise until the end of the 21st and 23rd centuries. Fur- ther on, the impact of elevation–surface mass balance feed- back, introduced via the MAR data, on future sea level rise is inspected. In our projections, we found the Greenland ice sheet to contribute between 1.9 and 13.0 cm to global sea level rise until the year 2100 and between 3.5 and 76.4 cm until the year 2300, including our simulated additional sea level rise due to elevation–surface mass balance feedback. Translated into additional sea level rise, the strength of this feedback in the year 2100 varies from 0.4 to 1.7 cm, and in the year 2300 it ranges from 1.7 to 21.8 cm. Additionally, taking the Helheim and Store glaciers as examples, we inves- tigate the role of ocean warming and surface runoff change for the melting of outlet glaciers. It shows that ocean temper- ature and subglacial discharge are about equally important for the melting of the examined outlet glaciers

Global Tipping Points Report 2023: Ch1.5: Climate tipping point interactions and cascades.

This chapter reviews interactions between climate tipping systems and assesses the potential risk of cascading effects. After a definition of tipping system interactions, we map out the current state of the literature on specific interactions between climate tipping systems that may be important for the overall stability of the climate system. For this, we gather evidence from model simulations, observations and conceptual understanding, as well as archetypal examples of palaeoclimate reconstructions where propagating transitions were potentially at play. This chapter concludes by identifying crucial knowledge gaps in tipping system interactions that should be resolved in order to improve risk assessments of cascading transitions under future climate change scenarios

Climate tipping point interactions and cascades: A review

Climate tipping elements are large-scale subsystems of the Earth that may transgress critical thresholds (tipping points) under ongoing global warming, with substantial impacts on the biosphere and human societies. Frequently studied examples of such tipping elements include the Greenland Ice Sheet, the Atlantic Meridional Overturning Circulation (AMOC), permafrost, monsoon systems, and the Amazon rainforest. While recent scientific efforts have improved our knowledge about individual tipping elements, the interactions between them are less well understood. Also, the potential of individual tipping events to induce additional tipping elsewhere or stabilize other tipping elements is largely unknown. Here, we map out the current state of the literature on the interactions between climate tipping elements and review the influences between them. To do so, we gathered evidence from model simulations, observations, and conceptual understanding, as well as examples of paleoclimate reconstructions where multi-component or spatially propagating transitions were potentially at play. While uncertainties are large, we find indications that many of the interactions between tipping elements are destabilizing. Therefore, we conclude that tipping elements should not only be studied in isolation, but also more emphasis has to be put on potential interactions. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 ◦C or on shorter timescales if global warming surpassed 2.0 ◦C. At these higher levels of global warming, tipping cascades may then include fast tipping elements such as the AMOC or the Amazon rainforest. To address crucial knowledge gaps in tipping element interactions, we propose four strategies combining observation-based approaches, Earth system modeling expertise, computational advances, and expert knowledge