Greenland surface mass balance simulated by a regional climate model and comparison with satellite-derived data in 1990–1991

The 1990 and 1991 ablation seasons over Greenland are simulated with a coupled atmosphere-snow regional climate model with a 25-km horizontal resolution. The simulated snow water content allows a direct comparison with the satellite-derived melt signal. The model is forced with 6-hourly ERA-40 reanalysis at its boundaries. An evaluation of the simulated precipitation and a comparison of the modelled melt zone and the surface albedo with remote sensing observations are presented. Both the distribution and quantity of the simulated precipitation agree with observations from coastal weather stations, estimates from other models and the ERA-40 reanalysis. There are overestimations along the steep eastern coast, which are most likely due to the “topographic barrier effect”. The simulated extent and time evolution of the wet snow zone compare generally well with satellite-derived data, except during rainfall events on the ice sheet and because of a bias in the passive microwave retrieved melt signal. Although satellite-based surface albedo retrieval is only valid in the case of clear sky, the interpolation and the correction of these data enable us to validate the simulated albedo on the scale of the whole Greenland. These two comparisons highlight a large sensitivity of the remote sensing observations to weather conditions. Our high-resolution climate model was used to improve the retrieval algorithms by taking more fully into account the atmosphere variability. Finally, the good agreement of the simulated melting surface with the improved satellite signal allows a detailed estimation of the melting volume from the simulation.     

Simulation of the Atlantic meridional overturning circulation in an atmosphere–ocean global coupled model. Part I: a mechanism governing the variability of ocean convection in a preindustrial experiment

A preindustrial climate experiment was conducted with the third version of the CNRM global atmosphere–ocean–sea ice coupled model (CNRM-CM3) for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4). This experiment is used to investigate the main physical processes involved in the variability of the North Atlantic ocean convection and the induced variability of the Atlantic meridional overturning circulation (MOC). Three ocean convection sites are simulated, in the Labrador, Irminger and Greenland–Iceland–Norwegian (GIN) Seas in agreement with observations. A mechanism linking the variability of the Arctic sea ice cover and convection in the GIN Seas is highlighted. Contrary to previous suggested mechanisms, in CNRM-CM3 the latter is not modulated by the variability of freshwater export through Fram Strait. Instead, the variability of convection is mainly driven by the variability of the sea ice edge position in the Greenland Sea. In this area, the surface freshwater balance is dominated by the freshwater input due to the melting of sea ice. The ice edge position is modulated either by northwestward geostrophic current anomalies or by an intensification of northerly winds. In the model, stronger than average northerly winds force simultaneous intense convective events in the Irminger and GIN Seas. Convection interacts with the thermohaline circulation on timescales of 5–10 years, which translates into MOC anomalies propagating southward from the convection sites.     

Snowpack model estimates of the mass balance of the Greenland ice sheet and its changes over the twentyfirst century

The performance of a snow cover model in capturing the ablation on the Greenland ice sheet is evaluated. This model allows an explicit calculation of the formation of melt water, of the fraction of melt water which re-freezes, and of runoff in the ablation region. The input climate variables to the snowpack model come from two climate models. While the higher resolution general circulation model (ECHAM 4), is closest to observations in its estimate of accumulation, it fails to give accurate results in its predictions of runoff, primarily in the southern half of the ice sheet. The two-dimensional low-resolution climate model (MIT 2D LO) produces estimates of runoff from the Greenland ice sheet within the range of uncertainty of the Inter governmental Panel on Climate Change (IPCC1) 1995 estimates. Both models reproduce some of the characteristics of the extent of the wet snow zone observed with satellite remote sensing; the MIT model is closer to observations in terms of areal extent and intensity of the melting in the southern half of the ice-sheet in July and August while the ECHAM model reproduces melting in the northern half of the ice sheet well. Changes in runoff from Greenland and Antarctica are often cited as one of the major concerns linked to anthropogenic changes in climate. Because it is based on physical principles and relies on the surface energy balance as input, the snow cover model can respond to the current climatic forcing as well as to future changes in climate on the century time scale without the limitations inherent in empirical parametrizations. For a reference climate scenario similar to the IPCC's IS92a, the model projects that the Greenland ice sheet does not contribute significantly to changes in the level of the ocean over the twenty-first century. Increases in accumulation over the central portion of the ice sheet offset most of the increase in melting and runoff, which takes place along the margins of the ice sheet. The range of uncertainty in the predictions of sea-level rise is estimated by repeating the calculation with the MIT model for seven climate change scenarios. The range is –0.5 to 1.7 cm.     

The Impact of Sediment-Laden Snow and Sea Ice in the Arctic on Climate

Sea ice formed over shallow Arctic shelves often entrains sediments resuspended from the sea floor. Some of this sediment-laden ice advects offshore into the Transpolar Drift Stream and the Beaufort Gyre of the Arctic Basin. Through the processes of seasonal melting at the top surface, and the freezing of clean ice on the bottom surface, these sediments tend, over time, to concentrate at the top of the ice where they can affect the surface albedo, and thus the absorbed solar radiation, when the ice is snow free. Similarly, wind-blown dust can reduce the albedo of snow. The question that is posed by this study is what is the impact of these sediments on the seasonal variation of sea ice, and how does it then affect climate? Experiments were conducted with a coupled energy balance climate-thermodynamic sea ice model to examine the impact of including sediments in the sea ice alone and in the sea ice and overlying snow. The focus of these experiments was the impact of the radiative and not the thermal properties of the sediments. The results suggest that if sea ice contains a significant amount of sediments which are covered by clean snow, there is only a small impact on the climate system. However, if the snow also contains significant sediments the impact on sea ice thickness and surface air temperature is much more significant.     

Climate sensitivity studies of the Greenland ice sheet using satellite AVHRR,SMMR, SSM/I and in situ data

Summary The feasibility of using satellite data for climate research over the Greenland ice sheet is discussed. In particular, we demonstrate the usefulness of Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) and Global Area Coverage (GAC) data for narrow-band albedo retrieval. Our study supports the use of lower resolution AVHRR (GAC) data for process studies over most of the Greenland ice sheet. Based on LAC data time series analysis, we can resolve relative albedo changes on the order of 2–5%. In addition, we examine Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) passive microwave data for snow typing and other signals of climatological significance. Based on relationships between in situ measurements and horizontally polarized 19 and 37 GHz observations, wet snow regions are identified. The wet snow regions increase in aerial percentage from 9% of the total ice surface in June to a maximum of 26% in August 1990. Furthermore, the relationship between brightness temperatures and accumulation rates in the northeastern part of Greenland is described. We found a consistent increase in accumulation rate for the northeastern part of the ice sheet from 1981 to 1986.With 16 Figures     

The effect of snow on Antarctic sea ice simulations in a coupled atmosphere-sea ice model

 The effect of a snow cover on sea ice accretion and ablation is estimated based on the ‘zero-layer’ version sea ice model of Semtner, and is examined using a coupled atmosphere-sea ice model including feedbacks and ice dynamics effects. When snow is disregarded in the coupled model the averaged Antarctic sea ice becomes thicker. When only half of the snowfall predicted by the atmospheric model is allowed to land on the ice surface sea ice gets thicker in most of the Weddell and Ross Seas but thinner in East Antarctic in winter, with the average slightly thicker. When twice as much snowfall as predicted by the atmospheric model is assumed to land on the ice surface sea ice also gets much thicker due to the large increase of snow-ice formation. These results indicate the importance of the correct simulation of the snow cover over sea ice and snow-ice formation in the Antarctic. Our results also illustrate the complex feedback effects of the snow cover in global climate models. In this study we have also tested the use of a mean value of 0.16 Wm^-1 K^-1 instead of 0.31 for the thermal conductivity of snow in the coupled model, based on the most recent observations in the eastern Antarctic and Bellingshausen and Amundsen Seas, and have found that the sea ice distribution changes greatly, with the ice becoming much thinner by about 0.2 m in the Antarctic and about 0.4 m in the Arctic on average. This implies that the magnitude of the thermal conductivity of snow is of considerable importance for the simulation of the sea ice distribution. An appropriate value of the thermal conductivity of snow is as crucial as the depth of the snow layer and the snowfall rate in a sea ice model. The coupled climate models require accurate values of the effective thermal conductivity of snow from observations for validating the simulated sea ice distribution under the present climate conditions. Received: 20 November 1997/Accepted: 27 July 1998     

Past and future polar amplification of climate change: climate model intercomparisons and ice-core constraints

Climate model simulations available from the PMIP1, PMIP2 and CMIP (IPCC-AR4) intercomparison projects for past and future climate change simulations are examined in terms of polar temperature changes in comparison to global temperature changes and with respect to pre-industrial reference simulations. For the mid-Holocene (MH, 6,000 years ago), the models are forced by changes in the Earth’s orbital parameters. The MH PMIP1 atmosphere-only simulations conducted with sea surface temperatures fixed to modern conditions show no MH consistent response for the poles, whereas the new PMIP2 coupled atmosphere–ocean climate models systematically simulate a significant MH warming both for Greenland (but smaller than ice-core based estimates) and Antarctica (consistent with the range of ice-core based range). In both PMIP1 and PMIP2, the MH annual mean changes in global temperature are negligible, consistent with the MH orbital forcing. The simulated last glacial maximum (LGM, 21,000 years ago) to pre-industrial change in global mean temperature ranges between 3 and 7°C in PMIP1 and PMIP2 model runs, similar to the range of temperature change expected from a quadrupling of atmospheric CO₂ concentrations in the CMIP simulations. Both LGM and future climate simulations are associated with a polar amplification of climate change. The range of glacial polar amplification in Greenland is strongly dependent on the ice sheet elevation changes prescribed to the climate models. All PMIP2 simulations systematically underestimate the reconstructed glacial–interglacial Greenland temperature change, while some of the simulations do capture the reconstructed glacial–interglacial Antarctic temperature change. Uncertainties in the prescribed central ice cap elevation cannot account for the temperature change underestimation by climate models. The variety of climate model sensitivities enables the exploration of the relative changes in polar temperature with respect to changes in global temperatures. Simulated changes of polar temperatures are strongly related to changes in simulated global temperatures for both future and LGM climates, confirming that ice-core-based reconstructions provide quantitative insights on global climate changes. An erratum to this article can be found at     

Examining the impact of multiple climate forcings on simulated Southern Hemisphere climate variability

Climate Dynamics - The study examines the influence of external climate forcings, and atmosphere–ocean–sea–ice coupled interaction on the Southern Hemisphere (SH) atmospheric...     

A new snow cover fraction parametrization for the ECHAM4 GCM

 Snow cover fraction (SCF) has a significant influence on the surface albedo and thus on the radiation balance and surface climate. Long-term three dimensional simulations with general circulation models (GCMs) show that the SCF greatly affects the climate in the Northern Hemisphere. By means of both ground observations and remotely sensed data, several deficiencies in the SCF simulated by the current ECHAM4 GCM were identified: over mountainous areas a substantial overestimation in the SCF was found whereas flat areas showed a distinctly underestimated SCF. This work proposes a new parametrization of the SCF for use in GCMs. Evaluations illustrate that it is beneficial to distinguish between the following three terrains: (1) flat, non-forested areas, (2) mountainous regions and (3) forests. The modified SCF parametrization for flat, non-forested areas was derived by using global datasets of ground-based snow depth and remote sensing observations of snow cover data. A 3-dimensional ECHAM4 simulation showed that this modification raises the SCF by up to approximately 20%, mainly in areas with a relatively thin snow cover. The comparison between remotely sensed and simulated mean monthly surface albedo revealed a significant overestimation of the surface albedo in snow-covered mountainous areas. An extension of the current SCF parametrization in ECHAM4 to take into account mountain effects, based on the French climate model Arpège, yielded a close agreement with satellite-derived surface albedo. The adoption of the submodel for snow albedo, as used in the Canadian Land Surface Scheme (CLASS), combined with a newly developed simple snow interception model, demonstrated the ability to capture the main physical processes of snow-covered canopies, including the albedo. The validation of the new parametrization with Boreal Ecosystem-Atmosphere Study (BOREAS) field data showed that the modification is appropriate to capture the main features of the albedo over snow-covered forests during and after heavy snowfall events. Furthermore, the proposed modification has a beneficial impact on the delayed snow melt in spring, a well-known problem in many current GCMs: The simulated surface albedo over the boreal forests decreases by approximately 0.1 during winter and spring, which is in better agreement with ground-based observations. This induces a significant rise in the surface temperature over extended parts of Eurasia and North America in late spring, which subsequently yields a faster snowmelt and an accelerated retreat of the snow line. Received: 28 April 2000 / Accepted: 18 December 2000     

Simulation of the Indian monsoon using the RegCM3–ROMS regional coupled model

A regional coupled atmosphere–ocean model was developed to study the role of air–sea interactions in the simulation of the Indian summer monsoon. The coupled model includes the regional climate model (RegCM3) as atmospheric component and the regional ocean modeling system (ROMS) as oceanic component. The two-way coupled model system exchanges sea surface temperature (SST) from the ocean to the atmospheric model and surface wind stress and energy fluxes from the atmosphere to the ocean model. The coupled model is run for four years 1997, 1998, 2002 and 2003 and the results are compared with observations and atmosphere-only model runs employing Reynolds SSTs as lower boundary condition. It is found that the coupled model captures the main features of the Indian monsoon and simulates a substantially more realistic spatial and temporal distribution of monsoon rainfall compared to the uncoupled atmosphere-only model. The intraseasonal oscillations are also better simulated in the coupled model compared to the atmosphere-only model. These improvements are due to a better representation of the feedbacks between the SST and convection and highlight the importance of air–sea coupling in the simulation of the Indian monsoon.     

Assessment of GCM simulated snow albedo using direct observations

 Annual cycles of monthly albedos simulated with a general circulation model (GCM) are compared with surface observations. The data observed at 35 stations are retrieved from the Global Energy Balance Archive (GEBA) and drawn from the soil moisture and meteorological observations in the former Soviet Union. The model data are obtained with the ECHAM4 GCM in a ten-year simulation of the present-day climate at T106 resolution. The model calculated albedo values are modified before they are compared with the surface observations: They are interpolated to the stations and adjusted to account for altitude differences and fractional forest area. During the snow-free period, the model underestimates the albedo by up to 0.05 at the stations (with values between 0.2 and 0.25 measured over short grass) because the albedo for grassland is too low in the model. During the period with seasonal snow cover, the model underestimates the albedo by up to 0.2 at stations in Russia, Scandinavia and Canada, which experience severe winters. This underestimation is due to an oversimplified parameterization of the snow covered grid fraction and an inadequate linear relation between snow albedo and temperature. The derivative of albedo with respect to the forest fraction implemented in ECHAM is in line with the observations, although a small overestimation of the model’s gradient has been detected. Received: 3 July 1998 / Accepted: 24 December 1998     

Radiative effect of black carbon aerosol on seasonal variation in snow depth in the Northern-Hemisphere

In this research, we studied the effects of black carbon (BC) aerosol radiative forcing on seasonal variation in the Northern Hemisphere (NH) using numerical simulations with the NASA finite-volume General Circulation Model (fvGCM) forced with monthly varying three-dimensional aerosol distributions from the Goddard Ozone Chemistry Aerosol Radiation and Transport Model (GOCART). The results show that atmospheric warming due to black carbon aerosols subsequently warm the atmosphere and land surfaces, especially those over Eurasia. As a result, the snow depth in Eurasia was greatly reduced in late winter and spring, and the reduction in snow cover decreased the surface albedo. Our surface energy balance analysis shows that the surface warming due to aerosol absorption causes early snow melting and further increases surface-atmosphere warming through snow/ice albedo feedback. Therefore, BC aerosol forcing may be an important factor affecting the snow/ice albedo in the NH.     

The impact of dynamic sea-ice on the climatology and climate sensitivity of a GCM: a study of past, present, and future climates

 We assess two parametrisations of sea-ice in a coupled atmosphere–mixed layer ocean–sea-ice model. One parametrisation represents the thermodynamic properties of sea-ice formation alone (THERM), while the other also includes advection of the ice (DYN). The inclusion of some sea-ice dynamics improves the model's simulation of the present day sea-ice cover when compared to observations. Two climate change scenarios are used to investigate the effect of these different parametrisations on the model's climate sensitivity. The scenarios are the equilibrium response to a doubling of atmospheric CO₂ and the response to imposed glacial boundary conditions. DYN produces a smaller temperature response to a doubling of CO₂ than THERM. The temperature response of THERM is more similar to DYN in the glacial case than in the 2×CO₂ case which implies that the climate sensitivity of THERM and DYN varies with the nature of the forcing. The different responses can largely be explained by the different distribution of Southern Hemisphere sea-ice cover in the control simulations, with the inclusion of ice dynamics playing an important part in producing the differences. This emphasises the importance of realistically simulating the reference climatic state when attempting to simulate a climate change to a prescribed forcing. The simulated glacial sea-ice cover is consistent with the limited palaeodata in both THERM and DYN, but DYN simulates a more realistic present day sea-ice cover. We conclude that the inclusion of simple ice dynamics in our model increases our confidence in the simulation of the anomaly climate. Received: 24 May 2000 / Accepted: 25 October 2000     

Effects of a melted greenland ice sheet on climate, vegetation, and the cryosphere

This paper investigates the possible implications for the earth-system of a melting of the Greenland ice-sheet. Such a melting is a possible result of increased high latitude temperatures due to increasing anthropogenic greenhouse gas emissions. Using an atmosphere-ocean general circulation model (AOGCM), we investigate the effects of the removal of the ice sheet on atmospheric temperatures, circulation, and precipitation. We find that locally over Greenland, there is a warming associated directly with the altitude change in winter, and the altitude and albedo change in summer. Outside of Greenland, the largest signal is a cooling over the Barents sea in winter. We attribute this cooling to a decrease in poleward heat transport in the region due to changes to the time mean circulation and eddies, and interaction with sea-ice. The simulated climate is used to force a vegetation model and an ice-sheet model. We find that the Greenland climate in the absence of an ice sheet supports the growth of trees in southern Greenland, and grass in central Greenland. We find that the ice sheet is likely to regrow following a melting of the Greenland ice sheet, the subsequent rebound of its bedrock, and a return to present day atmospheric CO₂ concentrations. This regrowth is due to the high altitude bedrock in eastern Greenland which allows the growth of glaciers which develop into an ice sheet.     

Albedo of coastal landfast sea ice in Prydz Bay,Antarctica: Observations and parameterization

The snow/sea-ice albedo was measured over coastal landfast sea ice in Prydz Bay, East Antarctica(off Zhongshan Station)during the austral spring and summer of 2010 and 2011. The variation of the observed albedo was a combination of a gradual seasonal transition from spring to summer and abrupt changes resulting from synoptic events, including snowfall, blowing snow, and overcast skies. The measured albedo ranged from 0.94 over thick fresh snow to 0.36 over melting sea ice. It was found that snow thickness was the most important factor influencing the albedo variation, while synoptic events and overcast skies could increase the albedo by about 0.18 and 0.06, respectively. The in-situ measured albedo and related physical parameters(e.g., snow thickness, ice thickness, surface temperature, and air temperature) were then used to evaluate four different snow/ice albedo parameterizations used in a variety of climate models. The parameterized albedos showed substantial discrepancies compared to the observed albedo, particularly during the summer melt period, even though more complex parameterizations yielded more realistic variations than simple ones. A modified parameterization was developed,which further considered synoptic events, cloud cover, and the local landfast sea-ice surface characteristics. The resulting parameterized albedo showed very good agreement with the observed albedo.     

Modeled seasonality of glacial abrupt climate events

Greenland ice cores, as well as many other paleo-archives from the northern hemisphere, recorded a series of 25 warm interstadial events, the so-called Dansgaard-Oeschger (D-O) events, during the last glacial period. We use the three-dimensional coupled global ocean–atmosphere–sea ice model ECBILT-CLIO and force it with freshwater input into the North Atlantic to simulate abrupt glacial climate events, which we use as analogues for D-O events. We focus our analysis on the Northern Hemisphere. The simulated events show large differences in the regional and seasonal distribution of the temperature and precipitation changes. While the temperature changes in high northern latitudes and in the North Atlantic region are dominated by winter changes, the largest temperature increases in most other land regions are seen in spring. Smallest changes over land are found during the summer months. Our model simulations also demonstrate that the temperature and precipitation change patterns for different intensifications of the Atlantic meridional overturning circulation are not linear. The extent of the transitions varies, and local non-linearities influence the amplitude of the annual mean response as well as the response in different seasons. Implications for the interpretation of paleo-records are discussed.     

Long-term ice sheet–climate interactions under anthropogenic greenhouse forcing simulated with a complex Earth System Model

Several multi-century and multi-millennia simulations have been performed with a complex Earth System Model (ESM) for different anthropogenic climate change scenarios in order to study the long-term evolution of sea level and the impact of ice sheet changes on the climate system. The core of the ESM is a coupled coarse-resolution Atmosphere–Ocean General Circulation Model (AOGCM). Ocean biogeochemistry, land vegetation and ice sheets are included as components of the ESM. The Greenland Ice Sheet (GrIS) decays in all simulations, while the Antarctic ice sheet contributes negatively to sea level rise, due to enhanced storage of water caused by larger snowfall rates. Freshwater flux increases from Greenland are one order of magnitude smaller than total freshwater flux increases into the North Atlantic basin (the sum of the contribution from changes in precipitation, evaporation, run-off and Greenland meltwater) and do not play an important role in changes in the strength of the North Atlantic Meridional Overturning Circulation (NAMOC). The regional climate change associated with weakening/collapse of the NAMOC drastically reduces the decay rate of the GrIS. The dynamical changes due to GrIS topography modification driven by mass balance changes act first as a negative feedback for the decay of the ice sheet, but accelerate the decay at a later stage. The increase of surface temperature due to reduced topographic heights causes a strong acceleration of the decay of the ice sheet in the long term. Other feedbacks between ice sheet and atmosphere are not important for the mass balance of the GrIS until it is reduced to 3/4 of the original size. From then, the reduction in the albedo of Greenland strongly accelerates the decay of the ice sheet.     

Application of the Canadian regional climate model to the Laurentian great lakes region: Implementation of a lake model

Abstract

This study reports on the implementation of an interactive mixed‐layer/thermodynamic‐ice lake model coupled with the Canadian Regional Climate Model (CRCM). For this application the CRCM, which uses a grid mesh of 45 km on a polar stereographic projection, 10 vertical levels, and a timestep of 15 min, is nested with the second generation Canadian General Circulation Model (GCM) simulated output. A numerical simulation of the climate of eastern North America, including the Laurentian Great Lakes, is then performed in order to evaluate the coupled model. The lakes are represented by a “mixed layer” model to simulate the evolution of the surface water temperature, and a thermodynamic ice model to simulate evolution of the ice cover. The mixed‐layer depth is allowed to vary spatially. Lake‐ice leads are parametrized as a function of ice thickness based on observations. Results from a 5‐year integration show that the coupled CRCM/lake model is capable of simulating the seasonal evolution of surface temperature and ice cover in the Great Lakes. When compared with lake climatology, the simulated mean surface water temperature agrees within 0.12°C on average. The seasonal evolution of the lake‐ice cover is realistic but the model tends to underestimate the monthly mean ice concentration on average. The simulated winter lake‐induced precipitation is also shown, and snow accumulation patterns on downwind shores of the lakes are found to be realistic when compared with observations.     

Climate modification by future ice sheet changes and consequences for ice sheet mass balance

The future evolution of global ice sheets under anthropogenic greenhouse forcing and its impact on the climate system, including the regional climate of the ice sheets, are investigated with a comprehensive earth system model consisting of a coupled Atmosphere–Ocean General Circulation Model, a dynamic vegetation model and an ice sheet model. The simulated control climate is realistic enough to permit a direct coupling of the atmosphere and ice sheet components, avoiding the use of anomaly coupling, which represents a strong improvement with respect to previous modelling studies. Glacier ablation is calculated with an energy-balance scheme, a more physical approach than the commonly used degree-day method. Modifications of glacier mask, topographic height and freshwater fluxes by the ice sheets influence the atmosphere and ocean via dynamical and thermodynamical processes. Several simulations under idealized scenarios of greenhouse forcing have been performed, where the atmospheric carbon dioxide stabilizes at two and four times pre-industrial levels. The evolution of the climate system and the ice sheets in the simulations with interactive ice sheets is compared with the simulations with passively coupled ice sheets. For a four-times CO₂ scenario forcing, a faster decay rate of the Greenland ice sheet is found in the non-interactive case, where melting rates are higher. This is caused by overestimation of the increase in near-surface temperature that follows the reduction in topographic height. In areas close to retreating margins, melting rates are stronger in the interactive case, due to changes in local albedo. Our results call for careful consideration of the feedbacks operating between ice sheets and climate after substantial decay of the ice sheets.     

The effect of land surface changes on Eemian climate

Transient experiments for the Eemian (128–113 ky BP) were performed with a complex, coupled earth system model, including atmosphere, ocean, terrestrial biosphere and marine biogeochemistry. In order to investigate the effect of land surface parameters (background albedo, vegetation and tree fraction and roughness length) on the simulated changes during the Eemian, simulations with interactive coupling between climate and vegetation were compared with additional experiments in which these feedbacks were suppressed. The experiments show that the influence of land surface on climate is mainly caused by changes in the albedo. For the northern hemisphere high latitudes, land surface albedo is changed partially due to the direct albedo effect of the conversion of grasses into forest, but the indirect effect of forests on snow albedo appears to be the major factor influencing the total absorption of solar radiation. The Western Sahara region experiences large changes in land surface albedo due to the appearance of vegetation between 128 and 120 ky BP. These local land surface albedo changes can be as much as 20%, thereby affecting the local as well as the global energy balance. On a global scale, latent heat loss over land increases more than 10% for 126 ky BP compared to present-day.