A global ocean general circulation model has been coupled with a dynamic thermodynamic sea-ice model. This model has been spun-up in a 1000 year integration using daily atmosphere model data. Main water masses and currents are reproduced as well as the seasonal characteristics of the ice cover of the Northern and Southern Hemispheres. Model results for the Southern Ocean, however, show the ice cover as too thin, and there are large permanent polynyas in the Weddell and Ross Seas. These polynyas are due to a large upward oceanic heat flux caused by haline rejection during the freezing of sea ice. Sensitivity studies were performed to test several ways of treating the sea-surface salinity and the rejected brine. The impact on the ice cover, water-mass characteristics, and ocean circulation are described.

A global coupled atmosphere-ocean-ice model is used to examine the interdependence among several components of the hydrologic cycle in the Arctic Ocean, including river discharge, sea-ice cover, and the flow of sea ice through Fram Strait. Since the ocean model has a free surface, fresh-water inflow from rivers is added directly to the ocean. The timing of the peak spring river flow depends on snowmelt runoff and its subsequent routing through the river system. Thermodynamic sea ice is included, and a new sea-iee advection scheme is described. The model’s river discharge affects salinity at the mouth of large rivers. The effect of the river discharge on sea-ice cover is not clear, either locally or at the basin scale. There is significant inter-annual variability of ice flow through Fram Strait, but the model’s flow is about half of that observed. The anomalous ice flow through Fram Strait is most highly correlated with the meridional wind stress. Potential implications for the “great salinity” anomaly are discussed.

Different vegetation models impact the atmospheric response of a regional climate model in different ways, and hence have an impact upon the ability of that model to match an observed climatology. Using a multivariate principal-component analysis, we investigate the relationships between several land-surface models (BATS, LSM) coupled to a regional climate model, and observed climate parameters over the North Slope of Alaska. In this application, annual cycle simulations at 20 km spatial resolution are compared with European Centre for Medium-Range Weather Forecasts (ECMWF) climatology. Initial results demonstrate broad agreement between all models; however, small-scale regional variations between land-surface models indicate the strengths and weaknesses of the land-surface treatments in a climate system model. Specifically, we found that the greater surface-moisture availability and temperature-dependent albedo formulation of the LSM model allow for a higher proportion of low-level cloud, and a later, more rapid transition from the winter to the summer regime. Crucial to this transition is the seasonal cycle of incoming solar radiation. These preliminary results indicate the importance of the land-surface hydrologic cycle in modelling the seasonal transitions.

During snowmelt over a continuous snow cover, the vertical turbulent exchanges of sensible and latent energy are influenced by regional air-mass characteristics, which exert a strong control on air temperature. In high-latitude sites, the melting surface rapidly becomes heterogeneous, with patches of snow and snow-free areas. Local advection occurs when near-surface air layers are warmed due to sensible heal flux from the snow-free areas, with the resulting heat transferred horizontally to adjacent snowpatches. This advection greatly increases the rate of snowmelt along the leading edges of the snowpatches. In order to estimate correctly the average melt rates of the snowpatches and the bulk energy balance of the entire landscape, it is necessary to estimate the local advection component. To date, few studies have dealt with this problem. This paper reports results from an Arctic tundra site located approximately 55 km northeast of Inuvik, Northwest Territories, Canada. The importance of local advection is estimated by comparing the sensible heat flux of the snowpatches to estimates of sensible heat without local advection. This latter term is derived from a relationship between upper air temperature and sensible heat flux over a continuous snow cover. This work has important implications for developing models that correctly represent the cryosphere of tundra regions, and in developing appropriate scaling techniques for heterogeneous landscapes.

The response of the Antarctic ice sheet to climate change over the next 500 years is calculated using the output of a transient-coupled ocean-atmosphere simulation assuming the atmospheric CO2 value increases up to three times present levels. The main effects on the ice sheet on this time-scale include increasing rates of accumulation, minimal surface melting, and basal melting of ice shelves. A semi-Lagrangian transport scheme for moisture was used to improve the model’s ability to represent realistic rates of accumulation under present-day conditions, and thereby increase confidence in the anomalies calculated under a warmer climate. The response of the Antarctic ice sheet to the warming is increased accumulation inland, offset by loss from basal melting from the floating ice, and increased ice flow near the grounding line. The preliminary results of this study show that the change to the ice-sheet balance for the transient-coupled model forcing amounted to a minimal sea-level contribution in the next century, but a net positive sea-level rise of 0.21 m by 500 years. This new result supercedes earlier results that showed the Antarctic ice sheet made a net negative contribution to sea-level rise over the next century. However, the amplitude of the sea-level rise is still dominated In the much larger contributions expected from thermal expansion of the ocean of 0.25 m for 100 years and 1.00 m for 500 years.

In the framework of the Paleoclimate Modelling Intercomparison Project (PMIP), simulations of the Last Glacial Maximum (LGM) have- been performed. More than 10 different atmospheric general circulation models (AGCMs) have been used with the same boundary conditions: sea-surface temperatures prescribed by CLIMAP (1981), ice-sheet reconstruction provided by Peltier (1994), change in insolation, and reduced CO2 content. One of the major questions is to investigate whether the simulations of the LGM are in equilibrium with the prescribed ice-sheet reconstruction. To answer this question, we have used two different approaches. First, we analyze the results of a sel of LGM simulations performed with different versions of the Laboratoire de Meteorolo-gie Dynamique (LMD) AGCM and study the hydrologic and snow- budgets over the Laurcntide and Fennoscandian ice sheets. Second, we use the AGCM outputs to force an ice-sheet model in order to investigate its ability to maintain the ice sheets as reconstructed by CLIMAP (1981) or Peltier (1994).

Mean oxygen-isotope ratio values relative to standard mean ocean water (δ18 O, in ‰) reported for 406 sites in Antarctica are compiled together with data on mean annual surface temperature, latitude, surface elevation, and mean annual shortest distance to open ocean denoted by the 20% sea-ice concentration boundary. Stepwise regression analyses with δ18O as the dependent variable are used as a model-building procedure based on statistical, rather than physical, criteria. Multivariate models sensitive to covariation between independent variables are defined using the whole dataset (N406 where N denotes the number of sites), as well as sub-sets for areas of conterminous grounded ice (N206) and ice shell (N110). The models show improvement over bivariate regression models. Distance to the open ocean enters all models at the second step. Inversions of the set and sub-set models applied to a database for 1351 gridpoint locations 100 km apart (it excludes the regions of Graham Land and eastern Palmer Land) are used to produce contoured distributions of δ18O. These may be used to assess the effects of atmospheric advection, as well as derive ice-flow adjustments for δ18O series obtained from deep-core or ablation-zone samples. Suggestions are made to improve model reliability.

A major component of the climate system on the 10 000-100 000 year time-scales is continental ice sheets, yet many of the mechanisms involved in the land-sea-ice processes that affect the ice sheets are poorly understood. In order to examine these processes in more detail, we have developed a coupled energy balance climate-thermodynamic sea-ice—continental-ice-sheet model (CCSLI model). This model includes a hydrologic cycle, a detailed surface energy and mass balance, a thermodynamic sea-ice model, and a zonally averaged dynamic ice-flow model with bedrock depression.

Because of the variety of space and time-scales inherent in such a model, we have asynchronously coupled the land—ice model to the other components of the model. In this paper the asynchronous coupling is described and sensitivity studies are presented that determine the values of the asynchronous coupling parameters. Model simulations using these values allow the model to run nearly ten times faster with minimal changes in the final state of the ice sheet.

Both observational studies and numerical experiments demonstrate the sensitivity of the atmosphere to variations in the extent and mass of snow cover. There is therefore a need for simple but realistic snow parameterizations in forecast and climate models. A new snow hydrology has recently been developed at Météo-France. This parameterization has been validated off-line against field measurements, as well as in a fully interactive numerical climate experiment. In this study, further tests were performed in stand-alone mode. The results indicate that the scheme is able to reproduce snow-cover evolution, both on local and global scales, and some directions to improve the parameterization further are suggested.

Crocus, a one-dimensional model of snow-cover stratigraphy and evolution, was developed by the Cenire d’Etudes de la Neige (CEN, Météo-France) and extensively validated in temperate Alpine conditions. We present here a study of Crocus’s ability to reproduce the characteristics of polar snow at the surface of ice sheets. Crocus simulates the evolution of the thermal and structural features of snow cover as a function of meteorological parameters at the snow-atmosphere interface. Only models can provide the necessary meteorologic at information with full ice-sheet spatial coverage, and with the temporal resolution needed by Crocus. Meteorological data have been extracted from the European Centre for Medium-Range Weather Forecasts (ECMWF) archives (analyses and short-term predictions), over the entire surface of Antarctica with a spatial resolution of 1.5°. Here, the ECMWF data from the South Pole are first compared with observations to check their quality. Then, 20 year simulations of snow covet are computed to test the sensitivity of Crocus to inaccuracies in the meteorological input. The simulated snow characteristics exhibit a strong sensitivity to air temperature, accumulation rate and the initial density of depositing snow. However, even with no major model adaptation to polar conditions, Crocus does reproduce a number of thermal and structural features of polar snow.

In situ measurements of ice stress were made on a multi-year floe in the Alaskan Beaufort Sea over a 6 month period, beginning in October 1993. The data suggest that, in this region of the Arctic during this experiment, there were two main sources of stress: a thermally induced stress caused by changes in air temperature, and a stress generated by ice motion. Due to the natural damping of the snow and ice above the sensor, the thermally-induced stresses are low frequency (order of days). Stresses associated with periods of ice motion have both a high-frequency (order of hours), and low-frequency, content. The relative significance of these sources of stress is seasonal, reflecting the changes in the strength and continuity of the pack.

Experiments with dynamic thermodynamic sea-ice models indicate a strong dependence of the net freezing rate, sea-ice transport and variability on dynamic model parameters. Although current dynamic—thermodynamic sea-ice models show relatively good agreement with observations, an optimization seems to be necessary, especially for the parameterizations of dynamic processes.

Presently, only a few coupled climate models use dynamic-thermodynamic sea-ice models. In order to promote, by means of coordinated numerical experiments, the development of an optimal sea-ice model for climate research, the Sea Ice Ocean Modelling Panel of the Arctic Climate System Study (ACSYS, a project of the World Climate Research Programme has initiated the Sea Ice Model Intercomparison Project (SIMIP). The first results from this model hierarchy approach are presented.

The emphasis of this paper is on the partitioning of solar energy in an open plane-parallel melt pond with a Lambertian bottom. Spectral radiative-energy fluxes into the meltwater and underlying ice ocean layers are calculated analytically as a function of pond-bottom spectral albedo, pond depth and illumination condition Albedo of the pond bottom is reconstructed from data on pond albedo and depth. Results of calculations are presented for melt ponds of comparatively high and comparatively low reflectivity for a broad range of pond depths and for various illumination conditions. In the 350–700 nm spectral band, spectrally averaged pond albedo and solar-energy inputs are a function of pond-bottom albedo, pond depth and illumination condition. In the 700–2400 nm spectral band, the partitioning of solar energy in melt ponds depends on pond depth and illumination condition only. The effect of uncertainty in specifying pond-bottom albedo on total energy input into the water layer is relatively small compared to that on spectrally averaged pond albedo and total energy input into the ice-ocean layer.

There are currently a variety of one- and two-dimensional sea-ice models being used for climate simulations and sensitivity studies. Though all the models can be timed to simulate current-day conditions to some degree of accuracy, the responses of each model to perturbations in forcing from the atmosphere or ocean are different. Thus, climate-change prediction depends on the choice of sea-ice model. In this study, the sensitivities of various sea-ice models to external heat-flux perturbations are examined in a systematic manner. Starting from similar baseline annual thicknesses, each model is subjected to an applied heat-flux perturbation to assess icemelt. Separate experiments are conducted to compare the response of each model to heat fluxes applied at the atmospheric and the oceanic interfaces. It is found that the magnitude of the heat-flux perturbation required to melt ice varies greatly among different models, with the largest difference arising between models that include ice dynamics vs those that do not. Most models show an asymmetry in the response to heat-flux perturbations applied at the top and bottom surfaces of the ice. This study has implications for the choice of sea-ice models used for climate-change simulations. It also gives insight to the accuracy required for observations and model simulations of the surface heat fluxes.

Many questions remain concerning whether or not an ice cap existed during the mid-Cretaceous period (120–90 Ma). Other than data and observations from ice-rafted materials, atmospheric general circulation models (AGCMs) may be appropriate tools to investigate whether changes in atmospheric composition, land-sea distribution, or oceanic circulation (used as boundary conditions to constrain the model), provide the climatic conditions that enable ice caps to be formed.

This study uses an AGCM developed by the Laboratoire de Météorologie Dynamique (LMD) to perform a set of numerical sensitivity experiments to investigate plate tectonics (land–sea distribution and orography), CO2 partial pressure in the atmosphere and changes in prescribed sea-surface temperatures. The main goals are to quantify the effect of each forcing factor on the increase of Northern Hemisphere high-latitude temperatures, and to investigate whether combining these factors produce temperatures that would allow the ice-sheet formation.

Global climate models have pointed to the polar regions as very sensitive areas in response to climate change. However, these models often do not contain representations of processes peculiar to the polar regions such as dynamic sea ice, permafrost, and Arctic stratus clouds. Further, global models do not have the resolution necessary to model accurately many of the important processes and feedbacks. Thus, there is a need for regional climate models of higher resolution. Our such model (ARCSy M) has been developed by A. Lynch and W. Chapman. This model incorporates the NCAR Regional Climate Model (RegCM2) with the addition of Flato–Hibler cavitating fluid sea-ice dynamics and Parkinson–Washington ice thermodynamic formulation. Recently work has been conducted to couple a mixed-layer ocean to the atmosphere–ice model, and a three-dimensional (3-D) dynamical ocean model, in this case the S-Coordinate Primitive Equation Model (SPEM), to the ice model. Simulations including oceanic circulation will allow investigations of the feedbacks involved in fresh-water runoff from sea-ice melt and sea-ice transport. Further, it is shown that the definition of the mixed-layer depth has significant impact on ice thermodynamics.

Mean values of the oxygen-isotope ratio relative to standard mean ocean water (δ18O, in ‰) reported for 46 sites on the Greenland ice sheet are compiled together with data on mean annual surface temperature, latitude, δ18O elevation, and mean annual shortest distance to the open ocean denoted by the 10% sea-ice concentration boundary. Stepwise regression analyses, with δ18O as the dependent variable, define two robust models. In the forward mode at the 99.9% confidence level, only temperature enters the model. In the backward mode at the 95% confidence level, only temperature, latitude and distance to the open ocean remain in the model. Inversions of the models on the basis of 160 gridpoint locations 100 km apart in the area delimited by the surface equilibrium line produce four contoured distributions of δ18O. Two distributions are based on the bivarrate model and two on the multivariate model. The second distribution for each model is obtained substituting mean annual surface-temperature values obtained from the Nimbus-7 Temperature Humidity Infrared Radiometer (THIR) database. All four distributions are considered valid, and differences between them are evaluated using contoured anomaly maps. It is suggested that the inversion of the multivariate model using THIR data provides the more reliable pattern for studies of atmospheric advection or for the derivation of ice-flow adjustments for δ18O series obtained from deep-core or ablation-zone sites.

A compilation of mean values of the oxygen-isotope ratio relative to standard mean ocean water (δ18O, in ‰) for 22 siIes representative of conditions in northeastern Canada is complemented with data on mean annual surface temperature, latitude, surface elevation, and mean annual shortest distance to open ocean denoted by the 10% sea-ice concentration boundary. Stepwise regression analysis is used to develop a multivariate model suitable to inter the distribution of δ18O in an area of complex topography and possibly mixed sourcing of advected water vapor. The best model is produced by a run in the backward mode at the 95% confidence level in which only temperature, latitude and distance to the open ocean remain in the model (the correlation coefficient is 0.915, the adjusted coefficient of determination is 0.809, the root mean square residual is 1.62). This model is similar to the best δ18O predictive model derived elsewhere for Greenland, suggesting a common principal source of advected moisture.

Seasonal variations of water-balance components at an experimental watershed were measured for three hydrologic years. Snowfall accounts for 47% of the annual precipitation, and snowmelt runoff comprises 45% of the total runoff. Evaporation changed markedly during the season; it increased during May to August, decreased in September and October, and was negligibly small during the period of snow cover in winter. Losses due to evaporation reached half of the precipitation during summer, and total loss is about 26 % of the annual precipitation.

A conceptual precipitation–runoff model (HYCYMODEL) is used to simulate the daily runoff from the 67% glacierized Lirung basin (16% of which is covered by debris). The average thermal resistance of the debris cover of the Lrung Glacier has been estimated from the surface temperature of the debris, which was obtained from Landsat 5 (TM Band 6) images. This enabled calculation of the melt rate of the debris-covered area of the glacier using meteorological data collected at a nearby weather station. The calculated discharge results are roughly compatible with the observed daily discharges.