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Melt ponds are pools of meltwater forming principally on Arctic sea ice during the melt season. The albedo of melt ponds is a key component of the surface energy balance. For this reason, various melt pond schemes have been developed for climate models. These schemes require assumptions on the physical processes governing melt ponds as well as a knowledge of the atmospheric state, which are not perfectly known. In this study, we investigate the effects of the sources of uncertainty from the prescribed atmospheric surface state, the melt pond scheme definition and the refreezing formulation of melt ponds on the simulated Arctic sea ice and melt pond properties with the NEMO-LIM3 ocean–sea ice general circulation model. We find that the simulated melt pond state is largely controlled by the freezing point of melt ponds. The representation of melt ponds is in better agreement with observations when using the freezing point of −0.15 ° C compared to the value of −2.00 ° C , in our model set-up. All the simulations feature positive trends in melt pond area fraction over the past decades. However, only 3 out of 8 simulations have significant positive trends in melt pond volume per sea ice area. This suggests an influence of the sea ice state for melt ponds over the last 30 years. Overall, we find that the simulated sea ice state, and in particular sea ice volume, is more affected by changes in the prescribed atmospheric forcing than by changes in the prescribed melt pond scheme or refreezing formulation. Including explicit melt pond schemes in large-scale sea-ice models offer the possibility to improve the representation of the surface energy balance in climate general circulation models. Our results underline that, in parallel to these efforts in model developments, improved estimates of surface atmospheric conditions will be required to achieve more realistic sea ice states.

Melt ponds appear during the Arctic summer on the sea ice cover when meltwater and liquid precipitation collect in the depressions of the ice surface. The albedo of the melt ponds is lower than that of surrounding ice and snow areas. Consequently, the melt ponds are an important factor for the ice-albedo feedback, a mechanism whereby a decrease in albedo results in greater absorption of solar radiation, further ice melt, and lower albedos To account for the effect of melt ponds on the climate, several numerical schemes have been introduced for Global Circulation Models. They can be classified into two groups. The first group makes use of an explicit relation to define the aspect ratio of the melt ponds. The scheme of Holland et al. (2012) uses a constant ratio of the melt pond depth to the fraction of sea ice covered by melt ponds. The second group relies on theoretical considerations to deduce the area and volume of the melt ponds. The scheme of Flocco et al. (2012) uses the ice thickness distribution to share the meltwater between the ice categories and determine the melt ponds characteristics.Despite their complexity, current melt pond schemes fail to agree on the trends in melt pond fraction of sea ice area during the last decades. The disagreement casts doubts on the projected melt pond changes. It also raises questions on the definition of the physical processes governing the melt ponds in the schemes and their sensitivity to atmospheric surface conditions.In this study, we aim at identifying 1) the conceptual difference of the aspect ratio definition in melt pond schemes; 2) the role of refreezing for melt ponds; 3) the impact of the uncertainties in the atmospheric reanalyses. To address these points, we have run the Louvain-la-Neuve Ice Model (LIM), part of the Nucleus for European Modelling of the Ocean (NEMO) version 3.6 along with two different atmospheric reanalyses as surface forcing sets. We used the reanalyses in association with Holland et al. (2012) and Flocco et al. (2012) melt pond schemes. We selected Holland et al. (2012) pond refreezing formulation for both schemes and tested two different threshold temperatures for refreezing. From the experiments, we describe the impact on Arctic sea ice and state the importance of including melt ponds in climate models. We attempt at disentangling the separate effects of the type of melt pond scheme, the refreezing mechanism, and the atmospheric surface forcing method, on the climate. We finally formulate a recommendation on the use of melt ponds in climate models.

Arctic sea ice is a major component of the Earth’s climate system and has been experiencing a drastic decline over the past decades, with important consequences regionally and globally. With the sustained warming of the Arctic, sea ice loss is expected to continue in the future. However, the estimation of its magnitude is model-dependent. As a result, the representation of sea ice in climate models requires further consideration. A major issue relates to the long-standing misrepresentation of snow properties on sea ice. However, the presence of snow strongly impacts sea ice growth and surface energy balance. Through its high albedo, snow reflects more solar radiation than bare sea ice does. When a snow cover is present, sea ice growth is reduced because snow is an effective insulator, with a thermal conductivity an order of magnitude lower than that of sea ice. Ocean circulation models usually use multiple layers to resolve sea ice thermodynamics but only one single layer for snow. Lecomte et al. (2013) developed a multilayer snow scheme for ocean circulation models and improved the snow depth distribution by considering the macroscopic effects of wind packing and redeposition. Since then, this snow scheme has been revisited and implemented in a more recent and much more robust NEMO-LIM version, using a simpler technical approach. In addition, new instrumental observations of snow thickness, distribution and density are available since these exploratory works. They are used in the current study to: 1) evaluate the performance of the multilayer snow scheme for sea ice in the NEMO-LIM3 model, and 2) investigate the climatic importance of this snow scheme. Here, we present results of simulations with a varying number of snow layers. By comparing these to the latest observational datasets, we recommend an optimum number of snow layers to be used in ocean circulation models in both hemispheres. Finally, we explore the impact of a few specific parameterizations of snow thermophysical properties on the representation of sea ice in climate models.

Driftwood is frequently used to estimate past changes of sea ice extent and circulation in the Arctic. Nevertheless, driftwood observations are difficult to interpret because of the potentially complex relation with climate change. In order to determine the origin of the observed changes, we built a driftwood transport model (DTM) simulating the driftwood trajectories from the boreal forest to Arctic coasts. The model is driven by three main variables, which are the sea ice velocity, concentration and the sea surface current velocity that can be derived from observations or climate model outputs (e.g. from a General Climate Model – GCM). Overall, the DTM model agrees with the observations, although this comparison needs to be taken with caution because of the sparse data and the uncertainties of driftwood provenance. Through simulations performed with the DTM model, we confirm the strong influence of the variability of the atmospheric circulation on the spatial driftwood distribution. Model simulations of the Mid-Holocene period driven by six GCMs show that small local changes in sea ice circulation – a westward shift in the Transpolar Drift and a reduced Beaufort Gyre during the Mid-Holocene compared to the present period – suffice to explain the driftwood landing change during the Mid-Holocene, with a non-negligible contribution from reduced sea ice concentration. Consequently, a change in driftwood deposit should not be directly interpreted as large modifications in atmospheric circulation and the complexity of the response of driftwood trajectories to past climate changes clearly highlights the interest of using a model to interpret driftwood records.

A one-dimensional snow–sea–ice model is used to simulate the evolution of temperature profiles in dry and wet snow over a diurnal cycle, at locations where associated observations collected during the Sea Ice Physics and Ecosystem eXperiment (SIPEX-II) are available. The model is used at two sites, corresponding to two of the field campaign׳s sea–ice stations (2 and 6), and under two configurations: dry and wet snow conditions. In the wet snow model setups, liquid water may refreeze internally into the snow. At station 6, this releases latent heat to the snow and results in temperature changes at the base of the snow pack of a magnitude comparing to the model-observation difference ( 1 – 2 ° C ) . As the temperature gradient across the snow is in turn weakened, the associated conductive heat flux through snow decreases. At station 2, internal refreezing also occurs but colder air temperatures and the competing process of strengthened heat conduction in snow concurrent to snow densification maintain a steady temperature profile. However, both situations share a common feature and show that the conductive heat flux through the snow may significantly be affected (by 10–20% in our simulations) as a result of the liquid water refreezing in snow, either through thermal conductivity enhancement or direct temperature gradient alteration. This ultimately gives motivation for further investigating the impacts of these processes on the sea–ice mass balance in the framework of global scale model simulations.

In late winter-early spring 2012, the second Sea Ice Physics and Ecosystems Experiment (SIPEX II) was conducted off Wilkes Land, East Antarctica, onboard R/V Aurora Australis. The sea-ice conditions were characterized by significantly thick first-year ice and snow, trapping the ship for about 10 days in the near coastal region. The deep snow cover was particularly remarkable, in that its average value of 0.45 m was almost three times that observed between 1992 and 2007 in the region. To reveal factors responsible, we used in situ observations and ERA-Interim reanalysis (1990–2012) to examine the relative contribution of the different components of the local-regional snow mass balance equation i.e., snow accumulation on sea ice, precipitation minus evaporation (P–E), and loss by (i) snow-ice formation and (ii) entering into leads due to drifting snow. Results show no evidence for significantly high P–E in the winter of 2012. Ice core analysis has shown that although the snow-ice layer was relatively thin, indicating less transformation from snow to snow-ice in 2012 as compared to measurements from 2007, the difference was not enough to explain the extraordinarily deep snow. Based on these results, we deduce that lower loss of snow into leads was probably responsible for the extraordinary snow in 2012. Statistical analysis and satellite images suggest that the reduction in loss of snow into leads is attributed to rough ice surface associated with active deformation processes and larger floe size due to sea-ice expansion. This highlights the importance of snow-sea ice interaction in determining the mean snow depth on Antarctic sea ice.

Snow is the most reflective, and also the most insulative, natural material on Earth. Consequently, it is an integral part of the sea-ice and climate systems. However, the spatial and temporal heterogeneities of snow pose challenges for observing, understanding and modelling those systems under anthropogenic warming. Here, we survey the snow–ice system, then provide recommendations for overcoming present challenges. These include: collecting process-oriented observations for model diagnostics and understanding snow–ice feedbacks, and improving our remote sensing capabilities of snow for monitoring large-scale changes in snow on sea ice. These efforts could be achieved through stronger coordination between the observational, remote sensing and modelling communities, and would pay dividends through distinct improvements in predictions of polar environments.

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range of feedbacks, offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes., Estimating the magnitude of radiative and non-radiative feedbacks is key for understanding the climate dynamics of polar regions. Here the authors propose an inclusive methodology to quantify the influence of all those feedbacks, stimulating more systematic analyses in observational and model ensembles.

Although atmospheric reanalyses are an extremely valuable tool to study the climate of polar regions, they suffer from large uncertainties in these data-poor areas. In this work, we examine how Antarctic sea ice biases in an ocean-sea ice model are related to these forcing uncertainties. Three experiments are conducted in which the NEMO-LIM model is driven by different atmospheric forcing sets. The minimum ice extent, the ice motion and the ice thickness are sensitive to the reanalysis chosen to drive the model, while the wintertime ice extent and inner pack concentrations are barely affected. The analysis of sea ice concentration budgets allows identifying the processes leading to differences between the experiments, and also indicates that large and similar errors compared to observations are present in all three cases. Our assessment of the influence of forcing inaccuracies on the simulated Antarctic sea ice allows disentangling two types of model biases: the ones that can be reduced thanks to better atmospheric forcings, and those that would require improvements of the physics of the ice or ocean model.

La notion de modernité est, selon Michel Foucault et Marcel Gauchet, intimement liée à l’idée d’une nouvelle forme de pouvoir. Alors que Foucault analyse les articulations des microphysiques du pouvoir, Gauchet formule une théorie du pouvoir en fonction d’un rapport à l’extériorité. Tous deux perçoivent l’asile comme l’un des lieux représentatifs par excellence de la forme moderne du pouvoir. Ce texte vise à montrer que le modèle de Gauchet permet de conserver l’apport de Foucault tout en lui conférant un sens nouveau.

Remotely sensed derivation of sea-ice thickness requires sea·ice density. Sea-ice density was estimated with three techniques during the second Sea Ice Physics and Ecosystem eXperimett (SIPEX-II, September-November 2012, East Antarctica). The sea ice was first-year highly deformed, mean thicknsss 1.2 m with layers, consistent with rafting, and 6-7/10 columnar ice and 3/10 granular ice. Ice density was found to be lower than values (900-920 kg m−3 used previously to derive ice thickness,, with columnar ice mean density of 870 kg m− 3. At two different ice stations the mean density of the ice was 800 kg m–3, the lower density reflecting a high percentage of porous granular ice at the second station. Error estimates for mass/volume and liquid/solid water methods are presented. With 0.1 m long, 0.1 m core samples, the error on individual density estimates is 28 kg m-3. Errors are larger for smaller machined blocks. Errors increase to 46 kg m-3 if the liquid/solid volume method is used. The mass/vouume method has a low bias due to brine drainage of at least 5%. Bulk densities estimated from ice and snow measurements along 100 m transects were high, and likely unrealistic as the assumption of isostatcc balance is not suitable over these length scales in deformed ice.

Sea ice cover and thickness have substantially decreased in the Arctic Ocean since the beginning of the satellite era. As a result, sea ice strength has been reduced, allowing more deformation and fracturing and leading to increased sea ice drift speed. The resulting increased sea ice export is thought to further lower sea ice concentration and thickness. We use the global ocean-sea ice NEMO-LIM3.6 model (Nucleus for European Modelling of the Ocean coupled to the Louvain-la-Neuve sea Ice Model), satellite and buoy observations, as well as reanalysis data over the period from 1979 to 2013 to study this positive feedback for the first time in such detail. Overall, the model agrees well with observations in terms of sea ice extent, concentration and thickness. Although the seasonal cycle of sea ice drift speed is reasonably well reproduced by the model, the recent positive trend in drift speed is weaker than observations in summer. NEMO-LIM3.6 is able to capture the relationships between sea ice drift speed, concentration and thickness in terms of seasonal cycle, with higher drift speed for both lower concentration and lower thickness, in agreement with observations. Sensitivity experiments are carried out by varying the initial ice strength and show that higher values of ice strength lead to lower sea ice thickness. We demonstrate that higher ice strength results in a more uniform sea ice thickness distribution, leading to lower heat conduction fluxes, which provide lower ice production, and thus lower ice thickness. This shows that the positive feedback between sea ice drift speed and strength is more than just dynamic, more complex than originally thought and that other processes are at play. The methodology proposed in this analysis provides a benchmark for a further model intercomparison related to the interactions between sea ice drift speed and strength.

Sea ice cover and thickness have substantially decreased in the Arctic Ocean since the beginning of the satellite era. As a result, sea ice strength has been reduced, allowing more deformation and fracturing and leading to increased sea ice drift speed. We use the version 3.6 of the global ocean–sea ice NEMO-LIM model (Nucleus for European Modelling of the Ocean coupled to the Louvain-la-Neuve sea Ice Model), satellite, buoy and submarine observations, as well as reanalysis data over the period from 1979 to 2013 to study these relationships. Overall, the model agrees well with observations in terms of sea ice extent, concentration and thickness. The seasonal cycle of sea ice drift speed is reasonably well reproduced by the model. NEMO-LIM3.6 is able to capture the relationships between the seasonal cycles of sea ice drift speed, concentration and thickness, with higher drift speed for both lower concentration and lower thickness, in agreement with observations. Model experiments are carried out to test the sensitivity of Arctic sea ice drift speed, thickness and concentration to changes in sea ice strength parameter P*. These show that higher values of P* generally lead to lower sea ice deformation and lower sea ice thickness, and that no single value of P* is the best option for reproducing the observed drift speed and thickness. The methodology proposed in this analysis provides a benchmark for a further model intercomparison related to the relationships between sea ice drift speed and strength, which is especially relevant in the context of the upcoming Coupled Model Intercomparison Project 6 (CMIP6). David Docquier and Antoine Barthélemy work on the PRIMAVERA project (PRocess-based climate sIMulation: AdVances in high-resolution modelling and European climate Risk Assessment), which is funded by the European Commission’s Horizon 2020 programme, grant agreement no. 641727. François Massonnet is funded by the Belgian Fonds National de la Recherche Scientifique (FNRS) and was funded by the Ministerio de Economía, Industria y Competitividad (MINECO). Neil F. Tandon is supported by the Canadian Sea Ice and Snow Evolution (CanSISE) Network. Olivier Lecomte is a research assistant within the Belgian FNRS. The present research benefited from computational resources made available on the Tier-1 supercomputer of the Fédération Wallonie-Bruxelles, infrastructure funded by the Walloon Region under the grant agreement no. 1117545. Computational resources have also been provided by the Consortium des Équipements de Calcul Intensif (CÉCI), funded by the Fonds de la Recherche Scientifique de Belgique (F.R.S.-FNRS) under grant no. 2.5020.11. We would like to thank Hugues Goosse, Martin Vancoppenolle, Jonathan Raulier and Véronique Dansereau for their very helpful comments regarding this study. We also acknowledge Pierre-Yves Barriat for his help in using computing resources at UCL and Damien François for his advice in improving Python scripts. Finally, we thank the editor Dirk Notz and the two anonymous reviewers for helping to improve the original paper.

Several processes have been hypothesized to explain the slight overall expansion of Antarctic sea ice over the satellite observation era, including externally forced changes in local winds or in the Southern Ocean’s hydrological cycle, as well as internal climate variability. Here, we show the critical influence of an ocean–sea-ice feedback. Once initiated by an external perturbation, it may be sufficient to sustain the observed sea-ice expansion in the Ross Sea, the region with the largest and most significant expansion. We quantify the heat trapped at the base of the ocean mixed layer and demonstrate that it is of the same order of magnitude as the latent heat storage due to the long-term changes in sea-ice volume. The evidence thus suggests that the recent ice coverage increase in the Ross Sea could have been achieved through a reorganization of energy within the near-surface ice-ocean system., The mechanisms responsible for the overall expansion of Antarctic sea-ice in recent decades remain unclear. Here, using observations and model results, the authors show that ice-ocean feedbacks, triggered by an external perturbation, could be responsible for changes in sea-ice extent observed in the Ross Sea.

A new meltpond parameterization has been developed for the CICE sea ice model, taking advantage of the level ice tracer available in the model. The ponds evolve according to physically based process descriptions, assuming a depth-area ratio for changes in pond volume. A novel aspect of the new scheme is that the ponds are carried as tracers on the level ice area of each thickness category, thus limiting their spatial extent based on the simulated sea ice topography. This limiting is meant to approximate the horizontal drainage of melt water into depressions in ice floes. Simulated melt pond processes include collection of liquid melt water and rain into ponds, drainage through permeable sea ice or over the edges of floes, infiltration of snow by pond water, and refreezing of ponds. Furthermore, snow that falls on top of ponds whose top surface has refrozen blocks radiation from penetrating into the ponds and sea ice below. Along with a control simulation, we present a range of sensitivity tests to parameters related to each subprocess described by the parameterization. With the exception of one parameter that alters the albedo of snow-covered pond ice, results are not highly sensitive to these parameters unless an entire process is removed. The snow simulation itself is critical, because the volume of snow deposition and rate of snow melt largely determine the timing and extent of the simulated melt ponds. Nevertheless, compensating effects moderate the model's sensitivity to precipitation changes. For instance, infiltration of the snow by melt water postpones the appearance of ponds and the subsequent acceleration of melting through albedo feedback, while snow on top of refrozen pond ice also reduces the ponds' effect on the radiation budget. By construction, the model simulation of level and ridged ice is also important for this parameterization. We find that as sea ice thins, either through time or when comparing sensitivity tests, the area of level ice increases. This leads to an enhanced thinning feedback in the model, because a greater ice area may be exposed to ponding and further thinning due to lowered albedo. © 2012 Elsevier Ltd.

An assessment of the performance of a state-of-the-art large-scale coupled sea iceocean model, including a new snow multilayer thermodynamic scheme, is performed. Four 29 year long simulations are compared against each other and against sea ice thickness and extent observations. Each simulation uses a separate parameterization for snow thermophysical properties. The first simulation uses a constant thermal conductivity and prescribed density profiles. The second and third parameterizations use typical power-law relationships linking thermal conductivity directly to density (prescribed as in the first simulation). The fourth parameterization is newly developed and consists of a set of two linear equations relating the snow thermal conductivity and density to the mean seasonal wind speed. Results show that simulation 1 leads to a significant overestimation of the sea ice thickness due to overestimated thermal conductivity, particularly in the Northern Hemisphere. Parameterizations 2 and 4 lead to a realistic simulation of the Arctic sea ice mean state. Simulation 3 results in the underestimation of the sea ice basal growth in both hemispheres, but is partly compensated by lateral growth and snow ice formation in the Southern Hemisphere. Finally, parameterization 4 improves the simulated Snow Depth Distributions by including snow packing by wind, and shows potential for being used in future works. The intercomparison of all simulations suggests that the sea ice model is more sensitive to the snow representation in the Arctic than it is in the Southern Ocean, where the sea ice thickness is not driven by temperature profiles in the snow.

We derive the terms in the Antarctic sea ice concentration budget from the output of three models, and compare them to observations of the same terms. Those models include two climate models from the 5th Coupled Model Intercomparison Project (CMIP5) and one ocean–sea ice coupled model with prescribed atmospheric forcing. Sea ice drift and wind fields from those models, in average over April-October 1992-2005, all exhibit large differences with the available observational or reanalysis datasets. However, the discrepancies between the two distinct ice drift products or the two wind reanalyses used here are sometimes even greater than those differences. Two major findings stand out from the analysis. Firstly, large biases in sea ice drift speed and direction in exterior sectors of the sea ice covered region tend to be systematic and consistent with those in winds. This suggests that sea ice errors in these areas are most likely wind-driven, so as errors in the simulated ice motion vectors. The systematic nature of these biases is less prominent in interior sectors, nearer the coast, where sea ice is mechanically constrained and its motion in response to the wind forcing more depending on the model rheology. Second, the intimate relationship between winds, sea ice drift and the sea ice concentration budget gives insight on ways to categorize models with regard to errors in their ice dynamics. In exterior regions, models with seemingly too weak winds and slow ice drift consistently yield a lack of ice velocity divergence and hence a wrong wintertime sea ice growth rate. In interior sectors, too slow ice drift, presumably originating from issues in the physical representation of sea ice dynamics as much as from errors in surface winds, leads to wrong timing of the late winter ice retreat. Those results illustrate that the applied methodology provides a valuable tool for prioritizing model improvements based on the ice concentration budget–ice drift biases–wind biases relationship prevailing in the simulation of Antarctic sea ice over the last decades.

第6回極域科学シンポジウム[OM] 極域気水圏11月16日（月） 統計数理研究所 セミナー室2（D304）

International audience; Several large-scale sea ice simulations are performed over the last three decades using a coupled ocean–sea ice model under the same experimental setup but partly modifying the representation of snow physics in the model. The inter-simulation spread analysis yields that the simulated multi-year ice is sensitive to such changes while the seasonal sea ice, is rather dominantly driven by the external oceanic and atmospheric forcings. In the context of a thinning Arctic sea ice cover, those findings suggest that including snow processes in large-scale sea ice models is beneficial, if not necessary, to predict the timing of the Arctic multi-year ice disappearance, whereas the operational forecasting of first-year ice extent using fully coupled models will likely require improvement to the oceanic and atmospheric components themselve

Introducing a parameterization of the interactions between wind-driven snow depth changes and melt\ud pond evolution allows us to improve large scale models. In this paper we have implemented an explicit\ud melt pond scheme and, for the first time, a wind dependant snow redistribution model and new snow\ud thermophysics into a coupled ocean–sea ice model.\ud The comparison of long-term mean statistics of melt pond fractions against observations demonstrates\ud realistic melt pond cover on average over Arctic sea ice, but a clear underestimation of the pond coverage\ud on the multi-year ice (MYI) of the western Arctic Ocean. The latter shortcoming originates from the concealing\ud effect of persistent snow on forming ponds, impeding their growth. Analyzing a second simulation\ud with intensified snow drift enables the identification of two distinct modes of sensitivity in the\ud melt pond formation process. First, the larger proportion of wind-transported snow that is lost in leads\ud directly curtails the late spring snow volume on sea ice and facilitates the early development of melt\ud ponds on MYI. In contrast, a combination of higher air temperatures and thinner snow prior to the onset\ud of melting sometimes make the snow cover switch to a regime where it melts entirely and rapidly. In the\ud latter situation, seemingly more frequent on first-year ice (FYI), a smaller snow volume directly relates to\ud a reduced melt pond cover.\ud Notwithstanding, changes in snow and water accumulation on seasonal sea ice is naturally limited,\ud which lessens the impacts of wind-blown snow redistribution on FYI, as compared to those on MYI. At\ud the basin scale, the overall increased melt pond cover results in decreased ice volume via the ice-albedo\ud feedback in summer, which is experienced almost exclusively by MYI.

Irrigation and society in Central Asia from the beginnings to the Achaemenid period. The present paper deals with the problem of the origin of artificial irrigation in Central Asia, from the beginnings in the early 3rd millennium B.C. to the Achaemenid period. It is based mainly on archaeological evidence since textual sources are scarce. Information brought by archaeological excavations and surveys (ancient canal remains, sites and artefacts) is put together with palaeo-environmental data in order to estimate the weight of environmental vs socio-economical parameters in the process of formation of early archaeological cultures in Central Asia. These cultures are spread over enormous territories and they are possibly reflecting socio-political formations of "Proto-State" type. The concept of Proto-State, its socio-economical correlates as well as the theory arguing that Central Asia is no more than the periphery of Near Eastern Early States are discussed., L'article fait le point sur la question de l'origine de l'agriculture irriguée en Asie centrale au début du IIIe millénaire et de son développement jusqu'à l'époque achéménide d'après une documentation principalement archéologique, car les sources textuelles sont rares. Les informations tirées des fouilles et des prospections (vestiges de canaux anciens, sites d'habitat, artefacts) sont confrontées aux données paléo-environnementales pour évaluer l'importance des paramètres naturels et celle des facteurs économiques et sociaux dans l'émergence, à haute époque, de cultures archéologiques homogènes sur de vastes territoires. Ces cultures sont souvent prises comme des expressions matérielles de formations socio-politiques appelées «proto-étatiques». Cette notion de proto-Etat, ses implications socio-économiques, ainsi que la conception de l'Asie centrale comme périphérie d'empires moyen-orientaux font l'objet d'une discussion critique., Francfort Henri-Paul, Lecomte Olivier. Irrigation et société en Asie centrale des origines à l'époque achéménide. In: Annales. Histoire, Sciences Sociales. 57ᵉ année, N. 3, 2002. pp. 625-663.

Les fouilles récentes de la mission archéologique franco-turkmène sur le site d'Ulug Dépé, dans le sud du Turkménistan, ont révélé la plus longue séquence stratigraphique d 'Asie centrale : du Chalcolithique à la période achéménide. De par sa situation géographique, sa surface (13 ha) et sa hauteur, Ulug Dépé est un site clé pour l'étude de l'interaction entre l'Asie centrale, l'Elam, la Mésopotamie et la civilisation de l'Indus ; mais également pour la compréhension des grandes articulations chrono-culturelles centre-asiatiques qui font débat dans la communauté scientifique.

This paper assesses the capabilities of a new one-dimensional snow scheme developed for the thermodynamic component of the Louvain-la-Neuve sea-Ice Model (LIM). the model is validated at Point Barrow, Alaska, and at Ice Station Polarstern (ISPOL) in the western Weddell Sea, Southern Ocean. the new snow thermodynamic scheme leads to better snow internal temperature profiles, with a set-up-dependent increase in the correlation between simulated and observed temperature profiles. on average over all runs, these correlations are 27% better with the six-layer configuration. the model’s ability to reproduce observed temperatures improves with the number of snow layers, but stabilizes after a threshold layer number is reached. the lowest and highest values for this threshold are 3 (at Point Barrow) and 6 (at ISPOL), respectively. Overall, the improvement of the model’s ability to simulate sea-ice thickness is not as significant as for snow temperature, probably because of the rather crude representation of the snow stratigraphy in the model.

This chapter describes the Gorgân and Dehistan areas of the Vehrkana or Hyrcania, the north-east frontier of the Iranian empire. The plain of Gorgân constitutes its southern part while the plain of Misrian, or Dehistan, its northern part. The chapter explains that the plain of Gorgân was occupied earlier than the plain of Misrian to the north because of its favourable hydrological resources, and describes the settlements in these two areas.

Lecomte Olivier. Entre Iran et Touran : recherches archéologiques au Turkménistan méridional (2001-2006). In: Comptes rendus des séances de l'Académie des Inscriptions et Belles-Lettres, 151ᵉ année, N. 1, 2007. pp. 195-226.

Cet article présente les restes fauniques recueillis dans un temple de tradition néo-babylonienne en Basse Mésopotamie. Le contexte archéologique des trouvailles permet d'affirme l'origine rituelle et religieuse de ces dépôts animaux. L'analyse archéozoologique apporte de nouvelles informations sur le statut d'espèces sacrifiées, en particulier l'âne (Equus asinus) dans un contexte non funéraire.

Plusieurs organisations representant les editeurs, les agences et les clients proposaient le 16 novembre 2006 une journee d’etude sur les abonnements. Apres un rappel des attentes de chacun de ces acteurs, la premiere partie s’est penchee sur la mise en pratique du vade-mecum sur la gestion des abonnements publie en 2005. La deuxieme partie s’est interessee aux abonnements electroniques : la strategie Internet des editeurs, le marche francais des e-revues, les attentes des utilisateurs, le role des consortiums, la problematique de l’acces aux archives et l’importance des statistiques d’usage.

The transition from the Early to the Middle Bronze Age is underlined by an important evolution in weaponry. A number of comparable graves containing a very specific selection of weapons (daggers, socketted spearheads and fenestrated axes) are spread over a vast and particular geographical area: the Levantine coast, the middle Euphrates, the Diyala as far as the strait of Hormuz (with the exception of teh axes for this region). We put forward the hypothesis that semi-nomadic populations would have contributes to the spread of this weaponry. This corpus illustrates the beginnings of political control by bedouins societies enriched by a new know-how. There was the a social, rather than an actual, movement of these populations.

International audience; Suhûm is the region of the Middle Euphrates which was situated between Mari and Hît (nowadays in Iraq). The archives from Mari, dating back to the 19th and 18th centuries B.C., inform us in a very detailed way about the struggles that were going on in an attempt to control the region. As far as we know, after a period of relative autonomy, the region passed under the alternating control of three regional powers: Ešnunna, Babylon and Mari. The texts mainly inform us about the invasions from Ešnunna when Suhûm was placed under the control of Mari. Nevertheless, the region, in particular the city of Hît and its bitumen springs, was also important to Babylon for economic reasons. Besides, the final destruction of Mari in 1759 B.C. might have been motivated by the will to have the region controlled exclusively by Babylon: the king Hammurabi might have wanted to destroy a kingdom that was threatening the Babylonian interests in the region forever.

International audience; The middle Euphrates region is well documented throughout the 1st millennium B.C. From the beginning of the period, the situation in the lower Khabur and the middle Euphrates varied between autonomy and the recognition of Assyrian domination. At the same time a passageway and a border between the Assyrian and Babylonian influences, the region was one of the entry points of the Assyrians into Babylonia, the Assyrians being in a position to ensure their domination at the heart of the territory of their southern neighbours, thanks to their troops posted in the region. The middle Euphrates, and in particular the region of Suhu, was the main route for the penetration of Aramaean and then Arab populations into Mesopotamia. Today the classical and cuneiform sources allow a path to be suggested, that seems to have been fairly common for the two population groups. The development of the caravan trade, as early as the 7th century, placed Suhu at the heart of exchanges between Arabia and Mesopotamia on a north-south axis. From being a secondary route in the Neo-Assyrian period until the end of the Seleucid empire, the middle Euphrates became the main axis of penetration into the Parthian empire from the west, which was probably not only under pressure from the vassal states of Rome, but also as a result of the development of relations with Arabia. Thus it was a strategic region, as much from an economic as a political point of view, that the Romans and Sasanids struggled over beginning in the 3rd century A.D.