Author: "Deborah Verfaillie" - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Deborah Verfaillie"' showing total 48 results

Start Over Author "Deborah Verfaillie"

48 results on '"Deborah Verfaillie"'

1. The circum-Antarctic ice-shelves respond to a more positive Southern Annular Mode with regionally varied melting

Author: Deborah Verfaillie, Charles Pelletier, Hugues Goosse, Nicolas C. Jourdain, Christopher Y. S. Bull, Quentin Dalaiden, Vincent Favier, Thierry Fichefet, and Jonathan D. Wille
Subjects: Geology, QE1-996.5, Environmental sciences, GE1-350
Abstract: Positive phases of the Southern Annular Mode lead to enhanced basal melt overall in the Antarctic ice shelves, with strong losses in the Bellingshausen and Western Pacific sectors and gains in the Amundsen Sea, according to ice-ocean model experiments.
Published: 2022
Full Text: View/download PDF

2. The S2M meteorological and snow cover reanalysis over the French mountainous areas: description and evaluation (1958–2021)

Author: Matthieu Vernay, Matthieu Lafaysse, Diego Monteiro, Pascal Hagenmuller, Rafife Nheili, Raphaëlle Samacoïts, Deborah Verfaillie, Samuel Morin, Centre d'Etudes de la Neige (CEN), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Direction de la climatologie et des services climatiques (DCSC), Météo-France, and Université Catholique de Louvain = Catholic University of Louvain (UCL)
Subjects: [SDE]Environmental Sciences, General Earth and Planetary Sciences
Abstract: This work introduces the S2M (SAFRAN–SURFEX/ISBA–Crocus–MEPRA) meteorological and snow cover reanalysis in the French Alps, Pyrenees and Corsica, spanning the time period from 1958 to 2021. The simulations are made over elementary areas, referred to as massifs, designed to represent the main drivers of the spatial variability observed in mountain ranges (elevation, slope and aspect). The meteorological reanalysis is performed by the SAFRAN system, which combines information from numerical weather prediction models (ERA-40 reanalysis from 1958 to 2002, ARPEGE from 2002 to 2021) and the best possible set of available in situ meteorological observations. SAFRAN outputs are used to drive the Crocus detailed snow cover model, which is part of the land surface scheme SURFEX/ISBA. This model chain provides simulations of the evolution of the snow cover, underlying ground and the associated avalanche hazard using the MEPRA model. This contribution describes and discusses the main climatological characteristics (climatology, variability and trends) and the main limitations of this dataset. We provide a short overview of the scientific applications using this reanalysis in various scientific fields related to meteorological conditions and the snow cover in mountain areas. An evaluation of the skill of S2M is also displayed, in particular through comparison to 665 independent in situ snow depth observations. Further, we describe the technical handling of this open-access dataset, available at https://doi.org/10.25326/37#v2020.2. The S2M data are provided by Météo-France – CNRS, CNRM, Centre d'Études de la Neige, through AERIS (Vernay et al., 2022).
Published: 2022
Full Text: View/download PDF

3. Climate Services Toolbox (CSTools) v4.0: from climate forecasts to climate forecast information

Author: Núria Pérez-Zanón, Louis-Philippe Caron, Silvia Terzago, Bert Van Schaeybroeck, Llorenç Lledó, Nicolau Manubens, Emmanuel Roulin, M. Carmen Alvarez-Castro, Lauriane Batté, Pierre-Antoine Bretonnière, Susana Corti, Carlos Delgado-Torres, Marta Domínguez, Federico Fabiano, Ignazio Giuntoli, Jost von Hardenberg, Eroteida Sánchez-García, Verónica Torralba, Deborah Verfaillie, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), and Barcelona Supercomputing Center
Subjects: SEASONAL FORECAST, Climate information, PREDICTION, EARTH SYSTEM MODELS, ADJUSTMENT, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, Climate data, Climatic changes--Forecasting, Simulació per ordinador, Pharmacology (medical), PHYSICAL SNOWPACK MODEL, COMBINATION, Simulació, Mètodes de, Climate forecast, CALIBRATION, Forecasting--Mathematical models, [STAT.AP]Statistics [stat]/Applications [stat.AP], Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia [Àrees temàtiques de la UPC], Climate Services Toolbox, MULTIMODEL ENSEMBLES, Climate Services Toolbox (CSTools) v4.0, General Medicine, Climatic changes, VARIABILITY, Temperature--Seasonal variations, Climate forecast data, Physics and Astronomy, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, PRECIPITATION
Abstract: Despite the wealth of existing climate forecast data, only a small part is effectively exploited for sectoral applications. A major cause of this is the lack of integrated tools that allow the translation of data into useful and skillful climate information. This barrier is addressed through the development of an R package. Climate Services Toolbox (CSTools) is an easy-to-use toolbox designed and built to assess and improve the quality of climate forecasts for seasonal to multi-annual scales. The package contains process-based, state-of-the-art methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination, and multivariate verification, as well as basic and advanced tools to obtain tailored products. Due to the modular design of the toolbox in individual functions, the users can develop their own post-processing chain of functions, as shown in the use cases presented in this paper, including the analysis of an extreme wind speed event, the generation of seasonal forecasts of snow depth based on the SNOWPACK model, and the post-processing of temperature and precipitation data to be used as input in impact models. This research has been supported by the Horizon 2020 (S2S4E; grant no. 776787), EUCP (grant no. 776613), ERA4CS (grant no. 690462), and the Ministerio de Ciencia e Innovación (grant no. FPI PRE2019-088646). Peer Reviewed "Article signat per 19 autors/es: Núria Pérez-Zanón, Louis-Philippe Caron, Silvia Terzago, Bert Van Schaeybroeck, Llorenç Lledó, Nicolau Manubens, Emmanuel Roulin, M. Carmen Alvarez-Castro, Lauriane Batté , Pierre-Antoine Bretonnière, Susana Corti, Carlos Delgado-Torres, Marta Domínguez, Federico Fabiano, Ignazio Giuntoli, Jost von Hardenberg, Eroteida Sánchez-García, Verónica Torralba, and Deborah Verfaillie"
Published: 2022
Full Text: View/download PDF

4. How Reliable Are Decadal Climate Predictions of Near-Surface Air Temperature?

Author: Francisco J. Doblas-Reyes, Verónica Torralba, Deborah Verfaillie, Núria Pérez-Zanón, Balakrishnan Solaraju-Murali, Markus G. Donat, Simon Wild, Universitat Politècnica de Catalunya. Doctorat en Enginyeria Ambiental, Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Earth and Life Institute [Louvain-La-Neuve] (ELI), Université Catholique de Louvain = Catholic University of Louvain (UCL), Institució Catalana de Recerca i Estudis Avançats (ICREA), and Barcelona Supercomputing Center
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, media_common.quotation_subject, Library science, Decadal variability, 010502 geochemistry & geophysics, Climate prediction, 01 natural sciences, Climate models, Surface air temperature, Simulació per ordinador, Political science, Gratitude, media_common.cataloged_instance, European union, Weatther forecasting -- Mathematical models, Physics::Atmospheric and Oceanic Physics, 0105 earth and related environmental sciences, media_common, Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia [Àrees temàtiques de la UPC], Computer simulation, Desenvolupament humà i sostenible::Enginyeria ambiental [Àrees temàtiques de la UPC], Climatology, Previsió del temps -- Models matemàtics, 13. Climate action, [SDE]Environmental Sciences, Christian ministry, Forecast verification/skill, Forecasting
Abstract: Decadal climate predictions are being increasingly used by stakeholders interested in the evolution of climate over the coming decade. However, investigating the added value of those initialized decadal predictions over other sources of information typically used by stakeholders generally relies on forecast accuracy, while probabilistic aspects, although crucial to users, are often overlooked. In this study, the quality of the near-surface air temperature from initialized predictions has been assessed in terms of reliability, an essential characteristic of climate simulation ensembles, and compared to the reliability of noninitialized simulations performed with the same model ensembles. Here, reliability is defined as the capability to obtain a true estimate of the forecast uncertainty from the ensemble spread. We show the limited added value of initialization in terms of reliability, the initialized predictions being significantly more reliable than their noninitialized counterparts only for specific regions and the first forecast year. By analyzing reliability for different forecast system ensembles, we further highlight the fact that the combination of models seems to play a more important role than the ensemble size of each individual forecast system. This is due to sampling different model errors related to model physics, numerics, and initialization approaches involved in the multimodel, allowing for a certain level of error compensation. Finally, this study demonstrates that all forecast system ensembles are affected by systematic biases and dispersion errors that affect the reliability. This set of errors makes bias correction and calibration necessary to obtain reliable estimates of forecast probabilities that can be useful to stakeholders. The EUCP project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement 776613. The research leading to these results has also received funding from the Spanish Ministerio de Ciencia, Innovación y Universidades as part of the CLINSA project with funding reference CGL2017-85791-R. MGD is also supported by the Spanish Ministry of Science, Innovation and Universities Grant RYC-2017-22964. BSM acknowledges financial support from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement 713673 and from a fellowship of “la Caixa” Foundation (ID 100010434). The fellowship code is LCF/BQ/IN17/11620038. SW has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433. We acknowledge the use of the s2dverification (Manubens et al. 2018), startR (BSC/CNS and Manubens 2020), SpecsVerification (Siegert 2017), CSTools (Perez-Zanon et al. 2019), ClimProjDiags (BSC/CNS et al. 2020), and boot (Davison and Hinkley 1997; Canty and Ripley 2020) R (R Core Team 2013) software packages. We also thank Nicolau Manubens, An-Chi Ho, Pablo Ortega, Rashed Mahmood, Yohan Ruprich-Robert, and Roberto Bilbao from the BSC for their technical and scientific support. We further express our gratitude to Charles Pelletier from ELI for his careful reading of the manuscript. Finally, we would like to thank Antje Weisheimer (University of Oxford) and two anonymous reviewers for constructive comments that helped us greatly improve this article.
Published: 2021
Full Text: View/download PDF

5. Oceanic drivers of air-sea-ice interactions: the imprint of mesoscale eddies and ocean heat content on the sea ice, atmosphere, and ice sheet

Author: Pierre-Vincent Huot, Christoph Kittel, Thierry Fichefet, Sylvain Marchi, Nicole Van Lipzig, Xavier Fettweis, Deborah Verfaillie, François Klein, and Nicolas Jourdain
Subjects: Astrophysics::Earth and Planetary Astrophysics, Physics::Atmospheric and Oceanic Physics, Physics::Geophysics
Abstract: The Antarctic Climate is characterized by strong interactions between the Southern Ocean, its sea ice cover, and the overlying atmosphere taking place over a wide range of spatio-temporal scales. This coupling constrains our ability to isolate the role of specific components of the climate system on the dynamics of the Antarctic Climate, especially with stand-alone approaches neglecting the feedbacks at play. Based on coupled model simulations, we explore how the ocean can drive the interactions with the cryosphere and atmosphere at two distinct spatio-temporal scales. First, the role of ocean mesoscale eddies is investigated. We describe the imprint of mesoscale eddies on the sea ice and atmosphere in a high-resolution simulation of the Adélie Land sector (East Antarctica) performed with a regional coupled ocean--sea ice--atmosphere model (NEMO-MAR). Specific attention is given to the role of the sea ice in the modulation of the air-sea interactions at mesoscale and to the influence of eddy-driven fluxes on the ocean and sea ice. We show that mesoscale eddies affect near-surface winds and air temperature both in ice-free and ice-covered conditions due to their imprint on the sea ice cover. In addition, eddies promote northward sea ice transport and decrease momentum transfer by surface stress to the ocean. In a second section, we move to larger spatial and temporal scales and delve into the influence of the ocean on the seasonal to interannual variability of the sea ice, atmosphere, and ice shelves basal melt at the scale of the Southern Ocean. This work is based on early results from a new coupled ocean–sea ice--atmosphere--ice sheet configuration with explicit under-ice shelf cavities called PARASO. We focus on subsurface heat content variability and its influence on the interactions between the ocean, the sea ice, the atmosphere, and the Antarctic Ice Sheet.
Published: 2022
Full Text: View/download PDF

6. PARASO, a circum-Antarctic fully-coupled ice-sheet - ocean - sea-ice - atmosphere - land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5

Author: Sylvain Marchi, Charles Pelletier, Thierry Fichefet, Hugues Goosse, Konstanze Haubner, Samuel Helsen, Pierre-Vincent Huot, Christoph Kittel, François Klein, Nicole P. M. van Lipzig, François Massonnet, Pierre Mathiot, Ehsan Moravveji, Eduardo Moreno-Chamarro, Pablo Ortega, Frank Pattyn, Niels Souverijns, Guillian Van Achter, Sam Vanden Broucke, Deborah Verfaillie, Sébastien Le Clech, Alexander Vanhulle, and Lars Zipf
Abstract: How well is the Antarctic climate over the last decades represented in climate models and how predictable is its future evolution? These questions delve into the specificities of the Antarctic climate, a system characterized by large natural fluctuations and complex interactions between the ice sheet, ocean, sea ice and atmosphere. The PARAMOUR project aims at improving our understanding of key processes which control the variability and predictability of the Antarctic climate at the decadal timescale. In this context, we introduce PARASO, a novel fully-coupled regional ocean - sea-ice - ice-sheet - atmosphere climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are f.ETISh1.7 (ice sheet), NEMO3.6 (ocean), LIM3.6 (sea ice), COSMO5.0 (atmosphere) and CLM4.5 (land), which are run at a horizontal resolution close to 1/4°. One key feature of this tool resides in a novel two-way coupling interface for representing the ocean - ice-sheet interactions, through explicitly resolved ice-shelf cavities. We also consider the impact of atmospheric processes on the Antarctic ice sheet through surface mass exchanges between COSMO-CLM and f.ETISh. Our developments include a new surface tiling approach to combine open-ocean and sea-ice covered cells within COSMO. Using a 30 year-long run, we investigate the model performance and the interannual-to-decadal variability of the simulated Antarctic climate. The focus is on the interactions between the atmosphere, ocean and ice components at the regional scale and the links with larger spatial scales. Specific attention is paid to the mass balance of ice sheets and ice shelves, which influences both the ice sheet dynamics and the changes in the ocean and atmosphere. The system and its performance will be documented in this presentation together with some aspects of decadal variability from a 30-year integration forced with reanalyses (ERA5 and ORAS5). Early results of a 3-member retrospective forecast driven by EC-Earth will also be presented.
Published: 2022
Full Text: View/download PDF

7. How does the Southern Annular Mode impact ice-shelf basal melt around Antarctica?

Author: Deborah Verfaillie, Charles Pelletier, Hugues Goosse, Nicolas C. Jourdain, Christopher Y.S. Bull, Quentin Dalaiden, Vincent Favier, Thierry Fichefet, and Jonathan Wille
Abstract: The climate of the polar regions is characterized by large fluctuations and has experienced dramatic changes over the past decades. In particular, the patterns of changes in sea ice and ice sheet mass are complex in the Southern Hemisphere. The Antarctic Ice Sheet has also lost mass in the past decades, especially in Western Antarctica, with a spectacular thinning and weakening of ice shelves, i.e., the floating extensions of the grounded ice sheet. Despite recent advances in observing and modelling the Antarctic climate, the mechanisms behind this long-term mass loss remain poorly understood because of the limited amount of observations and the large biases of climate models in polar regions, in concert with the large internal variability prevailing in the Antarctic. Among all the processes involved in the mass variability, changes in the general atmospheric circulation of the Southern Hemisphere may have played a substantial role. One of the most important atmospheric modes of climate variability in the Southern Ocean is the Southern Annular Mode (SAM), which represents the position and the strength of the westerly winds. During years with a positive SAM index, lower sea level pressure at high latitudes and higher sea level pressure at low latitudes occur, resulting in a stronger pressure gradient and intensified Westerlies. However, the current knowledge of the impact of these fluctuations of the Westerlies on the Antarctic cryosphere is still limited. Over the past few years, some efforts investigated the impact of the SAM on the Antarctic sea ice and the surface mass balance of the ice sheet from an atmosphere-only perspective. Recently, a few oceanic studies have focused on the local impact of SAM-related fluctuations on the ice-shelf basal melt in specific regions of Antarctica, particularly Western Antarctica. However, to our knowledge, there is no such study at the scale of the whole Antarctic continent. In this study, we performed idealized experiments with a pan-Antarctic regional ice-shelf cavity-resolving ocean - sea-ice model for different phases of the SAM. We show that positive (negative) phases lead to increased (decreased) upwelling and subsurface ocean temperature and salinity close to ice shelves. A one-standard-deviation increase of the SAM leads to a net basal mass loss of 40 Gt yr-1, with strong regional contrasts: increased melt in the Western Pacific and Amundsen-Bellingshausen sectors and the opposite response in the Ross sector. Taking these as a baseline sensitivity, we estimate last millennium and end-of-21st-century ice-shelf basal melt changes due to SAM of -60.7 Gt yr-1 and 1.8 to 26.8 Gt yr-1 (depending on the emission scenario considered), respectively, compared to the present.
Published: 2022
Full Text: View/download PDF

8. Supplementary material to 'The CSTools (v4.0) Toolbox: from Climate Forecasts to Climate Forecast Information'

Author: Núria Pérez-Zanón, Louis-Philippe Caron, Silvia Terzago, Bert Van Schaeybroeck, Llorenç Lledó, Nicolau Manubens, Emmanuel Roulin, M. Carmen Alvarez-Castro, Lauriane Batté, Carlos Delgado-Torres, Marta Domínguez, Jost von Hardenberg, Eroteida Sánchez-García, Verónica Torralba, and Deborah Verfaillie
Published: 2021
Full Text: View/download PDF

9. The CSTools (v4.0) Toolbox: from Climate Forecasts to Climate Forecast Information

Author: Núria Pérez-Zanón, Louis-Philippe Caron, Silvia Terzago, Bert Van Schaeybroeck, Llorenç Lledó, Nicolau Manubens, Emmanuel Roulin, M. Carmen Alvarez-Castro, Lauriane Batté, Carlos Delgado-Torres, Marta Domínguez, Jost von Hardenberg, Eroteida Sánchez-García, Verónica Torralba, and Deborah Verfaillie
Abstract: Despite the wealth of existing climate forecast data, only a small part is effectively exploited for sectoral applications. A major cause of this is the lack of integrated tools that allow the translation of data into useful and skilful climate information. This barrier is addressed through the development of an R package. CSTools is an easy-to-use toolbox designed and built to assess and improve the quality of climate forecasts for seasonal to multi–annual scales. The package contains process-based state-of-the-art methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination and multivariate verification, as well as basic and advanced tools to obtain tailored products. Due to the design of the toolbox in individual functions, the users can develop their own post-processing chain of functions as shown in the use cases presented in this manuscript: the analysis of an extreme wind speed event, the generation of seasonal forecasts of snow depth based on the SNOWPACK model and the post-processing of data to be used as input for the SCHEME hydrological model.
Published: 2021

10. PARASO, a circum-Antarctic fully-coupled ice-sheet - ocean - sea-ice - atmosphere - land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5

Author: Pablo Ortega, Eduardo Moreno-Chamarro, Pierre Mathiot, Konstanze Haubner, Samuel Helsen, Thierry Fichefet, Ehsan Moravveji, Pierre-Vincent Huot, Hugues Goosse, Lars Zipf, Sylvain Marchi, François Massonnet, Guillian Van Achter, Christoph Kittel, Alexander Vanhulle, Charles Pelletier, François Klein, Niels Souverijns, Nicole Van Lipzig, Deborah Verfaillie, Frank Pattyn, Sébastien Le clec'h, and Sam Vanden Broucke
Subjects: Atmosphere, geography, Coupling (physics), geography.geographical_feature_category, Sea ice, Polar, Antarctic ice sheet, Climate model, Context (language use), Geophysics, Ice sheet, Geology
Abstract: We introduce PARASO, a novel five-component fully-coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are f.ETISh1.7 (ice sheet), NEMO3.6 (ocean), LIM3.6 (sea ice), COSMO5.0 (atmosphere) and CLM4.5 (land), which are here run at an horizontal resolution close to 1/4°. One key-feature of this tool resides in a novel two-way coupling interface for representing ocean – ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM – f.ETISh surface mass exchanges. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO – f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled two-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.
Published: 2021
Full Text: View/download PDF

11. The S2M meteorological and snow cover reanalysis over the French mountainous areas, description and evaluation (1958–2020)

Author: Samuel Morin, Matthieu Vernay, Rafife Nheili, Raphaëlle Samacoïts, Deborah Verfaillie, Matthieu Lafaysse, Pascal Hagenmuller, and Diego Monteiro
Subjects: Meteorological reanalysis, Avalanche hazard, Climatology, Elevation, Numerical weather prediction models, Environmental science, Spatial variability, Snow, Snow cover
Abstract: This work introduces the S2M (SAFRAN - SURFEX/ISBA-Crocus - MEPRA) meteorological and snow cover reanalysis in the French Alps, Pyrenees and Corsica, spanning the time period from 1958 to 2020. The simulations are made over elementary areas, referred to as massifs, designed to represent the main drivers of the spatial variability observed in mountain ranges (elevation, slope and aspect). The meteorological reanalysis is performed by the SAFRAN system, which combines information from numerical weather prediction models (ERA-40 reanalysis from 1958 to 2002, ARPEGE from 2002 to 2020) and the best possible set of available in-situ meteorological observations. SAFRAN outputs are used to drive the Crocus detailed snow cover model, which is part of the land surface scheme SURFEX/ISBA. This model chain provides simulations of the evolution of the snow cover, underlying ground, and the associated avalanche hazard using the MEPRA model. This contribution describes and discusses the main climatological characteristics (climatology, variability and trends), and the main limitations of this dataset. We provide a short overview of the scientific applications using this reanalysis in various scientific fields related to meteorological conditions and the snow cover in mountain areas. An evaluation of the skill of S2M is also displayed, in particular through comparison to 665 independent in-situ snow depth observations. Further, we describe the technical handling of this open access data set, available at this address: http://dx.doi.org/10.25326/37#v2020.2. Scientiﬁc publications using this dataset must mention in the acknowledgments: "The S2M data are provided by Météo-France - CNRS, CNRM Centre d’Etudes de la Neige, through AERIS" and refer to it as Vernay et al. (2020).
Published: 2021

12. Combining random forests and class-balancing to discriminate between three classes of avalanche activity in the French Alps

Author: Pascal Dkengne Sielenou, Marie Dumont, Philippe Naveau, Léo Viallon-Galinier, Pascal Hagenmuller, Deborah Verfaillie, Samuel Morin, Nicolas Eckert, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre d'Etudes de la Neige (CEN), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA), Université Catholique de Louvain = Catholic University of Louvain (UCL), Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), French Ministry of the Environment, Risk Division (DGPR), French Gestion des Impacts du Changement ClimatiqueGICC and Obervatoire National du Changement climatiqueONERC programs (ADAMONT grant), and ANR-16-CE01-0006,EBONI,Dépot, devenir et impact des impuretés absorbantes dans le manteau neigeux(2016)
Subjects: business.industry, Computer science, Physics::Instrumentation and Detectors, Forest decision trees, Moderate activity, Geotechnical Engineering and Engineering Geology, Machine learning, computer.software_genre, Snow, Class (biology), Random forest, Physics::Geophysics, Avalanche forecasting, Variable (computer science), [SPI]Engineering Sciences [physics], Avalanche statistical forecasting, Snow and meteorological conditions and reanalyses, [SDE]Environmental Sciences, General Earth and Planetary Sciences, High activity, Artificial intelligence, business, Cluster analysis, French Alps, computer
Abstract: International audience; Determining avalanche activity corresponding to given snow and meteorological conditions is an old problem of high practical relevance. To address it, numerous statistical forecasting models have been developed, but intercomparisons of their efficiency on very large datasets are seldom. In this work, an approach combining random forests with class-balancing is presented and systematically compared with competing methods currently described in the avalanche literature. On more than 50 years of daily avalanche observations, in the 23 massifs of the French Alps, the competing classifiers are evaluated on their ability to distinguish three classes of avalanche activity: non-avalanche days, days with moderate activity, and days with high activity. Moreover, the variables of higher importance in the random forest classifiers are shown to be coherent with current avalanche literature and a clustering based on these variable importance separates massifs which are known to have different avalanche activities. Our approach opens perspectives to support operational avalanche forecasting.
Published: 2021
Full Text: View/download PDF

13. The Biggest Unknowns Related to Decadal Prediction: What 50 Experts Think Are the 5 Major Knowledge Gaps

Author: Dragana Bojovic, Leandro B. Díaz, Francisco J. Doblas-Reyes, Marta Terrado, Markus G. Donat, Yohan Ruprich-Robert, Roberto Bilbao, Pablo Ortega, Balakrishnan Solaraju-Murali, and Deborah Verfaillie
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, 0207 environmental engineering, 02 engineering and technology, 020701 environmental engineering, 01 natural sciences, 0105 earth and related environmental sciences
Published: 2019
Full Text: View/download PDF

14. CSTools: the MEDSCOPE Toolbox for Climate Forecasts postprocessing

Author: Núria Pérez-Zanón, Louis-Philippe Caron, Silvia Terzago, Bert Van Schaeybroeck, Lauriane Batté, M. Carmen Alvarez-Castro, Susana Corti, Marta Dominguez, Federico Fabiano, Silvio Gualdi, Jost von Hardenberg, Llorenç Lledó, Nicolau Manubens, Paola Marson, Stefano Materia, Eroteida Sánchez, Verónica Torralba, Deborah Verfaillie, and Danila Volpi
Abstract: Climate forecasts need to be postprocessed to obtain user-relevant climate information, to develop and implement strategies of adaptation to climate variability and to trigger decisions. Several postprocessing methods are gathered into CSTools (short for Climate Service Tools) for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination and multivariate verification, as well as basic and advanced tools to obtain tailored products. Besides an overview of the methods and documentation available in CSTools, a practical example is demonstrated. The objective of this practical example is to postprocess a seasonal forecast with a set of CSTools functions in order to obtain the required data to produce forecasts of mountain snow resources. Quantile mapping bias-correction and RainFARM stochastic downscaling methods are applied to raw seasonal forecast daily precipitation data to derive 1 km resolution fields. Bias-adjusted and downscaled precipitation data are then employed to drive a snow model, SNOWPACK, and generate snow depth seasonal forecasts at selected high-elevation sites in North-Western Italian Alps. The computational resources required by CSTools to process the forecasts will be discussed. This assessment is relevant given the memory requirements for the use case: while seasonal forecast data occupies ~10MB (8 x 8 grid cells, 215 forecast time steps for 30 different initializations with 25 members each), the data post-processed reaches ~1TB (the RainFARM downscaling requires a refinement factor 100 for the SNOWPACK model increasing the spatial resolution to 800 x 800 grid cells and creating 10 stochastic realizations for each ensemble member). In addition to one strategy using conventional loops, startR is introduced as an efficient alternative. startR is an R package that allows implementing the MapReduce paradigm, i.e. chunking the data and processing them either locally or remotely on high-performance computing systems, leveraging multi-node and multi-core parallelism where possible.
Published: 2021
Full Text: View/download PDF

15. New Late Glacial and Holocene 36Cl and 10Be moraine chronologies from sub-Antarctic Kerguelen Archipelago

Author: Didier Bourlès, Irene Schimmelpfennig, Vincent Favier, Léo Chassiot, Pierre-Henri Blard, Deborah Verfaillie, Joanna Charton, Vincent Jomelli, Georges Aumaître, Régis Braucher, Guillaume Delpech, Vincent Rinterknecht, Karim Keddadouche, Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Earth and Life Institute [Louvain-La-Neuve] (ELI), Université Catholique de Louvain = Catholic University of Louvain (UCL), Institut des Géosciences de l’Environnement (IGE), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Géosciences Paris Saclay (GEOPS), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre de Recherches Pétrographiques et Géochimiques (CRPG), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Université Laval [Québec] (ULaval), Plateforme de géochimie isotopique ASTER-CEREGE, Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )
Subjects: geography, geography.geographical_feature_category, [SDE.MCG]Environmental Sciences/Global Changes, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, 15. Life on land, Sub antarctic, Paleontology, 13. Climate action, Moraine, Archipelago, 14. Life underwater, Glacial period, Geology, Holocene, ComputingMilieux_MISCELLANEOUS
Abstract: The Kerguelen Archipelago (49°S, 69°E) is an excellent location for the study of multi-millennial glacier fluctuations, since it is the largest still glaciated emerged area (552 km2 in 2001) in the sub-Antarctic sector of the Indian Ocean, where many glacio-geomorphological formations such as moraines may be dated. To investigate the so-far little-known Late Glacial and the Holocene glacier fluctuations in Kerguelen, we apply cosmogenic nuclide dating of moraines in 3 glacial valleys: Val Travers valley, Ampere glacier valley and Arago glacier valley. We use in situ 36Cl dating of the basaltic moraine boulders at the first two sites, and 10Be dating of the quartz-bearing syenite boulders at the third site. The new 36Cl and 10Be exposure ages provide time constraints over the last 17,000 years. A glacial advance was highlighted during the Late Glacial at 14.4 ± 1.4 ka ago, probably linked to the Antarctic Cold Reversal event. These results are consistent with those previously obtained on the archipelago (Jomelli et al., 2017, 2018; Charton et al., 2020) and more generally those from other the sub-Antarctic regions (e.g. Sagredo et al., 2018). This suggests that all glaciers at this latitude were broadly sensitive to this specific climatic signal. No Early nor Mid Holocene advances were evidenced in Kerguelen glacier evolution during the Holocene due to missing moraines that may have formed in these specific periods. Radiocarbon-dated peat, published in the 1990s, provides evidence of less extensive glacier extents during the Early Holocene than during the Late Holocene (Frenot et al., 1997). Finally, glaciers seem to have re-advanced only during the Late Holocene, especially within the last millennium, at ⁓1 ka, ⁓620 years and ⁓390 years (Verfaillie et al., submitted). A comparison of this new dataset with the available 10Be ages from other sub-Antarctic regions allows for the identification of 3 different glacier evolution patterns during the Holocene. The glacial fluctuations experienced by Kerguelen glaciers seems particularly uncommon, and are likely due to its singular location in the Southern Indian Ocean. Finally, climatic factors that may explain the Kerguelen glacier evolution (temperature, precipitation) are discussed. To this end, we investigate the chronology of glacier advance/retreat periods with (i) the variation in atmospheric temperatures recorded in ice cores in Antarctica and (ii) the variation in precipitation (Southern Westerly Winds, Southern Annular Mode).Charton et al., 2020 : Ant. Sci. 1-13Frenot et al., 1997 : C.R. Acad. Sci. Paris Life Sciences 320, 567-573Jomelli et al., 2017 : Quat. Sci. Rev. 162, 128-144Jomelli et al., 2018 : Quat. Sci. Rev. 183, 110-123Sagredo et al., 2018 : Quat Sci. Rev. 188, 160-166Verfaillie et al., submitted
Published: 2021
Full Text: View/download PDF

16. Marine records of Holocene glacier variability in the Kerguelen Islands (South Indian Ocean): sedimentology, chronology, and paleoclimatic drivers

Author: Vincent Jomelli, Xavier Crosta, Vincent Favier, Joanna Charton, Deborah Verfaillie, Elisabeth Michel, Emmanuel Chapron, Léo Chassiot, Université Laval [Québec] (ULaval), Géographie de l'environnement (GEODE), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Earth and Life Institute [Louvain-La-Neuve] (ELI), Université Catholique de Louvain = Catholic University of Louvain (UCL), Environnements et Paléoenvironnements OCéaniques (EPOC), Observatoire aquitain des sciences de l'univers (OASU), Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École Pratique des Hautes Études (EPHE), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Indian ocean, geography, geography.geographical_feature_category, Oceanography, [SDE]Environmental Sciences, Glacier, Sedimentology, Holocene, Geology, ComputingMilieux_MISCELLANEOUS, Chronology
Abstract: The strength and the location of Southern Hemisphere winds (SHW) define an annular mode (SAM), a major component of interannual climatic variability in the Southern Hemisphere. SAM has a significant impact on mid-latitude westerly winds, but also acts on the meridional moisture transport over the Southern Ocean (for example, in the case of atmospheric rivers), with dramatic consequences on the cryosphere at high latitudes. Assessment of past, present and future changes in the SAM is essential for understanding climate variations and impacts at high latitudes. To date, Holocene proxy-based reconstructions of SAM are limited to South America, Australia/New Zealand, and Antarctica. In opposite, the paucity of SAM-related records for the Southern Indian Ocean presently limits our understanding of the spatial and temporal extent of SHW behavior in this region.To this aim, we present a series of 30-m long marine records retrieved from a fjord fed by glacial melt of the Ampere glacier belonging to the Cook Ice Cap in the Kerguelen Archipelago (49˚20’S, 69˚20’E). A new chronological framework, based on Bayesian modelling of 50 radiocarbon ages along with 137Cs and 210Pb measures, allows reconstructing 4 kyrs of sediment discharge related to glacier variability. Sedimentological and geochemical analyses from XRF and GEOTEK core scanners highlight (i) a regional tephra at 950 cal BP; (ii) regular occurrences of floods during the LIA; and (iii) a background sedimentation related to glacial flour inputs through hypo- and hyperpycnal flows favoring very high sedimentation rates (1-2 cm.a-1) in the fjord. Phases of glacier advances and retreats linked to moisture transport by SHW are reflected by fluctuations in sedimentological and geochemical signals, and correlated with moraines dating on land. Over the past 4 kyrs, four cycles of glacier advances/retreats can be evidenced, reflecting wet/dry periods in response to shifts in the position and changes in magnitude of the SHW, associated with moisture transport and precipitation in the Southern Indian Ocean. On centennial timescales, wet/dry periods inferred from Kerguelen are in-phase with Holocene SAM-related records from South America and Tasmania over the last 2 kyrs, suggesting the long-term glacier dynamic at Kerguelen is also related to a centennial expression of SAM.Acknowledgments : Marion Dufresne Crew, ARTEMIS program, UGA-ARCA.
Published: 2021
Full Text: View/download PDF

17. Recent climate variability around the Kerguelen Islands (Southern Ocean) seen through weather regimes

Author: Benjamin Pohl, Yves Richard, Deborah Verfaillie, Vincent Favier, Jean-Pierre Féral, Thomas Saucède, Ylber Krasniqi, Julien Pergaud, Biogéosciences [UMR 6282] [Dijon] (BGS), Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UMR237-Aix Marseille Université (AMU)-Avignon Université (AU), Université Grenoble Alpes (UGA), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Biogéosciences [UMR 6282] (BGS), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-Centre National de la Recherche Scientifique (CNRS), and Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Southern Oscillation, Geopotential height, Weather and climate, 010502 geochemistry & geophysics, 01 natural sciences, Wind speed, Interannual variability, medicine, 14. Life underwater, Precipitation, Southern Ocean, Climate variability, 0105 earth and related environmental sciences, Mode (statistics), Antarctic Oscillation, Seasonality, medicine.disease, 13. Climate action, [SDU]Sciences of the Universe [physics], Climatology, Period (geology), Environmental science, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Antarctic oscillation
Abstract: Daily weather regimes are defined around the Kerguelen Islands (Southern Ocean) based on daily 500 hPa geopotential height anomalies derived from the ERA5 ensemble reanalysis over the period 1979-2018. Ten regimes are retained as significant. Their occurrences are highly consistent across reanalysis ensemble members. Regimes show weak seasonality and non-significant long-term trends in their occurrences. Their sequences are usually short (1-3 days), with extreme persistence values above 10 days. Seasonal regime frequency is mostly driven by the phase of the Southern Annular Mode over Antarctica, mid-latitude dynamics over the Southern Ocean like the Pacific South American mode, and to a lesser extent, tropical variability, with significant but weaker relationships with El Niño Southern Oscillation. At the local scale over the Kerguelen Islands, regimes have a strong influence on measured atmospheric and oceanic variables, including minimum and maximum air temperature, mostly driven by horizontal advections, sea water temperature recorded 5 m below the surface, wind speed and sea level pressure. Relationships are weaker for precipitation amounts. Regimes also modify regional contrasts between observational sites in Kerguelen, highlighting strong exposure contrasts. The regimes allow improving our understanding of weather and climate variability and interactions in this region; they will be used in future work to assess past and projected long-term circulation changes in the southern mid-latitudes.
Published: 2021
Full Text: View/download PDF

18. Evolution of the Cook Ice Cap (Kerguelen Islands) between the last centuries and 2100 ce based on cosmogenic dating and glacio-climatic modelling

Author: Etienne Berthier, Joanna Charton, François Bétard, Zoe Stroebele, Irene Schimmelpfennig, Claude Legentil, Didier Bourlès, Julien Cavero, Vincent Favier, Vincent Jomelli, Raphaelle Charrassin, Karim Keddadouche, Deborah Verfaillie, Hugues Goosse, Vincent Rinterknecht, Georges Aumaître, Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de géographie physique : Environnements Quaternaires et Actuels (LGP), Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Pôle de recherche pour l'organisation et la diffusion de l'information géographique (PRODIG (UMR_8586 / UMR_D_215 / UM_115)), Université Paris 1 Panthéon-Sorbonne (UP1)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Université Grenoble Alpes (UGA), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), Catholic Univ Louvain, Appl Microbiol Earth & Life Inst, Louvain La Neuve, Belgium, Partenaires INRAE, Université Paris 1 Panthéon-Sorbonne (UP1)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université Paris 1 Panthéon-Sorbonne (UP1), UCL - SST/ELI/ELIC - Earth & Climate, and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)
Subjects: geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Ecology, Evolution, Context (language use), Glacier, Geology, 010502 geochemistry & geophysics, Oceanography, 01 natural sciences, Glacier mass balance, Surface exposure dating, Behavior and Systematics, 13. Climate action, Moraine, Deglaciation, Physical geography, Ice caps, Glacial period, [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences
Abstract: The Cook Ice Cap (CIC) on the sub-Antarctic Kerguelen Islands recently experienced extremely negative surface mass balance. Further deglaciation could have important impacts on endemic and invasive fauna and flora. To put this exceptional glacier evolution into a multi-centennial-scale context, we refined the evolution of the CIC over the last millennium, investigated the associated climate conditions and explored its potential evolution by 2100 ce. A glaciological model, constrained by cosmic ray exposure dating of moraines, historical documents and recent direct mass balance observations, was used to simulate the ice-cap extents during different phases of advance and retreat between the last millennium and 2100 ce. Cosmogenic dating suggests glacial advance around the early Little Ice Age (LIA), consistent with findings from other sub-Antarctic studies, and the rather cold and humid conditions brought about by the negative phase of the Southern Annular Mode (SAM). This study contributes to our currently limited understanding of palaeoclimate for the early LIA in the southern Indian Ocean. Glaciological modelling and observations confirm the recent decrease in CIC extent linked to the intensification of the SAM. Although affected by large uncertainties, future simulations suggest a complete disappearance of CIC by the end of the century.
Published: 2021
Full Text: View/download PDF

19. Evolution of a debris-covered glacier in the Kerguelen Archipelago (49°S, 69°E) over the past 15,000 years constrained by in situ cosmogenic 36Cl dating

Author: Irene Schimmelpfennig, Vincent Favier, Joanna Charton, Vincent Jomelli, Fatima Mokadem, Fanny Brun, Didier Bourlès, Georges Aumaître, Karim Keddadouche, Deborah Verfaillie, and Adrien Gilbert
Subjects: In situ, geography, geography.geographical_feature_category, Archipelago, Glacier, Physical geography, Debris, Geology
Abstract: Debris-covered glaciers constitute a substantial part of the worldwide cryosphere (Scherler et al. 2018). However, their long-term response to multi-millennial climate variability has rarely been studied, in particular in the Southern Hemisphere. The presence of both debris-covered and debris-free glaciers on Kerguelen Archipelago (49°S, 69°E) offers therefore an excellent opportunity to investigate and compare long-term evolution of these two types of glaciers. To do so, we used the cosmogenic 36Cl surface dating method on moraine boulders that allows to establish temporal constraints of glacier oscillation. We provide here the first Late Glacial and Holocene glacier chronology of a still active debris-covered glacier from the archipelago: the Gentil Glacier. Results show that the Gentil Glacier advanced once at ~14.3 ka, i.e. during the Late Glacial (19.0 – 11.6 ka), and re-advanced during the Late Holocene at ~2.6 ka (Charton et al., 2020). Both debris-covered and debris-free glaciers experienced a broadly synchronous advance during the Late Glacial, that may be assigned to the Antarctic Cold Reversal event (14.5 – 12.9 ka) (Jomelli et al., 2017; 2018). This suggests that both types (debris-covered and debris-free) of glaciers at Kerguelen were sensitive to large amplitude temperature fluctuations recorded in Antarctic ice cores (WAIS divide Project Members, 2013), associated with increased precipitations (Van der Putten, 2015). However, during the Late Holocene, the advance at about ~2.6 ka was not observed on other glaciers and seems to be a specific response of the debris-covered Gentil Glacier, either related to distinct ice dynamics or an individual response to precipitation changes. Charton et al., 2020 : Ant. Sci. 1-13Jomelli et al., 2017 : Quat. Sci. Rev. 162, 128-144Jomelli et al., 2018 : Quat. Sci. Rev. 183, 110-123Scherler et al., 2018 : GRL. 45, 11,798-11,805Van der Putten et al., 2015 : Quat. Sci. Rev. 122, 142-157WAIS Divide Project Members, 2013: Nature. 500, 440-444
Published: 2021
Full Text: View/download PDF

20. Investigating the impact of the Southern Annular Mode on ice-shelf basal melt in Antarctica using a regional ocean model forced by reanalysis data

Author: Charles Pelletier, Hugues Goosse, Thierry Fichefet, Vincent Favier, Nicolas C. Jourdain, Quentin Dalaiden, Deborah Verfaillie, and Jonathan Wille
Subjects: geography, Basal (phylogenetics), geography.geographical_feature_category, Oceanography, Mode (statistics), Regional ocean model, Ice shelf, Geology
Abstract: The climate of polar regions is characterized by large fluctuations and has experienced dramatic changes over the past decades. In the high latitudes of the Southern Hemisphere, the patterns of changes in sea ice and ice sheet mass, in particular, are more complex than for the Northern Hemisphere. Some regions have warmed less than the global average with some sea-ice advance, in particular in the Ross Sea, while other regions such as the Bellingshausen Sea have warmed significantly and displayed sea-ice loss. The Antarctic Ice Sheet has also lost mass in the past decades, with a spectacular thinning and weakening of ice shelves, i.e., the floating extensions of the grounded ice sheet. Despite recent advances in observing and modelling the Antarctic climate, the mechanisms at the origin of those trends are very uncertain because of the limited amount of observations and the large biases of climate models in polar regions, in concert with the large internal variability prevailing in the Antarctic. One of the most important atmospheric modes of climate variability in the Southern Ocean is the Southern Annular Mode (SAM), which represents the position and the strength of the westerly winds. During years with a positive SAM index, lower sea level pressure at high latitudes and higher sea level pressure at low latitudes occur, resulting in a stronger pressure gradient and intensified Westerlies. However, the current knowledge of the impact of these fluctuations of the Westerlies on the Southern Ocean and Antarctic cryosphere is still limited. Some efforts have been devoted over the past few years to the impact of the SAM on the Antarctic sea ice and the surface mass balance of the ice sheet from an atmospheric-specific perspective. Recently, a few studies have focused on the local impact on ice-shelf basal melt in specific regions of Antarctica. However, to our knowledge, there is no such study of the impact of the SAM on ice-shelf basal melt at the pan-Antarctic scale. In this communication, we will address this issue by using simulations performed with the regional ocean and sea-ice model NEMO-LIM3.6 at a spatial resolution of 0.25° forced by the ERA5 reanalysis over the period 1979-2018 CE. The impact of both the annular and the non-annular components of the SAM on ice-shelf basal melt will be assessed through regressions and correlations between the seasonal or annual averages of the SAM index and the ice-shelf basal melt.
Published: 2021
Full Text: View/download PDF

21. Impact of ice sheet – ocean interactions on the Southern Ocean using fully coupled models over a circumpolar domain

Author: Hugues Goosse, Deborah Verfaillie, Frank Pattyn, Lars Zipf, Charles Pelletier, Pierre Mathiot, Konstanze Haubner, and Thierry Fichefet
Subjects: Fully coupled, geography, geography.geographical_feature_category, Geophysics, Circumpolar star, Ice sheet, Geology, Domain (software engineering)
Abstract: From at least 1979 up until 2016, the surface of the Southern Ocean cooled down, leading to a small Antarctic sea ice extent increase, which is in stark contrast with the Arctic Ocean. The attribution of the origin of these robust observations is still very uncertain. Among other phenomena, the direct, two-way interactions between the Southern Ocean and the Antarctic ice sheet, through basal melting of its numerous and large ice-shelf cavities, have been suggested as a potentially important contributor of this cooling. In order to address this question, we perform multidecadal coupled ice sheet – ocean numerical simulations relying on f.ETISh-v1.7 and NEMO3.6-LIM3 for simulating the Antarctic ice sheet and Southern Ocean (including sea ice), respectively. This presentation is twofold. First, we present the technical aspects of the coupling infrastructure (e.g. workflow and exchanged information in between models). Second, we investigate the ice sheet – ocean feedbacks on the Southern Ocean, their interactions, and the roles of the related physical mechanisms on the ocean surface cooling.
Published: 2021
Full Text: View/download PDF

22. A debris-covered glacier at Kerguelen (49°S, 69°E) over the past 15 000 years

Author: Georges Aumaître, Vincent Favier, Vincent Jomelli, Didier Bourlès, Joanna Charton, Adrien Gilbert, Irene Schimmelpfennig, Karim Keddadouche, Fanny Brun, Deborah Verfaillie, Fatima Mokadem, Université Paris 1 Panthéon-Sorbonne (UP1), Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Catholique de Louvain = Catholic University of Louvain (UCL), Université Grenoble Alpes (UGA), French INSU LEFE Glacepreker project, IPEV Kesaaco 1048 project, and ANR-11-LABX-0046,Dynamite,Dynamiques Territoriales et spatiales(2011)
Subjects: 010504 meteorology & atmospheric sciences, 010502 geochemistry & geophysics, Oceanography, 01 natural sciences, glacier fluctuations, Antarctic Cold Reversal, in situ cosmogenic chlorine-36 dating, Ice core, [SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry, Paleoclimatology, paleoclimate, Cryosphere, Glacial period, [SDU.STU.GM]Sciences of the Universe [physics]/Earth Sciences/Geomorphology, Ecology, Evolution, Behavior and Systematics, Holocene, 0105 earth and related environmental sciences, geography, geography.geographical_feature_category, sub-Antarctic, Geology, Glacier, 13. Climate action, Moraine, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Physical geography
Abstract: ASTER Team: Georges Aumaître, Didier L. Bourlès and Karim Keddadouche; International audience; Debris-covered glaciers constitute a large part of the world's cryosphere. However, little is known about their long-term response to multi-millennial climate variability, in particular in the Southern Hemisphere. Here, we provide first insights into the response of a debris-covered glacier to multi-millennial climate variability in the sub-Antarctic Kerguelen Archipelago, which can be compared to that of recently investigated debris-free glaciers. We focus on the Gentil Glacier and present thirteen new 36 Cl cosmic-ray exposure ages from moraine boulders. The Gentil Glacier experienced at least two glacial advancesthe first one during the Late Glacial (19.0-11.6 ka) at ~14.3 ka and the second one during the Late Holocene at ~2.6 ka. Both debris-covered and debris-free glaciers advanced broadly synchronously during the Late Glacial, most probably during the Antarctic Cold Reversal event (14.5-12.9 ka). This suggests that both glacier types at Kerguelen were sensitive to abrupt temperature changes recorded in Antarctic ice cores, associated with increased moisture. However, during the late Holocene, the advance at about ~2.6 ka was not observed in other glaciers and seems to be an original feature of the debris-covered Gentil Glacier, either related to distinct dynamics or distinct sensitivity to precipitation changes.
Published: 2021
Full Text: View/download PDF

23. Partitioning uncertainty components of an incomplete ensemble of climate projections using data augmentation

Author: Deborah Verfaillie, Guillaume Evin, Benoit Hingray, Nicolas Eckert, Juliette Blanchet, Samuel Morin, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'Etudes de la Neige (CEN), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), and Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Atmospheric Science, 010504 meteorology & atmospheric sciences, Computer science, [SDE.MCG]Environmental Sciences/Global Changes, 0208 environmental biotechnology, Bayesian probability, 02 engineering and technology, 7. Clean energy, 01 natural sciences, Physics::Geophysics, 020801 environmental engineering, 13. Climate action, Error analysis, Climatology, Key (cryptography), Climate model, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract: The quantification of internal variability and model uncertainty sources in Multi-scenario Multi-model Ensembles of climate experiments (MMEs) is a key issue. It is expected to both help decision makers to identify robust adaptation measures and scientists to identify where their efforts are needed to narrow uncertainty. The setup of available MMEs makes however uncertainty analyses difficult. In the popular single-time ANOVA approach for instance, a precise estimate of internal variability requires multiple members for each simulation chain (e.g. each emission scenario/climate model combination) but multiple members are typically available for a few chains only (Hingray et al. 2019). In almost all ensembles also, the matrix of available scenario/models combinations is incomplete making a precise estimate of the main effects of each model difficult (e.g. projections are typically missing for some GCM/RCM combinations) (Evin et al. 2019).We present QUALYPSO, a Bayesian approach developed to assess the different sources of uncertainty in incomplete MMEs (Evin et al. submitted). It is based on the quasi-ergodic assumption for transient climate projections and uses data augmentation (Hingray and Said, 2014). The climate response of each available simulation chain is first estimated with a trend model fitted to raw climate projections. Residuals from the climate change response are used to estimate the internal variability of the chain. Scenario uncertainty and the different components of model uncertainty (e.g. GCM uncertainty, RCM uncertainty) are then estimated with a Bayesian ANOVA model applied to the climate change responses of all available chains. The different parameters of the ANOVA model and the missing quantities associated to the missing chains (e.g. missing scenario/GCM/RCM combinations) are jointly estimated using data augmentation techniques.QUALYPSO presents many advantages over classical estimation approaches. It first exploits all available experiments, avoiding a dramatic loss of information (the classical case when standard approaches are applied; where the typical solution is to select a complete subset of climate experiments). Along with the estimation of missing data, it also provides an assessment of the estimation uncertainty and adequately propagates the uncertainty due to missing chains. With the explicit treatment of missing experiments, it is then expected to produce unbiased estimates of all parameters, in contrast to direct empirical estimates.QUALYPSO can be applied to any kind of climate variable and any kind of MMEs. We present examples of application for different hydroclimatic variables from different ensembles of projections including EUROCORDEX and CORDEX-Africa.Hingray, B., Saïd, M., 2014. Partitioning internal variability and model uncertainty components in a multimodel multireplicate ensemble of climate projections. J.Climate.Hingray, B., Blanchet, J., Evin, G. Vidal, J.P. 2019. Uncertainty components estimates in transient climate projections. Precision of estimators in the single time and time series approaches. Clim.Dyn.Evin, G., Hingray, B., Blanchet, J., Eckert, N., Morin, S., Verfaillie, D. 2019. Partitioning uncertainty components of an incomplete ensemble of climate projections using data augmentation. J.Climate.Evin, G., Hingray, B. Blanchet, J., Eckert, N., Menegoz, M. Morin, S. (revision). Partitioning uncertainty components of an incomplete ensemble of climate projections using smoothing splines. J.Climate.
Published: 2020
Full Text: View/download PDF

24. CSTools R package bringing state-of-the-arts postprocessing methods to seasonal-to-decadal forecast users

Author: Danila Volpi, Susanna Corti, Stefano Materia, Bert Van Schaeybroeck, Núria Pérez-Zanón, Marta Domínguez, Lauriane Batté, Silvia Terzago, Silvio Gualdi, Llorenç Lledó, Paola Marson, Deborah Verfaillie, Jost von Hardenberg, Nicolau Manubens, Verónica Torralba, Eroteida Sánchez, M. Carmen Alvarez-Castro, Louis-Philippe Caron, and F. Fabiano
Subjects: R package, Meteorology, Computer science, State (computer science), The arts
Abstract: The availability of climate data has never been larger, as evidenced by the development of the Copernicus Climate Change Service. However, availability of climate data does not automatically translate into usability and sophisticated post-processing is often required to turn these climate data into user-relevant climate information allowing them to develop and implement strategies of adaptation to climate variability and to trigger decisions. Developed under the umbrella of the ERA4CS Medscope project by multiple European partners, here we present an R package currently in development, which aims to provide tools to exploit dynamical seasonal forecasts such as to provide information relevant to public and private stakeholders at the seasonal timescale. This toolbox, called CSTools (short for Climate Service Tools), contains process-based methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination and multivariate verification, as well as basic and advanced tools to obtain tailored products. In addition to presenting some of the tools that are contained in the package, we also present a short overview of the development strategy adopted for this toolbox. The latter relies on a version controlling system established such as to allow scientists and developers to work within a common framework using a platform where they can exchange with other developers, test the various functionalities and discuss issues arising from the work, amongst other things. Furthermore, we will also present some vignettes, which are one of the mechanisms that allows users to understand and visualize the capabilities of CSTools. For instance, CSTools contains a step by step vignette showing how to use and visualize the output of MultivarRMSE, which gives an indication of the forecast performance (RMSE) for multiple variables simultaneously. While the extensive community of R users offers the opportunity of merging climate forecaster experts with final users, CSTools can also be used by other communities, such as Python users through the interface rpy. Finally, the publication of this package on CRAN (the Comprehensive R Archive Network) makes it easily accessible to interested users and ensures its proper functioning on different operational systems.
Published: 2020
Full Text: View/download PDF

25. On the reliability of decadal climate prediction

Author: Deborah Verfaillie, Francisco J. Doblas-Reyes, Markus G. Donat, Nuria Pérez-Zanón, Balakrishnan Solaraju-Murali, Verónica Torralba, and Simon Wild
Abstract: Decadal climate predictions and forced climate projections both provide potentially useful information to users for the next ten years. They only differ in the former being initialised with observations, while the latter is not. Bringing together initialised decadal climate predictions and non-initialised climate projections in order to provide seamless climate information for users over the next decades is a new challenging area of research. This can be achieved by comparing the forecast quality of global initialised and non-initialised simulations in their common prediction time horizons (up to 10 years ahead), and quantify in how far initialisation improves the forecast quality. Forecast quality has been usually explored through skill assessment. However, the impact of initialisation on the reliability, which quantifies the agreement between the predicted probabilities and observed relative frequencies of a given event, of decadal predictions has not yet been investigated sufficiently. Hence, users of probabilistic predictions are particularly sensitive to the potential lack of reliability which would imply that the probabilities are not trustworthy and this can have negative consequences for decision-making. In this communication, initialised decadal hindcasts (or retrospective forecasts) from 12 forecasting systems of the Coupled Model Intercomparison Project Phase 5 are compared to the corresponding non-initialised historical simulations in terms of reliability over their common period 1961-2005. We show that reliability varies greatly depending on the region or model ensemble analysed and on the correction applied. In particular, the North Atlantic and Europe stand out as regions where there is some added-value of initialised decadal hindcasts over non-initialised historical simulations in terms of reliability, mainly because of smaller biases and/or a better representation of the trend. Furthermore, we show that post-processed data display more reliable results, indicating that bias correction and calibration are fundamental to obtain reliable climate information.
Published: 2020
Full Text: View/download PDF

26. Multi-component ensembles of future meteorological and natural snow conditions for 1500 m altitude in the Chartreuse mountain range, Northern French Alps

Author: Michel Déqué, Samuel Morin, Deborah Verfaillie, Nicolas Eckert, Yves Lejeune, Matthieu Lafaysse, Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)
Subjects: 010504 meteorology & atmospheric sciences, 0208 environmental biotechnology, 02 engineering and technology, 01 natural sciences, Altitude, Natural hazard, lcsh:Environmental sciences, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, lcsh:GE1-350, geography, geography.geographical_feature_category, Global temperature, lcsh:QE1-996.5, 15. Life on land, Snowpack, Snow, CHARTREUSE MASSIF, 020801 environmental engineering, Water resources, lcsh:Geology, 13. Climate action, [SDU]Sciences of the Universe [physics], Climatology, [SDE]Environmental Sciences, Environmental science, Climate model, Mountain range
Abstract: This article investigates the climatic response of a series of indicators for characterizing annual snow conditions and corresponding meteorological drivers at 1500 m altitude in the Chartreuse mountain range in the Northern French Alps. Past and future changes were computed based on reanalysis and observations from 1958 to 2016, and using CMIP5–EURO-CORDEX GCM–RCM pairs spanning historical (1950–2005) and RCP2.6 (4), RCP4.5 and RCP8.5 (13 each) future scenarios (2006–2100). The adjusted climate model runs were used to drive the multiphysics ensemble configuration of the detailed snowpack model Crocus. Uncertainty arising from physical modeling of snow accounts for 20 % typically, although the multiphysics is likely to have a much smaller impact on trends. Ensembles of climate projections are rather similar until the middle of the 21st century, and all show a continuation of the ongoing reduction in average snow conditions, and sustained interannual variability. The impact of the RCPs becomes significant for the second half of the 21st century, with overall stable conditions with RCP2.6, and continued degradation of snow conditions for RCP4.5 and 8.5, the latter leading to more frequent ephemeral snow conditions. Changes in local meteorological and snow conditions show significant correlation with global temperature changes. Global temperature levels 1.5 and 2 ∘C above preindustrial levels correspond to a 25 and 32 % reduction, respectively, of winter mean snow depth with respect to the reference period 1986–2005. Larger reduction rates are expected for global temperature levels exceeding 2 ∘C. The method can address other geographical areas and sectorial indicators, in the field of water resources, mountain tourism or natural hazards.
Published: 2018
Full Text: View/download PDF

27. Changement climatique et stations de montagne alpines : impacts et stratégies d'adaptation

Author: Emmanuelle George, Pierre Spandre, Coralie Achin, Hugues François, Deborah Verfaillie, Samuel Morin, Laboratoire des EcoSystèmes et des Sociétés en Montagne (UR LESSEM), and Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)
Subjects: lcsh:GE1-350, climatic change, AMENAGEMENT DU TERRITOIRE, aménagement du territoire, land use planning, stratégie adaptative, mountains, adaptation, STATION DE SPORTS D'HIVER, winter sports resort, lcsh:TD1-1066, 13. Climate action, CHANGEMENT CLIMATIQUE, [SDE]Environmental Sciences, General Earth and Planetary Sciences, impact économique, lcsh:Environmental technology. Sanitary engineering, lcsh:Environmental sciences, MONTAGNE, General Environmental Science
Abstract: Today, mountain resorts structure the economy of the territories supporting them. However, global change, and particularly the reduction of snow cover linked to climate change, is questioning their future and placing them under an imperative of adaptation. The resorts and their stakeholders then implement two main types of strategies: on the one hand, making ski resorts more reliable in order to reduce their vulnerability and thus strengthen their viability, and on the other hand, diversifying tourism towards a model less dependent on snow resources alone. This contribution provides an overview of the work and research carried out on these issues, both in France and internationally.; Les stations de montagne structurent aujourd'hui l'économie des territoires les supportant. Le changement global, et particulièrement la réduction de l'enneigement lié au changement climatique, questionne cependant leur devenir et les place face à un impératif d'adaptation. Les stations et leurs acteurs mettent alors en oeuvre deux grands types de stratégies : d'une part, la fiabilisation des domaines skiables visant à réduire leur vulnérabilité et donc à renforcer leur viabilité, d'autre part, la diversification touristique vers un modèle moins dépendant de la seule ressource neige. Cette contribution propose un état des lieux des travaux et recherches menés sur ces questions, à l'échelle française comme internationale.
Published: 2019
Full Text: View/download PDF

28. La statistique, une boîte à outils complète pour quantifier l'incertitude Application aux projections climatiques en zone de montagne

Author: Guillaume Evin, Nicolas Eckert, Samuel Morin, Juliette Blanchet, Benoit Hingray, Deborah Verfaillie, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Hydrology and Land Improvement Laboratory (HYDRAM), Ecole Polytechnique Fédérale de Lausanne (EPFL), Centre d'Etudes de la Neige (CEN), Centre national de recherches météorologiques (CNRM), Météo France-Centre National de la Recherche Scientifique (CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), and Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])
Subjects: General Earth and Planetary Sciences, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS, General Environmental Science
Abstract: International audience
Published: 2019
Full Text: View/download PDF

29. Winter tourism and climate change in the Pyrenees and the French Alps: relevance of snowmaking as a technical adaptation

Author: Pierre Spandre, Hugues François, Deborah Verfaillie, Marc Pons, Matthieu Vernay, Matthieu Lafaysse, Emmanuelle George, and Samuel Morin
Abstract: Climate change is increasingly regarded as a threat for winter tourism due to the combined effect of decreasing natural snow amounts and decreasing suitable periods for snowmaking. The present work investigated the snow reliability of 175 ski resorts in France (Alps and Pyrenees), Spain and Andorra under past and future conditions using state-of-the-art snowpack modelling and climate projections. The natural snow reliability (i.e. without snowmaking) elevation showed a significant spatial variability in the reference period (1986–2005) and to be highly impacted by the on-going climate change. The technical reliability (i.e. including snowmaking) is projected to rise by 200 m to 300 m in the Alps and by 400 m to 600 m in the Pyrenees in the near future (2030–2050) compared to the reference period for all climate scenarios. While 99 % of ski lift infrastructures are reliable in the reference period thanks to snowmaking, a significant fraction (14 % to 25 %) may be considered "at risk" in the near future. Beyond the mid century, climate projections highly depend on the scenario with steady conditions compared to the near future (RCP 2.6) or continuous decrease of snow reliability (RCP 8.5). According to the "business as usual" scenario (RCP 8.5), there would no longer be any snow reliable ski resorts based on natural snow conditions in French Alps and Pyrenees (France, Spain and Andorra) at the end of the century (2080–2100). Only 24 resorts are projected to remain technically reliable, all being located in the Alps.
Published: 2018
Full Text: View/download PDF

30. The method ADAMONT v1.0 for statistical adjustment of climate projections applicable to energy balance land surface models

Author: Matthieu Lafaysse, Samuel Morin, Michel Déqué, and Deborah Verfaillie
Subjects: Meteorological reanalysis, 010504 meteorology & atmospheric sciences, Meteorology, lcsh:QE1-996.5, 0208 environmental biotechnology, Elevation, 02 engineering and technology, Grid, Snow, 01 natural sciences, Wind speed, 020801 environmental engineering, lcsh:Geology, Environmental science, Climate model, Precipitation, 0105 earth and related environmental sciences, Quantile
Abstract: We introduce the method ADAMONT v1.0 to adjust and disaggregate daily climate projections from a regional climate model against an observational dataset at hourly time resolution. The method uses a refined quantile mapping approach for statistical adjustment and an analogous method for sub-daily disaggregation. The method produces ultimately adjusted hourly time series of temperature, precipitation, wind speed, humidity, and short- and longwave radiation, which can in turn be used to force any energy balance land surface model. While the method is generic and can be employed on any appropriate observation time series, here we focus on the description and evaluation of the method in the French mountainous regions. The observational dataset used here is the SAFRAN meteorological reanalysis, which covers the entire French Alps split into 23 massifs, within which meteorological conditions are provided for several 300 m elevation bands. In order to evaluate the skills of the method itself, it is applied to the ALADIN-Climate v5 RCM using the ERA-Interim reanalysis as boundary conditions, for the time period from 1980 to 2010. Results of the ADAMONT method are compared to the SAFRAN reanalysis itself. Various evaluation criteria are used for temperature, precipitation, but also snow depth, which is computed by the SURFEX/ISBA-Crocus model using the meteorological driving data from either the adjusted RCM data, or the SAFRAN reanalysis itself. The evaluation addresses in particular the time transferability of the method (using various learning/application time periods), the impact of the RCM grid point selection procedure for each massif/altitude band configuration, and the inter-variable consistency of the adjusted meteorological data generated by the method. Results show that the performance of the method is satisfactory, with similar or even better evaluation metrics than alternative methods. However, results for air temperature are generally better than for precipitation. Results in terms of snow depth are satisfactory, which can be viewed as indicating a reasonably good inter-variable consistency of the meteorological data produced by the method. In terms of temporal transferability (evaluated over time periods of 15 years only), results depend on the learning period. In terms of RCM grid point selection technique, the use of a complex RCM grid points selection technique, taking into account horizontal but also altitudinal proximity to SAFRAN massif centre points/altitude couples, generally degrades evaluation metrics for high altitudes, compared to a simpler grid point selection method based on horizontal distance.
Published: 2018

31. Traiter l'incertitude des projections climatiques (essai)

Author: Juliette Blanchet, Nicolas Eckert, Samuel Morin, Benoit Hingray, Matthieu Lafaysse, Guillaume Evin, Deborah Verfaillie, Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Institut des Géosciences de l’Environnement (IGE), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre d'Etudes de la Neige (CEN), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), and Météo France-Centre National de la Recherche Scientifique (CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)
Subjects: 021110 strategic, defence & security studies, Geography, 010504 meteorology & atmospheric sciences, 13. Climate action, [SDU]Sciences of the Universe [physics], 0211 other engineering and technologies, Forestry, 02 engineering and technology, ALPES FRANCAISES, 01 natural sciences, 0105 earth and related environmental sciences
Abstract: Handling the uncertainty of climate change projections (essay) The uncertainties associated with climate projections cannot be ignored when those projections are used. They arise from uncertainties surrounding developments for greenhouse gases, uncertainties arising from the climate models and the impact models (hydrology, biodiversity etc.), as well as the natural variability of the climate. To describe these different sources of uncertainty, and take them into account is not easy for engineers and managers, who are more accustomed to reasoning in a determinist framework. This article aims to demonstrate that statistics offers a number of approaches which make it possible to use a given multiscenario, multimodel climate projection. The simplest propose a descriptive summary of the information, while the more complex approaches can test the significance of the expected changes, to separate the different causes of uncertainty and measure each one's contribution to the overall variability. The approach is illustrated by a set of projections for temperature, precipitation and mean snow depth for a mountainous region of the French Alps. It can be easily applied to any variable whose projections have been generated through an impact model which simulates the consequences of a set of climate projections for a given sector defined in social and ecosystem terms.
Published: 2018
Full Text: View/download PDF

32. Glacier extent in sub-Antarctic Kerguelen archipelago from MIS 3 period: Evidence from 36Cl dating

Author: Vincent Favier, Amaelle Landais, Vincent Jomelli, Fatima Mokadem, Claude Legentil, Deborah Verfaillie, Didier Bourlès, Daniel Brunstein, Irene Schimmelpfennig, Georges Aumaître, Karim Keddadouche, Vincent Rinterknecht, Laboratoire de géographie physique : Environnements Quaternaires et Actuels (LGP), Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Collège de France (CdF (institution))-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA), Institut des Géosciences de l’Environnement (IGE), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Glaces et Continents, Climats et Isotopes Stables (GLACCIOS), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Lieux, Identités, eSpaces, Activités (LISA), Université Pascal Paoli (UPP)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Panthéon-Sorbonne (UP1), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Collège de France (CdF)-Institut national des sciences de l'Univers (INSU - CNRS)-Aix Marseille Université (AMU)-Institut National de la Recherche Agronomique (INRA), Unité de Recherche Great Ice, Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), DEES, University of St Andrews [Scotland], Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )
Subjects: Archeology, 010504 meteorology & atmospheric sciences, MIS 2-4, Antarctic ice sheet, 010502 geochemistry & geophysics, 01 natural sciences, Kerguelen, Antarctic Cold Reversal, [SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry, Deglaciation, 36Cl cosmic-ray exposure dating, 14. Life underwater, Glacial period, [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology, [SDU.STU.GM]Sciences of the Universe [physics]/Earth Sciences/Geomorphology, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences, Global and Planetary Change, geography, geography.geographical_feature_category, Geology, Glacier, Last Glacial Maximum, Glacier fluctuations, 13. Climate action, Moraine, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Archipelago, Physical geography
Abstract: International audience; Documenting sub-Antarctic glacier variations during the local last glacial maximum is of major interest to better understand their sensitivity to atmospheric and oceanic temperature changes in conjunction with Antarctic ice sheet changes. However, data are sparse because evidence of earlier glacier extents is for most sub-Antarctic islands located offshore making their observation complex. Here, we present 22 cosmogenic 36Cl surface exposure ages obtained from five sites at Kerguelen to document the glacial history. The 36Cl ages from roche moutonnee surfaces, erratics and boulders collected on moraines span from 41.9 ± 4.4 ka to 14.3 ± 1.1 ka. Ice began to retreat on the eastern part of the main island before 41.4 ± 4.4 ka. Slow deglaciation occurred from ∼41 to ∼29 ka. There is no evidence of advances between 29 ka and the Antarctic Cold Reversal (ACR) period (∼14.5–12.9 ka) period. During the ACR, however, the Bontemps and possibly Belvedere moraines were formed by the advance of a Cook Ice Cap outlet glacier and a local glacier on the Presque Ile Jeanne d’Arc, respectively. This glacier evolution differs partly from that of glaciers in New Zealand and in Patagonia. These asynchronous glacier changes in the sub-Antarctic region are however in agreement with sea surface temperature changes recorded around Antarctica, which suggest differences in the climate evolution of the Indo-Pacific and Atlantic sectors of Antarctica.
Published: 2018
Full Text: View/download PDF

33. Clima y variabilidad climática en los Pirineos

Author: Ana Moreno, Blas Valero Garcés, Deborah Verfaillie, Didier Galop, Ernesto Rodriguez-Camino, Ernesto Tejedo, Fernando Barreiro-Lostres, Jean-Michel Soubeyroux, Jordi Cunillera, Cuadrat, José M., José-Maria Garcia Ruiz, Juan Ignacio López Moreno, Laura Trapero, Marc Pons, Marc Prohom, Saz, Miguel A., Penélope González-Sampériz, Petra Ramos, Pilar Amblar, Ramón Copons, Roberto Serrano-Notivoli, Simon Gascoin, Yolanda Luna, Instituto Pirenaico de Ecología-CSIC (IPE-CSIC), Instituto Pirenaico de Ecologia (IPE), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Météo France, Géographie de l'environnement (GEODE), Université Toulouse - Jean Jaurès (UT2J)-Centre National de la Recherche Scientifique (CNRS), Agencia Estatal de Meteorología (AEMet), Instituto Agroalimentario de Aragón (IA2) (UNIZAR-CITA), Servei Meteorològic de Catalunya (SMC), CENIMAT, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Instituto Pirenaico de Ecologìa = Pyrenean Institute of Ecology [Zaragoza] (IPE - CSIC), Météo-France Direction Interrégionale Sud-Est (DIRSE), Météo-France, Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Pyrénées, Variabilidad climática, changement climatique, le Quaternaire, Holocene, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climat, Cambio climático, [SHS.GEO]Humanities and Social Sciences/Geography, Clima, Adaptación al cambio climático
Abstract: International audience; Los cambios climáticos durante el Cuaternario (últimos 2,6 millones de años), y en particular la sucesión de periodos glaciales e interglaciales, han tenido importantes repercusiones en los procesos superficiales (modelado del paisaje, geomorfología) y en los ecosistemas pirenaicos, incluyendo la formación de grandes artesas y circos glaciares, depósitos glaciolacustres y formas de detalle.
Published: 2018

34. Supplementary material to 'Multi-components ensembles of future meteorological and natural snow conditions in the Northern French Alps'

Author: Deborah Verfaillie, Matthieu Lafaysse, Michel Déqué, Nicolas Eckert, Yves Lejeune, and Samuel Morin
Published: 2017
Full Text: View/download PDF

35. Multi-components ensembles of future meteorological and natural snow conditions in the Northern French Alps

Author: Samuel Morin, Matthieu Lafaysse, Nicolas Eckert, Michel Déqué, Deborah Verfaillie, and Yves Lejeune
Subjects: geography, geography.geographical_feature_category, Global temperature, business.industry, Snowpack, Snow, Altitude, Climatology, Natural hazard, Environmental science, Climate model, business, Hydropower, Mountain range
Abstract: This article introduces climate variations of annual-scale indicators for seasonal snow and its meteorological drivers, at 1500 m altitude in the Chartreuse mountain range in the Northern French Alps. Past and future variations were computed based on reanalysis and observations from 1958 to 2016, and using CMIP5/EURO-CORDEX GCM/RCM pairs spanning historical (1950–2005) and RCP2.6 (4), RCP4.5 and RCP8.5 (13 each) future scenarios (2006–2100). The adjusted climate model runs were used to drive the multiphysics ensemble configuration of the detailed snowpack model Crocus. Uncertainty arising from physical modeling of snow accounts for 20 % typically, although the multiphysics is likely to have a much smaller impact on trends. Ensembles of climate projections are rather similar until the middle of the 21st century, and all show a continuation of the ongoing reduction in mean interannual snow conditions, and maintained interannual variability. The impact of the RCP becomes significant for the second half of the 21st century, with overall stable conditions with RCP2.6, and continued degradation of snow conditions for RCP4.5 and 8.5, the latter leading to more frequent ephemeral snow conditions. Variations of local meteorological and snow conditions show significant correlation with global temperature variations. Global temperature levels on the order of 1.5 °C above pre-industrial levels correspond to a 25 % reduction of winter mean snow depth (reference 1986–2005). Even larger reduction is expected for global temperature levels exceeding 2 °C. The method can address other sectorial indicators, in the field of hydropower, mountain tourism or natural hazards.
Published: 2017
Full Text: View/download PDF

36. Response to Referee 2

Author: Deborah Verfaillie
Published: 2017
Full Text: View/download PDF

37. Response to Referee 1

Author: Deborah Verfaillie
Published: 2017
Full Text: View/download PDF

38. Supplementary material to 'The method ADAMONT v1.0 for statistical adjustment of climate projections applicable to energy balance land surface models'

Author: Deborah Verfaillie, Michel Déqué, Samuel Morin, and Matthieu Lafaysse
Published: 2017
Full Text: View/download PDF

39. Response to Referee 3

Author: Deborah Verfaillie
Published: 2017
Full Text: View/download PDF

40. Sub-Antartic glacier extensions in the Kerguelen region (49° S, Indian Ocean) over the past 24 000 years constrained by 36Cl moraine dating

Author: Georges Aumaître, Irene Schimmelpfennig, Vincent Jomelli, Fatima Mokadem, Didier Bourlès, Didier Swingedouw, Karim Keddadouche, Vincent Favier, Claude Legentil, Emmanuel Chapron, Deborah Verfaillie, Vincent Rinterknecht, Elisabeth Michel, Alain Jaouen, Daniel Brunstein, Laboratoire de géographie physique : Environnements Quaternaires et Actuels (LGP), Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut des Sciences de la Terre d'Orléans - UMR7327 (ISTO), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS), Géographie de l'environnement (GEODE), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Biogéosystèmes Continentaux - UMR7327, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Paléocéanographie (PALEOCEAN), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Environnements et Paléoenvironnements OCéaniques (EPOC), Observatoire aquitain des sciences de l'univers (OASU), Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), L'Institut polaire français Paul-Emile Victor (IPEV), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), CNRS-INSU, ANR-10-EQPX-0024,ASTER-CEREGE,PLATEFORME DE GEOCHIMIE ISOTOPIQUE ASTER/CEREGE(2010), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Panthéon-Sorbonne (UP1), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Aix Marseille Université (AMU)-Collège de France (CdF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), UMR 5805 Environnements et Paléoenvironnements Océaniques et Continentaux (EPOC), Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Collège de France (CdF)-Institut national des sciences de l'Univers (INSU - CNRS)-Aix Marseille Université (AMU)-Institut National de la Recherche Agronomique (INRA), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS), PSL Research University (PSL)-PSL Research University (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), ANR-10-EQPX-0024/10-EQPX-0024,ASTER-CEREGE,PLATEFORME DE GEOCHIMIE ISOTOPIQUE ASTER/CEREGE(2010), Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Collège de France (CdF (institution))-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA), Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Université Toulouse - Jean Jaurès (UT2J)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)
Subjects: Archeology, 010504 meteorology & atmospheric sciences, 36 cl cosmic-ray exposure dating, Climate change, 010502 geochemistry & geophysics, 01 natural sciences, Kerguelen, Ice core, Deglaciation, 36Cl cosmic-ray exposure dating, 14. Life underwater, Glacial period, [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Ecology, Evolution, Behavior and Systematics, Holocene, 0105 earth and related environmental sciences, Global and Planetary Change, geography, geography.geographical_feature_category, Geology, Last Glacial Maximum, Glacier, Glacier fluctuations, [SHS.GEO]Humanities and Social Sciences/Geography, Oceanography, 13. Climate action, Moraine, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDU]Sciences of the Universe [physics], late glacial
Abstract: International audience; Similar to many other regions in the world, glaciers in the southern sub-polar regions are currently retreating. In the Kerguelen Islands (49°S, 69°E), the mass balance of the Cook Ice Cap (CIC), the largest ice cap in the region, experimented dramatic shrinking between 1960 and 2013 with retreat rates among the highest in the world. This observation needs to be evaluated in a long-term context. However, data on the past glacier extents are sparse in the sub-Antartic regions. To investigate the deglaciation pattern since the Last Glacial Maximum (LGM) period, we present the first 13 cosmogenic 36Cl surface exposure ages from four sites in the Kerguelen Islands. The 36Cl ages from erratic and moraine boulders span from 24.4±2.7 ka to 0.3±0.1 ka. We combined these ages with extisting glacio-marine radiocarbon ages and bathymetric data to document the temporal and spatial changes of the island's glacial history. Ice began to retreat on the main island before 24.4±2.7 ka until around the time of the Antartic Cold Reversal (ACR) period (-14.5-12.9 ka), during which the Bontemps moraine was formed by the advance of a CIC outlet glacier. Deglacication continued during the Holocene probably until 3 ka with evidence of miror advances during the last millennium. This chronology is in pace with majeor changes in the ᵟ18O in a recent West Antartica ice core record, showing that Kerguelen Islands glaciers are particularly sensitive and relevant to document climate change in the southern polar regions.
Published: 2017
Full Text: View/download PDF

41. Déclin des deux plus grands glaciers des Alpes françaises au cours du XXIe siècle : Argentière et Mer de Glace

Author: Christian Vincent, Antoine Rabatel, Vincent Peyaud, Adrien Gilbert, Olivier Laarman, Etienne Berthier, Deborah Verfaillie, Jordi Bolibar, Delphine Six, Samuel Morin, Fabien Gillet-Chaulet, and Bruno Jourdain
Abstract: Des modelisations ont ete realisees sur les deux plus grands glaciers des Alpes francaises afin d'estimer leur evolution au cours du XXI e siecle. Pour un scenario climatique intermediaire avec reduction des emissions de gaz a effet de serre avant la fin du XXI e siecle (RCP 4.5), les simulations indiquent que le glacier d'Argentiere devrait disparaitre vers la fin du XXI e siecle et que la surface de la Mer de Glace pourrait diminuer de 80 %. Dans l'hypothese la plus pessimiste d'une croissance ininterrompue des emissions de gaz a effet de serre (RCP 8.5), la Mer de Glace pourrait disparaitre avant 2100 et le glacier d'Argentiere une vingtaine d'annees plus tot.
Published: 2019
Full Text: View/download PDF

42. The downscaling and adjustment method ADAMONT v1.0 for climate projections in mountainous regions applicable to energy balance land surface models

Author: Michel Déqué, Deborah Verfaillie, Matthieu Lafaysse, and Samuel Morin
Subjects: Altitude, Meteorology, Elevation, Environmental science, Climate model, Precipitation, Snow, Wind speed, Downscaling, Quantile
Abstract: We introduce a method – called ADAMONT (ADAptation of RCM outputs to MOuNTain regions) v1.0 – to downscale and adjust daily climate projections from a regional climate model against a regional reanalysis of hourly meteorological conditions using quantile mapping. The method produces adjusted hourly time series of temperature, precipitation, wind speed, humidity, and short- and longwave radiation, which can in turn be used to force any energy balance land surface model. The ADAMONT method is evaluated through its application to the ALADIN-Climate v5 RCM forced by the ERA-Interim reanalysis, compared to the SAFRAN reanalysis, used as the pseudo-observation database covering the entire French Alps split into 23 massifs within which meteorological conditions are provided for several elevation bands separated by 300 m altitude. Different evaluation criteria are analysed for temperature, precipitation, but also snow depth, which is computed by the SURFEX/ISBA-Crocus model using the meteorological driving data generated using this method. The impact of the learning period and of the method used to select neighbouring RCM grid points for each SAFRAN massif/altitude configuration is tested. The performance of the method is satisfying, with similar or even better evaluation metrics than previous literature findings. Results for temperature are generally better than for precipitation. Snow depth yields good results, which can be viewed as indicating a reasonably good inter-variable consistency of the meteorological data produced by the method. The temporal transferability of the method is assessed through the comparison of results obtained using different learning periods, and shows that the method is sensitive to the period considered due to the empirical treatment of values beyond the 99.5 th quantile. The use of a complex RCM grid points selection technique taking into account horizontal but also altitudinal proximity to SAFRAN massif centroids/altitude couples generally degrades evaluation metrics for high altitudes, compared to a simpler 2-dimensional proximity selection technique.
Published: 2016
Full Text: View/download PDF

43. Supplementary material to 'The downscaling and adjustment method ADAMONT v1.0 for climate projections in mountainous regions applicable to energy balance land surface models'

Author: Deborah Verfaillie, Michel Déqué, Samuel Morin, and Matthieu Lafaysse
Published: 2016
Full Text: View/download PDF

44. Atmospheric drying as the main driver of dramatic glacier wastage in the southern Indian Ocean

Author: Yoann Malbeteau, Deborah Verfaillie, Vincent Rinterknecht, Jennifer E. Kay, Hubert Gallée, Vincent Jomelli, Etienne Berthier, Martin Ménégoz, Daniel Brunstein, Young-Hyang Park, Vincent Favier, L. Ducret, Laboratoire d'Ingénierie des Matériaux (LIM), Centre National de la Recherche Scientifique (CNRS), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble [1985-2015] (OSUG [1985-2015]), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Géographie Physique, LGP, Laboratoire de géographie physique : Environnements Quaternaires et Actuels (LGP), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Panthéon-Sorbonne (UP1), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Département Milieux et Peuplements Aquatiques, Muséum national d'Histoire naturelle (MNHN), SUPA School of Physics and Astronomy [St Andrews], University of St Andrews [Scotland], University of St Andrews. Earth and Environmental Sciences, University of St Andrews. Marine Alliance for Science & Technology Scotland, University of St Andrews. Scottish Oceans Institute, Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado [Boulder]-National Oceanic and Atmospheric Administration (NOAA), Université Grenoble Alpes (UGA), Biogéochimie-Traceurs-Paléoclimat (BTP), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN), Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Météo France-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Université Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), SUPA School of Physics and Astronomy [University of St Andrews], University of St Andrews [Scotland]-Scottish Universities Physics Alliance (SUPA), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)
Subjects: 010504 meteorology & atmospheric sciences, Atmospheric circulation, [SDE.MCG]Environmental Sciences/Global Changes, 010502 geochemistry & geophysics, 01 natural sciences, Article, Latitude, Glacier mass balance, SDG 13 - Climate Action, Precipitation, General, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, GB, geography, GE, Multidisciplinary, geography.geographical_feature_category, Glacier, 3rd-DAS, Indian ocean, 13. Climate action, Climatology, [SDE]Environmental Sciences, GB Physical geography, Environmental science, Climate model, Storm track, GE Environmental Sciences
Abstract: This study was funded by IPEV-1048 GLACIOCLIM-KESAACO and LEFE-INSU KCRuMBLE programs, and the Agence Nationale de la Recherche through contract ANR-14-CE01-0001-01 (ASUMA). The ongoing retreat of glaciers at southern sub-polar latitudes is particularly rapid and widespread. Akin to northern sub-polar latitudes, this retreat is generally assumed to be linked to warming. However, no long-term and well-constrained glacier modeling has ever been performed to confirm this hypothesis. Here, we model the Cook Ice Cap mass balance on the Kerguelen Islands (Southern Indian Ocean, 49°S) since the 1850s. We show that glacier wastage during the 2000s in the Kerguelen was among the most dramatic on Earth. We attribute 77% of the increasingly negative mass balance since the 1960s to atmospheric drying associated with a poleward shift of the mid-latitude storm track. Because precipitation modeling is very challenging for the current generation of climate models over the study area, models incorrectly simulate the climate drivers behind the recent glacier wastage in the Kerguelen. This suggests that future glacier wastage projections should be considered cautiously where changes in atmospheric circulation are expected. Publisher PDF
Published: 2016
Full Text: View/download PDF

45. Un tour d’horizon rapide et incomplet des enjeux du dérèglement climatique pour les massifs de haute (Alpes) et de moyenne (Massif vosgien) montagne français, avec un focus sur la saison hivernale

Author: Giacona Florie, Nicolas Eckert, Brice Martin, Matthieu Lafaysse, Deborah Verfaillie, Samuel Morin, Coralie Achin, Hugues François, Emmanuel-Georges Marcelpoil, Pierre Spandre, Centre de Recherches sur les Économies, les Sociétés, les Arts et les Techniques (CRESAT), Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA)), Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Centre d'Etudes de la Neige (CEN), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Pacte, Laboratoire de sciences sociales (PACTE), Sciences Po Grenoble - Institut d'études politiques de Grenoble (IEPG)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Ecosystèmes montagnards (UR EMGR), Développement des territoires montagnards (UR DTGR), Météo France-Centre National de la Recherche Scientifique (CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Pacte, Laboratoire de sciences sociales, and Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Sciences Po Grenoble - Institut d'études politiques de Grenoble (IEPG)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)
Subjects: [SDE]Environmental Sciences, [SHS.GEO]Humanities and Social Sciences/Geography, [SHS.HIST]Humanities and Social Sciences/History, ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2016

46. Recent glacier decline in the Kerguelen Islands (49°S, 69°E) derived from modeling, field observations, and satellite data

Author: Yves Frenot, Marie Dumont, Vincent Favier, Vincent Rinterknecht, Daniel Brunstein, Martin Ménégoz, Adrien Gilbert, Hubert Gallée, Deborah Verfaillie, Vincent Jomelli, Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Météo-France Direction Interrégionale Sud-Est (DIRSE), Météo-France, Laboratoire de géographie physique : Environnements Quaternaires et Actuels (LGP), Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), DEES, University of St Andrews [Scotland], Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), IPEV program 1048 (GLACIOCLIM-KESAACO), INSU program LEFE-KCRuMBLE, Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), University of St Andrews. Earth and Environmental Sciences, University of St Andrews. Marine Alliance for Science & Technology Scotland, University of St Andrews. Scottish Oceans Institute, Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Météo France, Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Université Grenoble Alpes (UGA), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Panthéon-Sorbonne (UP1), and Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Centre National de la Recherche Scientifique (CNRS)
Subjects: GB, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, NDAS, Elevation, Glacier, Albedo, 010502 geochemistry & geophysics, Spatial distribution, Snow, 01 natural sciences, QE Geology, Glacier mass balance, Geophysics, 13. Climate action, Climatology, GB Physical geography, [SDE]Environmental Sciences, Snow line, QE, Moderate-resolution imaging spectroradiometer, Geology, 0105 earth and related environmental sciences, Earth-Surface Processes
Abstract: Date of Acceptance: 28/02/2015 The retreat of glaciers in the Kerguelen Islands (49°S, 69°E) and their associated climatic causes have been analyzed using field data and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images to validate a positive degree-day (PDD) model forced by data from local meteorological stations. Mass balance measurements made during recent field campaigns on the largest glacier of the Cook Ice Cap were compared to data from the early 1970s, providing a 40 year view of the differences in the spatial distribution of surface mass balance (SMB). To obtain additional regional data for the validation of our models, we analyzed MODIS images (2000-2012) to determine if our model was capable of reproducing variations in the transient snow line. The PDD model correctly simulated the variations in the snow line, the spatial variations in the SMB, and its trend with elevation. Yet current SMB values diverge from their classic linear representation with elevation, and stake data at high altitudes now display more negative SMB values than expected. By analyzing MODIS albedo, we observed that these values are caused by the disappearance of snow and associated feedback on melt rates. In addition, certain parts of Ampere Glacier could not be reproduced by the surface energy balance model because of overaccumulation due to wind deposition. Finally, the MODIS data, field data, and our models suggest that the acceleration of glacier wastage in Kerguelen is due to reduced net accumulation and an associated rise in the snow line since the 1970s. Publisher PDF
Published: 2015
Full Text: View/download PDF

47. Snow accumulation variability in Adelie Land (East Antarctica) derived from radar and firn core data. A 600 km transect from Dome C

Author: Michel Fily, Olivier Magand, E. Le Meur, Vincent Favier, Deborah Verfaillie, Laurent Arnaud, and Bruno Jourdain
Subjects: Dome (geology), Oceanography, law, Firn, East antarctica, Radar, Snow, Transect, Geology, law.invention
Abstract: Polar ice sheets mass balance is a timely topic intensively studied in the context of global change and sea-level rise. However, obtaining mass balance estimates in Antarctica in particular, remains difficult due to various logistical problems. In the framework of the TASTE-IDEA program, labeled as an International Polar Year project, continuous Ground Penetrating Radar (GPR) measurements were carried out during a traverse realised in Adelie Land (East Antarctica) during the 2008–2009 austral summer between the Italo-French Dome C (DC) polar plateau site and French Dumont D'Urville (DdU) coastal station. The aim of this study was to process and interpret GPR data in terms of snow accumulation, to analyse its spatial and temporal variability along the DC-DdU traverse and compare it with historical data and modeling. The emphasis has been put on the last 300 yr, from the pre-industrial to recent time period. Beta-radioactivity counting and gamma spectrometry were studied in cores at LGGE laboratory, providing a depth-age calibration for radar measurements. Over the 600 km of usable GPR data, depth and snow accumulation were determined with the help of three distinct layers visible on the radargrams (≈1730, 1799 and 1941 AD). Preliminary results reveal a gradual accumulation increase towards the coast and the occurrence of previously undocumented undulating structures between 300 and 600 km from DC. Results agree fairly well with data from previous studies and modeling. Concluding on temporal variations is difficult because of the margin of error introduced by density estimation. This study should have various applications such as for model validation.
Published: 2012
Full Text: View/download PDF

48. The circum-Antarctic ice-shelves respond to a more positive Southern Annular Mode with regionally varied melting

Author: 'Deborah Verfaillie

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Topic

Publication Year Range

Language

Publication Type

Journal

Database

Publisher

48 results on '"Deborah Verfaillie"'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources