711 results on '"Fettweis, Xavier"'
Search Results
2. Increasing extreme melt in northeast Greenland linked to foehn winds and atmospheric rivers
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Mattingly, Kyle S., Turton, Jenny V., Wille, Jonathan D., Noël, Brice, Fettweis, Xavier, Rennermalm, Åsa K., and Mote, Thomas L.
- Published
- 2023
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3. Systematic framework for quantitative assessment of Indoor Air Quality under future climate scenarios; 2100s Projection of a Belgian case study
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Pourkiaei, Mohsen, Rahif, Ramin, Falzone, Claudia, Elnagar, Essam, Doutreloup, Sébastien, Martin, Justin, Fettweis, Xavier, Lemort, Vincent, Attia, Shady, and Romain, Anne-Claude
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- 2024
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4. Probabilistic forecasting for sizing in the capacity firming framework
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Dumas, Jonathan, Cornélusse, Bertrand, Fettweis, Xavier, Giannitrapani, Antonello, Paoletti, Simone, and Vicino, Antonio
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Mathematics - Optimization and Control ,Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper proposes a strategy to size a grid-connected photovoltaic plant coupled with a battery energy storage device within the \textit{capacity firming} specifications of the French Energy Regulatory Commission. In this context, the sizing problem is challenging due to the two-phase engagement control with a day-ahead nomination and an intraday control to minimize deviations from the planning. The two-phase engagement control is modeled with deterministic and stochastic approaches. The optimization problems are formulated as mixed-integer quadratic problems, using a Gaussian copula methodology to generate PV scenarios, to approximate the mixed-integer non-linear problem of the capacity firming. Then, a grid search is conducted to approximate the optimal sizing for a given selling price using both the deterministic and stochastic approaches. The case study is composed of PV production monitored on-site at the Li\`ege University (ULi\`ege), Belgium.
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- 2021
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5. Deep learning-based multi-output quantile forecasting of PV generation
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Dumas, Jonathan, Cointe, Colin, Fettweis, Xavier, and Cornélusse, Bertrand
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Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Systems and Control ,Statistics - Machine Learning - Abstract
This paper develops probabilistic PV forecasters by taking advantage of recent breakthroughs in deep learning. It tailored forecasting tool, named encoder-decoder, is implemented to compute intraday multi-output PV quantiles forecasts to efficiently capture the time correlation. The models are trained using quantile regression, a non-parametric approach that assumes no prior knowledge of the probabilistic forecasting distribution. The case study is composed of PV production monitored on-site at the University of Li\`ege (ULi\`ege), Belgium. The weather forecasts from the regional climate model provided by the Laboratory of Climatology are used as inputs of the deep learning models. The forecast quality is quantitatively assessed by the continuous ranked probability and interval scores. The results indicate this architecture improves the forecast quality and is computationally efficient to be incorporated in an intraday decision-making tool for robust optimization.
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- 2021
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6. A Probabilistic Forecast-Driven Strategy for a Risk-Aware Participation in the Capacity Firming Market: extended version
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Dumas, Jonathan, Cointe, Colin, Wehenkel, Antoine, Sutera, Antonio, Fettweis, Xavier, and Cornélusse, Bertrand
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Statistics - Applications ,Computer Science - Artificial Intelligence ,Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper addresses the energy management of a grid-connected renewable generation plant coupled with a battery energy storage device in the capacity firming market, designed to promote renewable power generation facilities in small non-interconnected grids. The core contribution is to propose a probabilistic forecast-driven strategy, modeled as a min-max-min robust optimization problem with recourse. It is solved using a Benders-dual cutting plane algorithm and a column and constraints generation algorithm in a tractable manner. A dynamic risk-averse parameters selection strategy based on the quantile forecasts distribution is proposed to improve the results. A secondary contribution is to use a recently developed deep learning model known as normalizing flows to generate quantile forecasts of renewable generation for the robust optimization problem. This technique provides a general mechanism for defining expressive probability distributions, only requiring the specification of a base distribution and a series of bijective transformations. Overall, the robust approach improves the results over a deterministic approach with nominal point forecasts by finding a trade-off between conservative and risk-seeking policies. The case study uses the photovoltaic generation monitored on-site at the University of Li\`ege (ULi\`ege), Belgium., Comment: Extended version of the paper accepted for publication in IEEE Transactions on Sustainable Energy
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- 2021
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7. Future projections of wind energy potentials in the arctic for the 21st century under the RCP8.5 scenario from regional climate models (Arctic-CORDEX)
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Akperov, Mirseid, Eliseev, Alexey V., Rinke, Annette, Mokhov, Igor I., Semenov, Vladimir A., Dembitskaya, Mariya, Matthes, Heidrun, Adakudlu, Muralidhar, Boberg, Fredrik, Christensen, Jens H., Dethloff, Klaus, Fettweis, Xavier, Gutjahr, Oliver, Heinemann, Günther, Koenigk, Torben, Sein, Dmitry, Laprise, René, Mottram, Ruth, Nikiéma, Oumarou, Sobolowski, Stefan, Winger, Katja, and Zhang, Wenxin
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- 2023
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8. Projected land ice contributions to twenty-first-century sea level rise
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Edwards, Tamsin L, Nowicki, Sophie, Marzeion, Ben, Hock, Regine, Goelzer, Heiko, Seroussi, Hélène, Jourdain, Nicolas C, Slater, Donald A, Turner, Fiona E, Smith, Christopher J, McKenna, Christine M, Simon, Erika, Abe-Ouchi, Ayako, Gregory, Jonathan M, Larour, Eric, Lipscomb, William H, Payne, Antony J, Shepherd, Andrew, Agosta, Cécile, Alexander, Patrick, Albrecht, Torsten, Anderson, Brian, Asay-Davis, Xylar, Aschwanden, Andy, Barthel, Alice, Bliss, Andrew, Calov, Reinhard, Chambers, Christopher, Champollion, Nicolas, Choi, Youngmin, Cullather, Richard, Cuzzone, Joshua, Dumas, Christophe, Felikson, Denis, Fettweis, Xavier, Fujita, Koji, Galton-Fenzi, Benjamin K, Gladstone, Rupert, Golledge, Nicholas R, Greve, Ralf, Hattermann, Tore, Hoffman, Matthew J, Humbert, Angelika, Huss, Matthias, Huybrechts, Philippe, Immerzeel, Walter, Kleiner, Thomas, Kraaijenbrink, Philip, Le clec’h, Sébastien, Lee, Victoria, Leguy, Gunter R, Little, Christopher M, Lowry, Daniel P, Malles, Jan-Hendrik, Martin, Daniel F, Maussion, Fabien, Morlighem, Mathieu, O’Neill, James F, Nias, Isabel, Pattyn, Frank, Pelle, Tyler, Price, Stephen F, Quiquet, Aurélien, Radić, Valentina, Reese, Ronja, Rounce, David R, Rückamp, Martin, Sakai, Akiko, Shafer, Courtney, Schlegel, Nicole-Jeanne, Shannon, Sarah, Smith, Robin S, Straneo, Fiammetta, Sun, Sainan, Tarasov, Lev, Trusel, Luke D, Van Breedam, Jonas, van de Wal, Roderik, van den Broeke, Michiel, Winkelmann, Ricarda, Zekollari, Harry, Zhao, Chen, Zhang, Tong, and Zwinger, Thomas
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Earth Sciences ,Physical Geography and Environmental Geoscience ,Climate Action ,General Science & Technology - Abstract
The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2-8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.
- Published
- 2021
9. Author Correction: Increasing extreme melt in northeast Greenland linked to foehn winds and atmospheric rivers
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Mattingly, Kyle S., Turton, Jenny V., Wille, Jonathan D., Noël, Brice, Fettweis, Xavier, Rennermalm, Åsa K., and Mote, Thomas L.
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- 2024
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10. Greenland ice sheet climate disequilibrium and committed sea-level rise
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Box, Jason E., Hubbard, Alun, Bahr, David B., Colgan, William T., Fettweis, Xavier, Mankoff, Kenneth D., Wehrlé, Adrien, Noël, Brice, van den Broeke, Michiel R., Wouters, Bert, Bjørk, Anders A., and Fausto, Robert S.
- Published
- 2022
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11. Complementarity Assessment of South Greenland Katabatic Flows and West Europe Wind Regimes
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Radu, David, Berger, Mathias, Fonteneau, Raphaël, Hardy, Simon, Fettweis, Xavier, Du, Marc Le, Panciatici, Patrick, Balea, Lucian, and Ernst, Damien
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Physics - Atmospheric and Oceanic Physics ,Computer Science - Computational Engineering, Finance, and Science - Abstract
Current global environmental challenges require vigorous and diverse actions in the energy sector. One solution that has recently attracted interest consists in harnessing high-quality variable renewable energy resources in remote locations, while using transmission links to transport the power to end users. In this context, a comparison of western European and Greenland wind regimes is proposed. By leveraging a regional atmospheric model specifically designed to accurately capture polar phenomena, local climatic features of southern Greenland are identified to be particularly conducive to extensive renewable electricity generation from wind. A methodology to assess how connecting remote locations to major demand centres would benefit the latter from a resource availability standpoint is introduced and applied to the aforementioned Europe-Greenland case study, showing superior and complementary wind generation potential in the considered region of Greenland with respect to selected European sites., Comment: Published in Elsevier Energy
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- 2018
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12. Critical Time Windows for Renewable Resource Complementarity Assessment
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Berger, Mathias, Radu, David, Fonteneau, Raphael, Henry, Robin, Glavic, Mevludin, Fettweis, Xavier, Du, Marc Le, Panciatici, Patrick, Balea, Lucian, and Ernst, Damien
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Physics - Physics and Society ,Computer Science - Computational Engineering, Finance, and Science - Abstract
This paper proposes a systematic framework to assess the complementarity of renewable resources over arbitrary geographical scopes and temporal scales which is particularly well-suited to exploit very large data sets of climatological data. The concept of critical time windows is introduced, and a spatio-temporal criticality indicator is proposed, consisting in a parametrised family of scalar indicators quantifying the complementarity between renewable resources in both space and time. The criticality indicator is leveraged to devise a family of optimisation problems identifying sets of locations with maximum complementarity under arbitrary geographical deployment constraints. The applicability of the framework is shown in a case study investigating the complementarity between the wind regimes in continental western Europe and southern Greenland, and its usefulness in a power system planning context is demonstrated. Besides showing that the occurrence of low wind power production events can be significantly reduced on a regional scale by exploiting diversity in local wind patterns, results highlight the fact that aggregating wind power production sites located on different continents may result in a lower occurrence of system-wide low wind power production events and indicate potential benefits of intercontinental electrical interconnections.
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- 2018
13. Evaluation Framework for Subdaily Rainfall Extremes Simulated by Regional Climate Model
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Van de Vyver, Hans, Van Schaeybroeck, Bert, De Troch, Rozemien, De Cruz, Lesley, Hamdi, Rafiq, Villanueva-Birriel, Cecille, Marbaix, Philippe, van Ypersele, Jean-Pascal, Wouters, Hendrik, Broucke, Sam Vanden, van Lipzig, Nicole P. M., Doutreloup, Sébastien, Wyard, Coraline, Scholzen, Chloé, Fettweis, Xavier, Caluwaerts, Steven, and Termonia, Piet
- Published
- 2021
14. Antwerpen_AGU2023_poster
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Antwerpen, Raf, primary, Tedesco, Marco, additional, Gentine, Pierre, additional, Fettweis, Xavier, additional, Alexander, Patrick, additional, and Berg, Willem Jan van de, additional
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- 2024
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15. Repeated subglacial jökulhlaups in northeastern Greenland revealed by CryoSat
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Gray, Laurence, primary, Burgess, David, additional, Copland, Luke, additional, Dow, Christine, additional, Fettweis, Xavier, additional, Fisher, David, additional, Kochtitzky, Will, additional, van Wychen, Wesley, additional, and Zheng, James, additional
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- 2024
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16. Discrepancies between observations and climate models of large-scale wind-driven Greenland melt influence sea-level rise projections
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Topál, Dániel, Ding, Qinghua, Ballinger, Thomas J., Hanna, Edward, Fettweis, Xavier, Li, Zhe, and Pieczka, Ildikó
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- 2022
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17. Intense atmospheric rivers can weaken ice shelf stability at the Antarctic Peninsula
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Wille, Jonathan D., Favier, Vincent, Jourdain, Nicolas C., Kittel, Christoph, Turton, Jenny V., Agosta, Cécile, Gorodetskaya, Irina V., Picard, Ghislain, Codron, Francis, Santos, Christophe Leroy-Dos, Amory, Charles, Fettweis, Xavier, Blanchet, Juliette, Jomelli, Vincent, and Berchet, Antoine
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- 2022
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18. Spatially consistent microbial biomass and future cellular carbon release from melting Northern Hemisphere glacier surfaces
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Stevens, Ian T., Irvine-Fynn, Tristram D. L., Edwards, Arwyn, Mitchell, Andrew C., Cook, Joseph M., Porter, Philip R., Holt, Tom O., Huss, Matthias, Fettweis, Xavier, Moorman, Brian J., Sattler, Birgit, and Hodson, Andy J.
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- 2022
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19. Arctic glaciers record wavier circumpolar winds
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Sasgen, Ingo, Salles, Annette, Wegmann, Martin, Wouters, Bert, Fettweis, Xavier, Noël, Brice P. Y., and Beck, Christoph
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- 2022
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20. Impact of climate change on nearly zero-energy dwelling in temperate climate: Time-integrated discomfort, HVAC energy performance, and GHG emissions
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Rahif, Ramin, Norouziasas, Alireza, Elnagar, Essam, Doutreloup, Sébastien, Pourkiaei, Seyed Mohsen, Amaripadath, Deepak, Romain, Anne-Claude, Fettweis, Xavier, and Attia, Shady
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- 2022
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21. Surface meltwater runoff routing through a coupled supraglacial-proglacial drainage system, Inglefield Land, northwest Greenland
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Li, Ya, Yang, Kang, Gao, Shuai, Smith, Laurence C., Fettweis, Xavier, and Li, Manchun
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- 2022
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22. Effects of the atmospheric forcing resolution on simulated sea ice and polynyas off Adélie Land, East Antarctica
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Huot, Pierre-Vincent, Kittel, Christoph, Fichefet, Thierry, Jourdain, Nicolas C., Sterlin, Jean, and Fettweis, Xavier
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- 2021
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23. On the importance of the humidity flux for the surface mass balance in the accumulation zone of the Greenland Ice Sheet
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Dietrich, Laura J., primary, Steen-Larsen, Hans Christian, additional, Wahl, Sonja, additional, Faber, Anne-Katrine, additional, and Fettweis, Xavier, additional
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- 2024
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24. Strong Summer Atmospheric Rivers Trigger Greenland Ice Sheet Melt through Spatially Varying Surface Energy Balance and Cloud Regimes
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Mattingly, Kyle S., Mote, Thomas L., Fettweis, Xavier, van As, Dirk, Van Tricht, Kristof, Lhermitte, Stef, Pettersen, Claire, and Fausto, Robert S.
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- 2020
25. Influence of ocean tides and ice shelves on ocean–ice interactions and dense shelf water formation in the D’Urville Sea, Antarctica
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Huot, Pierre-Vincent, Fichefet, Thierry, Jourdain, Nicolas C., Mathiot, Pierre, Rousset, Clément, Kittel, Christoph, and Fettweis, Xavier
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- 2021
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26. The recent warming trend in North Greenland
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Orsi, Anais J, Kawamura, Kenji, Masson‐Delmotte, Valerie, Fettweis, Xavier, Box, Jason E, Dahl‐Jensen, Dorthe, Clow, Gary D, Landais, Amaelle, and Severinghaus, Jeffrey P
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Climate Action ,Meteorology & Atmospheric Sciences - Published
- 2017
27. Twentieth century temperature and snow cover changes in the French Alps
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Beaumet, Julien, Ménégoz, Martin, Morin, Samuel, Gallée, Hubert, Fettweis, Xavier, Six, Delphine, Vincent, Christian, Wilhelm, Bruno, and Anquetin, Sandrine
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- 2021
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28. Increased variability in Greenland Ice Sheet runoff from satellite observations
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Slater, Thomas, Shepherd, Andrew, McMillan, Malcolm, Leeson, Amber, Gilbert, Lin, Muir, Alan, Munneke, Peter Kuipers, Noël, Brice, Fettweis, Xavier, van den Broeke, Michiel, and Briggs, Kate
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- 2021
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29. Critical time windows for renewable resource complementarity assessment
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Berger, Mathias, Radu, David, Fonteneau, Raphaël, Henry, Robin, Glavic, Mevludin, Fettweis, Xavier, Le Du, Marc, Panciatici, Patrick, Balea, Lucian, and Ernst, Damien
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- 2020
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30. Comment on hess-2023-223
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Fettweis, Xavier, primary
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- 2023
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31. Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula
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Dethinne, Thomas, primary, Glaude, Quentin, additional, Picard, Ghislain, additional, Kittel, Christoph, additional, Alexander, Patrick, additional, Orban, Anne, additional, and Fettweis, Xavier, additional
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- 2023
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32. Introduction
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Boyer, Tim, primary, Bartow-Gillies, Ellen, additional, Abida, A., additional, Ades, Melanie, additional, Adler, Robert, additional, Adusumilli, Susheel, additional, Agyakwah, W., additional, Ahmasuk, Brandon, additional, Aldeco, Laura S., additional, Alexe, Mihai, additional, Alfaro, Eric J., additional, Allan, Richard P., additional, Allgood, Adam, additional, Alves, Lincoln. M., additional, Amador, Jorge A., additional, Anderson, John, additional, Andrade, B., additional, Anneville, Orlane, additional, Aono, Yasuyuki, additional, Arguez, Anthony, additional, Arosio, Carlo, additional, Atkinson, C., additional, Augustine, John A., additional, Avalos, Grinia, additional, Azorin-Molina, Cesar, additional, Backensto, Stacia A., additional, Bader, Stephan, additional, Baez, Julian, additional, Baiman, Rebecca, additional, Ballinger, Thomas J., additional, Banwell, Alison F., additional, Bardin, M. Yu, additional, Barichivich, Jonathan, additional, Barnes, John E., additional, Barreira, Sandra, additional, Beadling, Rebecca L., additional, Beck, Hylke E., additional, Becker, Emily J., additional, Bekele, E., additional, Bellido, Guillem Martín, additional, Bellouin, Nicolas, additional, Benedetti, Angela, additional, Benestad, Rasmus, additional, Berne, Christine, additional, Berner, Logan. T., additional, Bernhard, Germar H., additional, Bhatt, Uma S., additional, Bhuiyan, A. E., additional, Bigalke, Siiri, additional, Biló, Tiago, additional, Bissolli, Peter, additional, Bjerke Jarle, W., additional, Blagrave, Kevin, additional, Blake, Eric S., additional, Blenkinsop, Stephen, additional, Blunden, Jessica, additional, Bochníček, Oliver, additional, Bock, Olivier, additional, Bodenstein, Barbara, additional, Bodin, Xavier, additional, Bosilovich, Michael, additional, Boucher, Olivier, additional, Bozkurt, Deniz, additional, Brettschneider, Brian, additional, Bringas, Francis G., additional, Bringas, Francis, additional, Buechler, Dennis, additional, Buehler, Stefan A., additional, Bukunt, Brandon, additional, Calderón, Blanca, additional, Camargo, Suzana J., additional, Campbell, Jayaka, additional, Campos, Diego, additional, Carrea, Laura, additional, Carter, Brendan R., additional, Cetinić, Ivona, additional, Chambers, Don P., additional, Chan, Duo, additional, Chandler, Elise, additional, Chang, Kai-Lan, additional, Chen, Hua, additional, Chen, Lin, additional, Cheng, Lijing, additional, Cheng, Vincent Y. S., additional, Chomiak, Leah, additional, Christiansen, Hanne H., additional, Christy, John R., additional, Chung, Eui-Seok, additional, Ciasto, Laura M., additional, Clarke, Leonardo, additional, Clem, Kyle R., additional, Clingan, Scott, additional, Coelho, Caio A.S., additional, Cohen, Judah L., additional, Coldewey-Egbers, Melanie, additional, Colwell, Steve, additional, Cooper, Owen R., additional, Cornes, Richard C., additional, Correa, Kris, additional, Costa, Felipe, additional, Covey, Curt, additional, Coy, Lawrence, additional, Créatux, Jean-François, additional, Crhova, Lenka, additional, Crimmins, Theresa, additional, Cronin, Meghan F., additional, Cropper, Thomas, additional, Crotwell, Molly, additional, Culpepper, Joshua, additional, Cunha, Ana P., additional, Cusicanqui, Diego, additional, Datta, Rajashree T., additional, Davis, Sean M., additional, De Bock, Veerle, additional, de Jeu, Richard A. M., additional, De Laat, Jos, additional, Decharme, Bertrand, additional, Degenstein, Doug, additional, Delaloye, Reynald, additional, Demircan, Mesut, additional, Derksen, Chris, additional, Deus, Ricardo, additional, Dhurmea, K. R., additional, Diamond, Howard J., additional, Dirkse, S., additional, Divine, Dmitry, additional, Dokulil, Martin T., additional, Donat, Markus G., additional, Dong, Shenfu, additional, Dorigo, Wouter A., additional, Drost Jensen, Caroline, additional, Druckenmiller, Matthew L., additional, Drumond, Paula, additional, du Plessis, Marcel, additional, Dugan, Hilary A., additional, Dulamsuren, Dashkhuu, additional, Dunmire, Devon, additional, Dunn, Robert J. H., additional, Durre, Imke, additional, Dusek, Robert, additional, Dutton, Geoff, additional, Duveiller, Gregory, additional, Ekici, Mithat, additional, Elias Chereque, Alesksandra, additional, ElKharrim, M., additional, Epstein, Howard E., additional, Espinoza, Jhan-Carlo, additional, Estilow, Thomas W., additional, Estrella, Nicole, additional, Fauchereau, Nicolas, additional, Fausto, Robert S., additional, Feely, Richard A., additional, Fenimore, Chris, additional, Fereday, David, additional, Fettweis, Xavier, additional, Fioletov, vitali E., additional, Flemming, Johannes, additional, Fogarty, Chris, additional, Fogt, Ryan L., additional, Forbes, Bruce C., additional, Foster, Michael J., additional, Franz, Bryan A., additional, Freeman, Natalie M., additional, Fricker, Helen A., additional, Frith, Stacey M., additional, Froidevaux, Lucien, additional, Frost, Gerald V. (JJ), additional, Fuhrman, Steven, additional, Füllekrug, Martin, additional, Ganter, Catherine, additional, Gao, Meng, additional, Gardner, Alex S., additional, Garforth, Judith, additional, Garg, Jay, additional, Gerland, Sebastian, additional, Gibbes, Badin, additional, Gille, Sarah T., additional, Gilson, John, additional, Gleason, Karin, additional, Gobron, Nadine, additional, Goetz, Scott J., additional, Goldenberg, Stanley B., additional, Goni, Gustavo, additional, Goodman, Steven, additional, Goto, Atsushi, additional, Grooß, Jens-Uwe, additional, Gruber, Alexander, additional, Gu, Guojun, additional, Guard, Charles “Chip” P., additional, Hagos, S., additional, Hahn, Sebastian, additional, Haimberger, Leopold, additional, Hall, Bradley D., additional, Hamlington, Benjamin D., additional, Hanna, Edward, additional, Hanssen-Bauer, Inger, additional, Harnos, Daniel S., additional, Harris, Ian, additional, He, Qiong, additional, Heim, Richard R., additional, Hellström, Sverker, additional, Hemming, Deborah L., additional, Hendricks, Stefan, additional, Hicks, J., additional, Hidalgo, Hugo G., additional, Hirschi, Martin, additional, Ho, Shu-peng (Ben), additional, Hobbs, W., additional, Holmes, Robert M., additional, Holzworth, Robert, additional, Hrbáček, Filip, additional, Hu, Guojie, additional, Hu, Zeng-Zhen, additional, Huang, Boyin, additional, Huang, Hongjie, additional, Hurst, Dale F., additional, Ialongo, Iolanda, additional, Inness, Antje, additional, Isaksen, Ketil, additional, Ishii, Masayoshi, additional, Jadra, Gerardo, additional, Jevrejeva, Svetlana, additional, John, Viju O., additional, Johns, W., additional, Johnsen, Bjørn, additional, Johnson, Bryan, additional, Johnson, Gregory C., additional, Jones, Philip D., additional, Jones, Timothy, additional, Josey, Simon A., additional, Jumaux, G., additional, Junod, Robert, additional, Kääb, Andreas, additional, Kabidi, K., additional, Kaiser, Johannes W., additional, Kaler, Robb S.A., additional, Kaleschke, Lars, additional, Kaufmann, Viktor, additional, Kazemi, Amin Fazl, additional, Keller, Linda M., additional, Kellerer-Pirklbauer, Andreas, additional, Kendon, Mike, additional, Kennedy, John, additional, Kent, Elizabeth C., additional, Kerr, Kenneth, additional, Khan, Valentina, additional, Khiem, Mai Van, additional, Kidd, Richard, additional, Kim, Mi Ju, additional, Kim, Seong-Joong, additional, Kipling, Zak, additional, Klotzbach, Philip J., additional, Knaff, John A., additional, Koppa, Akash, additional, Korshunova, Natalia N., additional, Kraemer, Benjamin M., additional, Kramarova, Natalya A., additional, Kruger, A. C., additional, Kruger, Andries, additional, Kumar, Arun, additional, L’Heureux, Michelle, additional, La Fuente, Sofia, additional, Laas, Alo, additional, Labe, Zachary M., additional, Lader, Rick, additional, Lakatos, Mónika, additional, Lakkala, Kaisa, additional, Lam, Hoang Phuc, additional, Lan, Xin, additional, Landschützer, Peter, additional, Landsea, Chris W., additional, Lang, Timothy, additional, Lankhorst, Matthias, additional, Lantz, Kathleen O., additional, Lara, Mark J., additional, Lavado-Casimiro, Waldo, additional, Lavers, David A., additional, Lazzara, Matthew A., additional, Leblanc, Thierry, additional, Lee, Tsz-Cheung, additional, Leibensperger, Eric M., additional, Lennard, Chris, additional, Leuliette, Eric, additional, Leung, Kinson H. Y., additional, Lieser, Jan L., additional, Likso, Tanja, additional, Lin, I-I., additional, Lindsey, Jackie, additional, Liu, Yakun, additional, Locarnini, Ricardo, additional, Loeb, Norman G., additional, Loomis, Bryant D., additional, Lorrey, Andrew M., additional, Loyola, Diego, additional, Lu, Rui, additional, Lumpkin, Rick, additional, Luo, Jing-Jia, additional, Luojus, Kari, additional, Lyman, John M., additional, Maberly, Stephen C., additional, Macander, Matthew J., additional, MacFerrin, Michael, additional, MacGilchrist, Graeme A., additional, MacLennan, Michelle L., additional, Madelon, Remi, additional, Magee, Andrew D., additional, Magnin, Florence, additional, Mamen, Jostein, additional, Mankoff, Ken D., additional, Manney, Gloria L., additional, Marcinonienė, Izolda, additional, Marengo, Jose A., additional, Marjan, Mohammadi, additional, Martínez, Ana E., additional, Massom, Robert A., additional, Matsuzaki, Shin-Ichiro, additional, May, Linda, additional, Mayer, Michael, additional, Mazloff, Matthew R., additional, McAfee, Stephanie A., additional, McBride, C., additional, McCabe, Matthew F., additional, McClelland, James W., additional, McPhaden, Michael J., additional, Mcvicar, Tim R., additional, Mears, Carl A., additional, Meier, Walter N., additional, Mekonnen, A., additional, Menzel, Annette, additional, Merchant, Christopher J., additional, Merrifield, Mark A., additional, Meyer, Michael F., additional, Meyers, Tristan, additional, Mikolajczyk, David E., additional, Miller, John B., additional, Miralles, Diego G., additional, Misevicius, Noelia, additional, Mishonov, Alexey, additional, Mitchum, Gary T., additional, Moat, Ben I., additional, Moesinger, Leander, additional, Moise, Aurel, additional, Molina-Carpio, Jorge, additional, Monet, Ghislaine, additional, Montzka, Stephan A., additional, Moon, Twila A., additional, Moore, G. W. K., additional, Mora, Natali, additional, Morán, Johnny, additional, Morehen, Claire, additional, Morice, Colin, additional, Mostafa, A. E., additional, Mote, Thomas L., additional, Mrekaj, Ivan, additional, Mudryk, Lawrence, additional, Mühle, Jens, additional, Müller, Rolf, additional, Nance, David, additional, Nash, Eric R., additional, Nerem, R. Steven, additional, Newman, Paul A., additional, Nicolas, Julien P., additional, Nieto, Juan J., additional, Noetzli, Jeannette, additional, Noll, Ben, additional, Norton, Taylor, additional, Nyland, Kelsey E., additional, O’Keefe, John, additional, Ochwat, Naomi, additional, Oikawa, Yoshinori, additional, Okunaka, Yuka, additional, Osborn, Timothy J., additional, Overland, James E., additional, Park, Taejin, additional, Parrington, Mark, additional, Parrish, Julia K., additional, Pasch, Richard J., additional, Pascual Ramírez, Reynaldo, additional, Pellet, Cécile, additional, Pelto, Mauri S., additional, Perčec Tadić, Melita, additional, Perovich, Donald K., additional, Petersen, Guðrún Nína, additional, Petersen, Kyle, additional, Petropavlovskikh, Irina, additional, Petty, Alek, additional, Pezza, Alexandre B., additional, Pezzi, Luciano P., additional, Phillips, Coda, additional, Phoenix, Gareth K., additional, Pierson, Don, additional, Pinto, Izidine, additional, Pires, Vanda, additional, Pitts, Michael, additional, Po-Chedley, Stephen, additional, Pogliotti, Paolo, additional, Poinar, Kristin, additional, Polvani, Lorenzo, additional, Preimesberger, Wolfgang, additional, Price, Colin, additional, Pulkkanen, Merja, additional, Purkey, Sarah G., additional, Qiu, Bo, additional, Quisbert, Kenny, additional, Quispe, Willy R., additional, Rajeevan, M., additional, Ramos, Andrea M., additional, Randel, William J., additional, Rantanen, Mika, additional, Raphael, Marilyn N., additional, Reagan, James, additional, Recalde, Cristina, additional, Reid, Phillip, additional, Rémy, Samuel, additional, Reyes Kohler, Alejandra J., additional, Ricciardulli, Lucrezia, additional, Richardson, Andrew D., additional, Ricker, Robert, additional, Robinson, David A., additional, Robjhon, M., additional, Rocha, Willy, additional, Rodell, Matthew, additional, Rodriguez Guisado, Esteban, additional, Rodriguez-Fernandez, Nemesio, additional, Romanovsky, Vladimir E., additional, Ronchail, Josyane, additional, Rosencrans, Matthew, additional, Rosenlof, Karen H., additional, Rösner, Benjamin, additional, Rösner, Henrieke, additional, Rozanov, Alexei, additional, Rozkošný, Jozef, additional, Rubek, Frans, additional, Rusanovskaya, Olga O., additional, Rutishauser, This, additional, Sabeerali, C. T., additional, Salinas, Roberto, additional, Sánchez-Lugo, Ahira, additional, Santee, Michelle L., additional, Santini, Marcelo, additional, Sato, Katsunari, additional, Sawaengphokhai, Parnchai, additional, Sayouri, A., additional, Scambos, Theodore, additional, Schenzinger, Verena, additional, Schimanke, Semjon, additional, Schlegel, Robert W., additional, Schmid, Claudia, additional, Schmid, Martin, additional, Schneider, Udo, additional, Schreck, Carl J., additional, Schultz, Cristina, additional, _, _, additional, Segele, Z. T., additional, Sensoy, Serhat, additional, Serbin, Shawn P., additional, Serreze, Mark C., additional, Setiawan, Amsari Mudzakir, additional, Sezaki, Fumi, additional, Sharma, Sapna, additional, Sharp, Jonathan D., additional, Sheffield, Gay, additional, Shi, Jia-Rui, additional, Shi, Lei, additional, Shiklomanov, Alexander I., additional, Shiklomanov, Nikolay I., additional, Shimaraeva, Svetlana V., additional, Shukla, R., additional, Siegel, David A., additional, Silow, Eugene A., additional, Sima, F., additional, Simmons, Adrian J., additional, Smeed, David A., additional, Smith, Adam, additional, Smith, Matthew M., additional, Smith, Sharon L., additional, Soden, Brian J., additional, Sofieva, Viktoria, additional, Souza, Everaldo, additional, Sparks, Tim H., additional, Spence-Hemmings, Jacqueline, additional, Spencer, Robert G. M., additional, Spillane, Sandra, additional, Sreejith, O. P., additional, Srivastava, A. K., additional, Stackhouse, Paul W., additional, Stammerjohn, Sharon, additional, Stauffer, Ryan, additional, Steinbrecht, Wolfgang, additional, Steiner, Andrea K., additional, Stella, Jose L., additional, Stephenson, Tannecia S., additional, Stradiotti, Pietro, additional, Strahan, Susan E., additional, Streletskiy, Dmitry A., additional, Surendran, Divya E., additional, Suslova, Anya, additional, Svendby, Tove, additional, Sweet, William, additional, Takahashi, Kiyotoshi, additional, Takemura, Kazuto, additional, Tank, Suzanne E., additional, Taylor, Michael A., additional, Tedesco, Marco, additional, Thackeray, Stephen J., additional, Thiaw, W. M., additional, Thibert, Emmanuel, additional, Thoman, Richard L., additional, Thompson, Andrew F., additional, Thompson, Philip R., additional, Tian-Kunze, Xiangshan, additional, Timmermans, Mary-Louise, additional, Timofeyev, Maxim A., additional, Tobin, Skie, additional, Tømmervik, Hans, additional, Tourpali, Kleareti, additional, Trescilo, Lidia, additional, Tretiakov, Mikhail, additional, Trewin, Blair C., additional, Triñanes, Joaquin A., additional, Trotman, Adrian, additional, Truchelut, Ryan E., additional, Trusel, Luke D., additional, Tye, Mari R., additional, van der A, Ronald, additional, van der Schalie, Robin, additional, van der Schrier, Gerard, additional, Van Hemert, Caroline, additional, Van Meerbeeck, Cedric J., additional, van vliet, Arnold J.H., additional, Vazife, Ahad, additional, Verburg, Piet, additional, Vernier, Jean-Paul, additional, Vimont, Isaac J., additional, Virts, Katrina, additional, Vivero, Sebastián, additional, Volkov, Denis L., additional, Vömel, Holger, additional, Vose, Russell S., additional, Walker, Donald (Skip) A., additional, Walsh, John E., additional, Wang, Bin, additional, Wang, Hui, additional, Wang, Muyin, additional, Wang, Ray H. J., additional, Wang, Xinyue, additional, Wanninkhof, Rik, additional, Warnock, Taran, additional, Weber, Mark, additional, Webster, Melinda, additional, Wehrlé, Adrian, additional, Wen, Caihong, additional, Westberry, Toby K., additional, Widlansky, Matthew J., additional, Wiese, David N., additional, Wild, Jeannette D., additional, Wille, Jonathan D., additional, Willems, An, additional, Willett, Kate M., additional, Williams, Earle, additional, Willis, J., additional, Wong, Takmeng, additional, Wood, Kimberly M., additional, Woolway, Richard Iestyn, additional, Xie, Ping-Ping, additional, Yang, Daqing, additional, Yin, Xungang, additional, Yin, Ziqi, additional, Zeng, Zhenzhong, additional, Zhang, Huai-min, additional, Zhang, Li, additional, Zhang, Peiqun, additional, Zhao, Lin, additional, Zhou, Xinjia, additional, Zhu, Zhiwei, additional, Ziemke, Jerry R., additional, Ziese, Markus, additional, Zolkos, Scott, additional, Zotta, Ruxandra M., additional, Zou, Cheng-Zhi, additional, Allen, Jessicca, additional, Camper, Amy V., additional, Haley, Bridgette O., additional, Hammer, Gregory, additional, Love-Brotak, S. Elizabeth, additional, Ohlmann, Laura, additional, Noguchi, Lukas, additional, Riddle, Deborah B., additional, and Veasey, Sara W., additional
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- 2023
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33. The Arctic
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Moon, T. A., primary, Thoman, R., additional, Druckenmiller, M. L., additional, Ahmasuk, Brandon, additional, Backensto, Stacia A., additional, Ballinger, Thomas J., additional, Benestad, Rasmus, additional, Berner, Logan. T., additional, Bernhard, Germar H., additional, Bhatt, Uma S., additional, Bigalke, Siiri, additional, BjerkeJarle, W., additional, Brettschneider, Brian, additional, Christiansen, Hanne H., additional, Cohen, Judah L., additional, Decharme, Bertrand, additional, Derksen, Chris, additional, Divine, Dmitry, additional, Drost, Jensen, additional, Druckenmiller, Matthew L., additional, EliasChereque, Alesksandra, additional, Epstein, Howard E., additional, Fausto, Robert S., additional, Fettweis, Xavier, additional, Fioletov, Vitali E., additional, Forbes, Bruce C., additional, Frost, Gerald V., additional, Gerland, Sebastian, additional, Goetz, Scott J., additional, Grooß, Jens-Uwe, additional, Hanna, Edward, additional, Hanssen-Bauer, Inger, additional, Hendricks, Stefan, additional, Holmes, Robert M., additional, Ialongo, Iolanda, additional, Isaksen, Ketil, additional, Johnsen, Bjørn, additional, Jones, Timothy, additional, Kaler, Robb S.A., additional, Kaleschke, Lars, additional, Kim, Seong-Joong, additional, Labe, Zachary M., additional, Lader, Rick, additional, Lakkala, Kaisa, additional, Lara, Mark J., additional, Lindsey, Jackie, additional, Loomis, Bryant D., additional, Luojus, Kari, additional, Macander, Matthew J., additional, Mamen, Jostein, additional, Mankoff, Ken D., additional, Manney, Gloria L., additional, McAfee, Stephanie A., additional, McClelland, James W., additional, Meier, Walter N., additional, Moon, Twila A., additional, Moore, G. W. K., additional, Mote, Thomas L., additional, Mudryk, Lawrence, additional, Müller, Rolf, additional, Nyland, Kelsey E., additional, Overland, James E., additional, Parrish, Julia K., additional, Perovich, Donald K., additional, Petersen, Guðrún Nína, additional, Petty, Alek, additional, Phoenix, Gareth K., additional, Poinar, Kristin, additional, Rantanen, Mika, additional, Ricker, Robert, additional, Romanovsky, Vladimir E., additional, Serbin, Shawn P., additional, Serreze, Mark C., additional, Sheffield, Gay, additional, Shiklomanov, Alexander I., additional, Shiklomanov, Nikolay I., additional, Smith, Sharon L., additional, Spencer, Robert G. M., additional, Streletskiy, Dmitry A., additional, Suslova, Anya, additional, Svendby, Tove, additional, Tank, Suzanne E., additional, Tedesco, Marco, additional, Thoman, Richard L., additional, Tian-Kunze, Xiangshan, additional, Timmermans, Mary-Louise, additional, Tømmervik, Hans, additional, Tretiakov, Mikhail, additional, Walker, Donald A., additional, Walsh, John E., additional, Wang, Muyin, additional, Webster, Melinda, additional, Wehrlé, Adrian, additional, Yang, Dedi, additional, Zolkos, Scott, additional, Allen, Jessicca, additional, Camper, Amy V., additional, Haley, Bridgette O., additional, Hammer, Gregory, additional, Love-Brotak, S., additional, Ohlmann, Laura, additional, Noguchi, Lukas, additional, Riddle, Deborah B., additional, and Veasey, Sara W., additional
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- 2023
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34. Accelerating changes in ice mass within Greenland, and the ice sheet’s sensitivity to atmospheric forcing
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Bevis, Michael, Harig, Christopher, Khan, Shfaqat A., Brown, Abel, Simons, Frederik J., Willis, Michael, Fettweis, Xavier, van den Broeke, Michiel R., Madsen, Finn Bo, Kendrick, Eric, Caccamise, Dana J., van Dam, Tonie, Knudsen, Per, and Nylen, Thomas
- Published
- 2019
35. Surface meltwater runoff on the Greenland ice sheet estimated from remotely sensed supraglacial lake infilling rate
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Yang, Kang, Smith, Laurence C., Fettweis, Xavier, Gleason, Colin J., Lu, Yao, and Li, Manchun
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- 2019
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36. Future projections of cyclone activity in the Arctic for the 21st century from regional climate models (Arctic-CORDEX)
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Akperov, Mirseid, Rinke, Annette, Mokhov, Igor I., Semenov, Vladimir A., Parfenova, Mariya R., Matthes, Heidrun, Adakudlu, Muralidhar, Boberg, Fredrik, Christensen, Jens H., Dembitskaya, Mariya A., Dethloff, Klaus, Fettweis, Xavier, Gutjahr, Oliver, Heinemann, Günther, Koenigk, Torben, Koldunov, Nikolay V., Laprise, René, Mottram, Ruth, Nikiéma, Oumarou, Sein, Dmitry, Sobolowski, Stefan, Winger, Katja, and Zhang, Wenxin
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- 2019
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37. Regional modeling of surface mass balance on the Cook Ice Cap, Kerguelen Islands (49∘S69∘E, 49∘S69∘E)
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Verfaillie, Deborah, Favier, Vincent, Gallée, Hubert, Fettweis, Xavier, Agosta, Cécile, and Jomelli, Vincent
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- 2019
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38. Complementarity assessment of south Greenland katabatic flows and West Europe wind regimes
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Radu, David, Berger, Mathias, Fonteneau, Raphaël, Hardy, Simon, Fettweis, Xavier, Le Du, Marc, Panciatici, Patrick, Balea, Lucian, and Ernst, Damien
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- 2019
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39. Modelling snowpack on ice surfaces with the ORCHIDEE land surface model: Application to the Greenland ice sheet.
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Charbit, Sylvie, Dumas, Christophe, Maignan, Fabienne, Ottlé, Catherine, Raoult, Nina, and Fettweis, Xavier
- Abstract
Current climate warming is accelerating mass loss from glaciers and ice sheets. In Greenland, the rates of mass changes are now dominated by changes in surface mass balance (SMB) due to increased surface melting. To improve the future sea-level rise projections, it is therefore critical to have an accurate estimate of the SMB, which depends on the representation of the processes occurring within the snowpack. The snow scheme (ES) implemented in the land surface model ORCHIDEE has not yet been adapted to ice-covered areas. Here, we present the preliminary developments we made to apply the ES model to glaciers and ice sheets. Our analysis mainly concerns the model's ability to represent ablation-related processes. At the regional scale, our results are compared to the MAR regional atmospheric model outputs and to MODIS albedo retrievals. Using different albedo parameterizations, we performed offline ES simulations forced by the MAR model over the 2000–2019 period. Our results reveal a strong sensitivity of the modeled SMB components to the albedo parameterization. Results inferred with albedo parameters obtained with a manual tuning approach present a very good agreement with the MAR outputs. Conversely, with the albedo parameterization used in the standard ORCHIDEE version, runoff and sublimation were underestimated. We also tested parameters found from a previous data assimilation experiment calibrating the ablation processes using MODIS snow albedo. While these parameters greatly improve the modelled albedo over the entire ice sheet, they degrade the other model outputs compared to those obtained with the manually-tuned approach. This is likely due to the model overfitting to the calibration albedo dataset without any constraint applied to the other processes controlling the state of the snowpack. This underlines the need for performing a "multi-objective" optimisation using auxiliary observations related to snowpack internal processes. Although there is still room for further improvements, the developments reported in the present study constitute an important advance in assessing the Greenland SMB with possible extension to mountain glaciers or the Antarctic ice sheet. [ABSTRACT FROM AUTHOR]
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- 2024
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40. Coupling MAR (Modèle Atmosphérique Régional) with PISM (Parallel Ice Sheet Model) mitigates the positive melt–elevation feedback.
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Delhasse, Alison, Beckmann, Johanna, Kittel, Christoph, and Fettweis, Xavier
- Subjects
ICE sheets ,GREENLAND ice ,TEMPERATURE lapse rate ,SURFACE topography ,ATMOSPHERIC models - Abstract
The Greenland Ice Sheet is a key contributor to sea level rise. By melting, the ice sheet thins, inducing higher surface melt due to lower surface elevations, accelerating the melt coming from global warming. This process is called the melt–elevation feedback and can be considered by using two types of models: either (1) atmospheric models, which can represent the surface mass balance (SMB), or SMB estimates resulting from simpler models such as positive degree day models or (2) ice sheet models representing the surface elevation evolution. The latter ones do not represent the surface mass balance explicitly as well as polar-oriented climate models. A new coupling between the MAR (Modèle Atmosphérique Régional) regional climate model and the PISM (Parallel Ice Sheet Model) ice sheet model is presented here following the CESM2 (Community Earth System Model; SSP5-8.5, Shared Socioeconomic Pathway) scenario until 2100 at the MAR lateral boundaries. The coupling is extended to 2200 with a stabilised climate (+7 ∘ C compared to 1961–1990) by randomly sampling the last 10 years of CESM2 to force MAR and reaches a sea level rise contribution of 64 cm. The fully coupled simulation is compared to a one-way experiment where surface topography remains fixed in MAR. However, the surface mass balance is corrected for the melt–elevation feedback when interpolated on the PISM grid by using surface mass balance vertical gradients as a function of local elevation variations (offline correction). This method is often used to represent the melt–elevation feedback and prevents a coupling which is too expensive in computation time. In the fully coupled MAR simulation, the ice sheet morphology evolution (changing slope and reducing the orographic barrier) induces changes in local atmospheric patterns. More specifically, wind regimes are modified, as well as temperature lapse rates, influencing the melt rate through modification of sensible heat fluxes at the ice sheet margins. We highlight mitigation of the melt lapse rate on the margins by modifying the surface morphology. The lapse rates considered by the offline correction are no longer valid at the ice sheet margins. If used (one-way simulation), this correction implies an overestimation of the sea level rise contribution of 2.5 %. The mitigation of the melt lapse rate on the margins can only be corrected by using a full coupling between an ice sheet model and an atmospheric model. [ABSTRACT FROM AUTHOR]
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- 2024
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41. Recent warming trends of the Greenland ice sheet documented by historical firn and ice temperature observations and machine learning.
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Vandecrux, Baptiste, Fausto, Robert S., Box, Jason E., Covi, Federico, Hock, Regine, Rennermalm, Åsa K., Heilig, Achim, Abermann, Jakob, van As, Dirk, Bjerre, Elisa, Fettweis, Xavier, Smeets, Paul C. J. P., Kuipers Munneke, Peter, van den Broeke, Michiel R., Brils, Max, Langen, Peter L., Mottram, Ruth, and Ahlstrøm, Andreas P.
- Subjects
GREENLAND ice ,ICE sheets ,MELTWATER ,ARTIFICIAL neural networks ,ICE sheet thawing ,MACHINE learning - Abstract
Surface melt on the Greenland ice sheet has been increasing in intensity and extent over the last decades due to Arctic atmospheric warming. Surface melt depends on the surface energy balance, which includes the atmospheric forcing but also the thermal budget of the snow, firn and ice near the ice sheet surface. The temperature of the ice sheet subsurface has been used as an indicator of the thermal state of the ice sheet's surface. Here, we present a compilation of 4612 measurements of firn and ice temperature at 10 m below the surface (T10m) across the ice sheet, spanning from 1912 to 2022. The measurements are either instantaneous or monthly averages. We train an artificial neural network model (ANN) on 4597 of these point observations, weighted by their relative representativity, and use it to reconstruct T10m over the entire Greenland ice sheet for the period 1950–2022 at a monthly timescale. We use 10-year averages and mean annual values of air temperature and snowfall from the ERA5 reanalysis dataset as model input. The ANN indicates a Greenland-wide positive trend of T10m at 0.2 ∘ C per decade during the 1950–2022 period, with a cooling during 1950–1985 (-0.4 ∘ C per decade) followed by a warming during 1985–2022 (+0.7 ∘ per decade). Regional climate models HIRHAM5, RACMO2.3p2 and MARv3.12 show mixed results compared to the observational T10m dataset, with mean differences ranging from -0.4 ∘ C (HIRHAM) to 1.2 ∘ C (MAR) and root mean squared differences ranging from 2.8 ∘ C (HIRHAM) to 4.7 ∘ C (MAR). The observation-based ANN also reveals an underestimation of the subsurface warming trends in climate models for the bare-ice and dry-snow areas. The subsurface warming brings the Greenland ice sheet surface closer to the melting point, reducing the amount of energy input required for melting. Our compilation documents the response of the ice sheet subsurface to atmospheric warming and will enable further improvements of models used for ice sheet mass loss assessment and reduce the uncertainty in projections. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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42. Cloud- and ice-albedo feedbacks drive greater Greenland Ice Sheet sensitivity to warming in CMIP6 than in CMIP5.
- Author
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Mostue, Idunn Aamnes, Hofer, Stefan, Storelvmo, Trude, and Fettweis, Xavier
- Subjects
GREENLAND ice ,ICE sheets ,GREENHOUSE gases ,ENERGY budget (Geophysics) ,AUTUMN ,ICE clouds - Abstract
The Greenland Ice Sheet (GrIS) has been losing mass since the 1990s as a direct consequence of rising temperatures and has been projected to continue to lose mass at an accelerating pace throughout the 21st century, making it one of the largest contributors to future sea-level rise. The latest Coupled Model Intercomparison Project Phase 6 (CMIP6) models produce a greater Arctic amplification signal and therefore also a notably larger mass loss from the GrIS when compared to the older CMIP5 projections, despite similar forcing levels from greenhouse gas emissions. However, it is also argued that the strength of regional factors, such as melt–albedo feedbacks and cloud-related feedbacks, will partly impact future melt and sea-level rise contribution, yet little is known about the role of these regional factors in producing differences in GrIS surface melt projections between CMIP6 and CMIP5. In this study, we use high-resolution (15 km) regional climate model simulations over the GrIS performed using the Modèle Atmosphérique Régional (MAR) to physically downscale six CMIP5 Representative Concentration Pathway (RCP) 8.5 and five CMIP6 Shared Socioeconomic Pathway (SSP) 5-8.5 extreme high-emission-scenario simulations. Here, we show a greater annual mass loss from the GrIS at the end of the 21st century but also for a given temperature increase over the GrIS, when comparing CMIP6 to CMIP5. We find a greater sensitivity of Greenland surface mass loss in CMIP6 centred around summer and autumn, yet the difference in mass loss is the largest during autumn with a reduction of 27.7 ± 9.5 Gt per season for a regional warming of +6.7 ∘ C and 24.6 Gt per season more mass loss than in CMIP5 RCP8.5 simulations for the same warming. Assessment of the surface energy budget and cloud-related feedbacks suggests a reduction in high clouds during summer and autumn – despite enhanced cloud optical depth during autumn – to be the main driver of the additional energy reaching the surface, subsequently leading to enhanced surface melt and mass loss in CMIP6 compared to CMIP5. Our analysis highlights that Greenland is losing more mass in CMIP6 due to two factors: (1) a (known) greater sensitivity to greenhouse gas emissions and therefore warmer temperatures and (2) previously unnotified cloud-related surface energy budget changes that enhance the GrIS sensitivity to warming. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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43. A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR.
- Author
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Tedesco, Marco, Colosio, Paolo, Fettweis, Xavier, and Cervone, Guido
- Subjects
ATMOSPHERIC models ,GREENLAND ice ,ICE sheets ,ATMOSPHERIC temperature ,SPATIAL resolution - Abstract
The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. Using the results obtained in the case of the SMB, surface and air temperature are assessed through the comparison of the modeled outputs with in situ and satellite measurement. The downscaled products show a considerable improvement in the case of the downscaled product with respect to the original coarse output, with the coefficient of determination (R2) increasing from 0.868 for the original MAR output to 0.935 for the SMB downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the slope and from the value -235 mm w.e. yr -1 (original) to -57 mm w.e. yr -1 (downscaled) in the case of the intercept, considerably improving upon results previously published in the literature. [ABSTRACT FROM AUTHOR]
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- 2023
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44. Characterising the ice sheet surface in Northeast Greenland using Sentinel-1 SAR data
- Author
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Shu, Qingying, primary, Killick, Rebecca, additional, Leeson, Amber, additional, Nemeth, Christopher, additional, Fettweis, Xavier, additional, Hogg, Anna, additional, and Leslie, David, additional
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- 2023
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45. Supplementary material to "Historical snow and ice temperature observations document the recent warming of the Greenland ice sheet"
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Vandecrux, Baptiste, primary, Fausto, Robert S., additional, Box, Jason E., additional, Covi, Federico, additional, Hock, Regine, additional, Rennermalm, Asa K., additional, Heilig, Achim, additional, Abermann, Jakob, additional, van As, Dirk, additional, Bjerre, Elisa, additional, Fettweis, Xavier, additional, Smeets, Paul C. J. P., additional, Kuipers Munneke, Peter, additional, van den Broeke, Michiel R., additional, Brils, Max, additional, Langen, Peter L., additional, Mottram, Ruth, additional, and Ahlstrøm, Andreas P., additional
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- 2023
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46. Historical snow and ice temperature observations document the recent warming of the Greenland ice sheet
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Vandecrux, Baptiste, primary, Fausto, Robert S., additional, Box, Jason E., additional, Covi, Federico, additional, Hock, Regine, additional, Rennermalm, Asa K., additional, Heilig, Achim, additional, Abermann, Jakob, additional, van As, Dirk, additional, Bjerre, Elisa, additional, Fettweis, Xavier, additional, Smeets, Paul C. J. P., additional, Kuipers Munneke, Peter, additional, van den Broeke, Michiel R., additional, Brils, Max, additional, Langen, Peter L., additional, Mottram, Ruth, additional, and Ahlstrøm, Andreas P., additional
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- 2023
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47. Coupled models may help clarify the drivers of observed icesheet melt season shift: comments on Liang et al. (2023)
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Fettweis, Xavier, primary
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- 2023
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48. Greenland ice sheet rainfall climatology, extremes and atmospheric river rapids
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Box, Jason E., primary, Nielsen, Kristian P., additional, Yang, Xiaohua, additional, Niwano, Masashi, additional, Wehrlé, Adrien, additional, van As, Dirk, additional, Fettweis, Xavier, additional, Køltzow, Morten A. Ø., additional, Palmason, Bolli, additional, Fausto, Robert S., additional, van den Broeke, Michiel R., additional, Huai, Baojuan, additional, Ahlstrøm, Andreas P., additional, Langley, Kirsty, additional, Dachauer, Armin, additional, and Noël, Brice, additional
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- 2023
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49. Evaluating Model Simulations of Twentieth-Century Sea Level Rise. Part I : Global Mean Sea Level Change
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Slangen, Aimée B. A., Meyssignac, Benoit, Agosta, Cecile, Champollion, Nicolas, Church, John A., Fettweis, Xavier, Ligtenberg, Stefan R. M., Marzeion, Ben, Melet, Angelique, Palmer, Matthew D., Richter, Kristin, Roberts, Christopher D., and Spada, Giorgio
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- 2017
50. The CORDEX.be initiative as a foundation for climate services in Belgium
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Termonia, Piet, Van Schaeybroeck, Bert, De Cruz, Lesley, De Troch, Rozemien, Caluwaerts, Steven, Giot, Olivier, Hamdi, Rafiq, Vannitsem, Stéphane, Duchêne, François, Willems, Patrick, Tabari, Hossein, Van Uytven, Els, Hosseinzadehtalaei, Parisa, Van Lipzig, Nicole, Wouters, Hendrik, Vanden Broucke, Sam, van Ypersele, Jean-Pascal, Marbaix, Philippe, Villanueva-Birriel, Cecille, Fettweis, Xavier, Wyard, Coraline, Scholzen, Chloé, Doutreloup, Sébastien, De Ridder, Koen, Gobin, Anne, Lauwaet, Dirk, Stavrakou, Trissevgeni, Bauwens, Maite, Müller, Jean-François, Luyten, Patrick, Ponsar, Stéphanie, Van den Eynde, Dries, and Pottiaux, Eric
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- 2018
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