Articles | Volume 18, issue 1
https://doi.org/10.5194/tc-18-475-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-18-475-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Feb 2024
Research article |
| 01 Feb 2024
| 01 Feb 2024
Cloud- and ice-albedo feedbacks drive greater Greenland Ice Sheet sensitivity to warming in CMIP6 than in CMIP5
Department of Geosciences, University of Oslo, Oslo, Norway
Stefan Hofer
Department of Geosciences, University of Oslo, Oslo, Norway
School of Geographical Sciences, University of Bristol, Bristol, United Kingdom
Trude Storelvmo
Department of Geosciences, University of Oslo, Oslo, Norway
Xavier Fettweis
Department of Geography, SPHERES research unit, University of Liège, Liège, Belgium
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Ragnhild Bieltvedt Skeie, Terje K. Berntsen, Ada Gjermundsen, Ragnar Bang Huseby, Gunnar Myhre, Dirk Olivié, and Trude Storelvmo
EGUsphere, https://doi.org/10.5194/egusphere-2026-4634, https://doi.org/10.5194/egusphere-2026-4634, 2026
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
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Climate sensitivity is a key quantity in climate science. We tested an observation-based method for estimating climate sensitivity by replacing observations with historical climate model simulations. Estimates varied substantially among simulations of the same model where only the initial conditions differed. Since the historical climate is only one realization of the Earth’s climate, this highlights that natural variability is an important source of uncertainty in observation-based estimates.
Christian Torres, Deniz Bozkurt, Vincent Favier, Victoire Buffet, Claudio Bravo, Xavier Fettweis, Thomas Dethinne, Antoine Rabatel, Maximiliano Viale, Sang-Jong Park, and Jorge Arigony-Neto
EGUsphere, https://doi.org/10.5194/egusphere-2026-3508, https://doi.org/10.5194/egusphere-2026-3508, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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We investigated periods when unusually warm conditions in Patagonia occurred at the same time as precipitation events on the Antarctic Peninsula. By combining observations and simulations, we identified 127 such events between 1980 and 2022. These events increased ice melt in Patagonia while enhancing accumulation on the Antarctic Peninsula, highlighting how large-scale weather patterns can simultaneously affect ice-covered regions in different ways.
Marco Tedesco, Racheet Matai, and Xavier Fettweis
The Cryosphere, 20, 4235–4253, https://doi.org/10.5194/tc-20-4235-2026, https://doi.org/10.5194/tc-20-4235-2026, 2026
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We developed a machine learning emulator of a climate model simulating melting over Greenland that performs as well as the original model but it is much faster. We show that this emulator can be used as powerful tools to complement regional climate models by enabling computationally efficient ensemble simulations and physically interpretable attribution of past and future Greenland surface melt. Development of regional climate models should go hand in hand with ML-based tools.
Guillaume Timmermans, Brice Noël, Christoph Kittel, Thomas Dethinne, Nicolas Ghilain, and Xavier Fettweis
EGUsphere, https://doi.org/10.5194/egusphere-2026-2341, https://doi.org/10.5194/egusphere-2026-2341, 2026
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We assess how well a regional climate model reproduces changes in the mass of the Greenland Ice Sheet due to surface processes, an important driver of sea level rise. By comparing model results with observations, we show that high-resolution simulations closely match reality. Coarser simulations are less detailed near the edges but remain reliable overall. A resolution of 10 kilometers provides a good balance between accuracy and computing cost for long-term projections.
Ian Simpson, Edward Hanna, Ryan S. Williams, Linh Luu, Andrew Orr, Julie Jones, Xavier Fettweis, Jose Abraham Torres Alavez, Ole Bøssing Christensen, Ella Gilbert, Sid Gumber, Christoph Kittel, Sihan Li, Damien Maure, Ruth Mottram, Tony Phillips, Willem Jan van de Berg, and Kristiina Verro
EGUsphere, https://doi.org/10.5194/egusphere-2026-2270, https://doi.org/10.5194/egusphere-2026-2270, 2026
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The warming trend in global temperatures has potential to result in accelerated break up of the Antarctic ice shelves, which would contribute to rising sea levels. Here we present a novel database of Antarctic extreme weather events over a selection of the Antarctic ice shelves. We examine air temperature, precipitation, wind and surface pressure. In addition, we examine trends in the frequency of extreme events and the links with weather patterns around Antarctica.
Raf Antwerpen, Marco Tedesco, Pierre Gentine, Willem Jan van de Berg, and Xavier Fettweis
The Cryosphere, 20, 3131–3149, https://doi.org/10.5194/tc-20-3131-2026, https://doi.org/10.5194/tc-20-3131-2026, 2026
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We study why Greenland ice melts faster by improving how ice brightness is represented. This is important because it controls how much sunlight is absorbed by the ice. Using satellite data and a new transparent machine learning method trained with climate model information, we capture how the shape of the ice sheet, temperature, and meltwater change ice brightness. Our approach outperforms existing climate models and can reduce uncertainty in future sea level rise projections.
Ian Castellanos, Martin Ménégoz, Juliette Blanchet, Julien Beaumet, Hubert Gallée, Eduardo Moreno-Chamarro, Chantal Staquet, and Xavier Fettweis
Earth Syst. Dynam., 17, 581–605, https://doi.org/10.5194/esd-17-581-2026, https://doi.org/10.5194/esd-17-581-2026, 2026
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The Alps host glaciers, distinct ecosystems, socio-economic interests and water resources that are being impacted by climate change. In this study, we aim at understanding how warming occurs in the Alps in projected scenarios and what physical processes drive it. We find under these scenarios that elevations around the snowline will warm faster than elsewhere, because snow retreats to higher elevations. Indeed, snow slows down warming due to its high albedo and the energy consumed to melt it.
Fredrik Boberg, Xavier Fettweis, Nicolaj Hansen, Ruth Mottram, and Michiel R. van den Broeke
The Cryosphere, 20, 2947–2960, https://doi.org/10.5194/tc-20-2947-2026, https://doi.org/10.5194/tc-20-2947-2026, 2026
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An ensemble of regional climate model simulations is used to estimate the 21st century change in precipitation on the Greenland ice sheet. For the end of the century, the change is in the range 40 to 170 Gt per year, depending on the emission scenario. Using annual values of 2 m air temperature and precipitation, we estimate an increase in precipitation of 35 Gt per year for every degree of warming.
Jonathon R. Preece, Patrick Alexander, Thomas L. Mote, Gabriel J. Kooperman, Xavier Fettweis, and Marco Tedesco
The Cryosphere, 20, 2871–2894, https://doi.org/10.5194/tc-20-2871-2026, https://doi.org/10.5194/tc-20-2871-2026, 2026
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Surface melt of the Greenland Ice Sheet has increased dramatically since the turn of the century, aided by an increase in persistent atmospheric circulation patterns that promote anomalously warm conditions. Through modeling experiments, this study shows that surface mass loss would have been reduced by 62% relative to historical conditions if this shift in atmospheric circulation would have occurred under the lower average temperatures of a preindustrial climate.
Ella Gilbert, José Abraham Torres-Alavez, Marte G. Hofsteenge, Willem Jan van de Berg, Fredrik Boberg, Ole Bøssing Christensen, Christiaan Timo van Dalum, Xavier Fettweis, Siddharth Gumber, Nicolaj Hansen, Christoph Kittel, Clara Lambin, Damien Maure, Ruth Mottram, Martin Olesen, Andrew Orr, Tony Phillips, Maurice van Tiggelen, Kristiina Verro, and Priscilla A. Mooney
The Cryosphere, 20, 2629–2658, https://doi.org/10.5194/tc-20-2629-2026, https://doi.org/10.5194/tc-20-2629-2026, 2026
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Here we present a new dataset – the PolarRES ensemble – of four state-of-the-art regional climate models, which capture the full complexity of Antarctica's climate. The ensemble out-performs other available tools, advancing our ability to explore Antarctic climate. While it still has limitations, the PolarRES ensemble offers a novel and exciting way of evaluating climate processes and features, and we encourage researchers to use the data, which are freely available.
Audrey Goutard, Marion Réveillet, Fanny Brun, Delphine Six, Kevin Fourteau, Charles Amory, Xavier Fettweis, Mathieu Fructus, Arbindra Khadka, and Matthieu Lafaysse
The Cryosphere, 20, 2393–2416, https://doi.org/10.5194/tc-20-2393-2026, https://doi.org/10.5194/tc-20-2393-2026, 2026
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A new scheme has been developed in a snowpack model (SURFEX/ISBA-Crocus), to consider the impact of liquid water dynamics on bare ice, including albedo feedback and refreezing. When applied to the Mera Glacier in Nepal, the model reveals strong seasonal effects on the energy and mass balance, with increased melting in dry seasons and significant refreezing during the monsoon. This development improves mass balance modeling under increasing rainfall and bare ice exposure due to climate warming.
Nina Elisabeth Larsgård, Tim Carlsen, Robert Oscar David, Filip Severin von der Lippe, Alfons Schwarzenboek, Harald Sodemann, and Trude Storelvmo
EGUsphere, https://doi.org/10.5194/egusphere-2026-1650, https://doi.org/10.5194/egusphere-2026-1650, 2026
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In-situ data from multiple research flights are combined to investigate the cloud evolution of Arctic marine cold air outbreaks during the ISLAS2022 campaign. We observe a cloud development similar to what other studies have shown: More liquid at cloud top close to the sea ice, and increased glaciation as clouds mature and deepen. This composite approach can be used by the community to further understand mCAO cloud evolution with increased confidence compared to single-flight analysis.
Benjamin Heurgue, Charles Amory, Christoph Kittel, Fredrik Boberg, Gaël Durand, Vincent Favier, Xavier Fettweis, Quentin Glaude, Heiko Goelzer, Nicolaj Hansen, Nicolas C. Jourdain, Ruth Mottram, Martin Olesen, Willem Jan Van de Berg, Michiel R. Van den Broeke, and René R. Wijngaard
EGUsphere, https://doi.org/10.5194/egusphere-2026-624, https://doi.org/10.5194/egusphere-2026-624, 2026
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We studied how the Antarctic ice sheet surface mass balance may change by 2100 using three high-resolution climate models forced by the same future climate scenario. While the models agree for present-day conditions, they project very different futures, especially over floating ice shelves. These differences mainly come from how melting, refreezing, and temperature are represented. Our results show that future sea level projections strongly depend on how well models simulate today’s climate.
Jenny Bjordal, Anthony A. Smith Jr., Henri Cornec, and Trude Storelvmo
Geosci. Model Dev., 19, 1337–1365, https://doi.org/10.5194/gmd-19-1337-2026, https://doi.org/10.5194/gmd-19-1337-2026, 2026
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We introduce NorESM2-DIAM (Norwegian Earth System Model version 2-Disaggregated Integrated Assessment Model), a first-of-its-kind tool linking a climate model with a high-resolution economic model to study how climate change, internal variability, and economic activity interact across the world. The model reveals strong regional differences and large annual swings in economic impacts, offers insights for climate policy discussions, and provides a strong foundation for future model development.
Filip Severin von der Lippe, Tim Carlsen, Trude Storelvmo, and Robert Oscar David
Atmos. Chem. Phys., 26, 1565–1585, https://doi.org/10.5194/acp-26-1565-2026, https://doi.org/10.5194/acp-26-1565-2026, 2026
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This paper investigates how clouds associated with Arctic marine cold air outbreaks (CAOs) respond to climate change. By utilizing machine learning methods and remote sensing data from the past 25 years, the study identifies trends indicating a shortening of the CAO season. This has implications for the Arctic energy balance, underscoring the importance of further investigating these clouds to understand the trajectory of future Arctic climate.
Horst Machguth, Andrew Tedstone, Peter Kuipers Munneke, Max Brils, Brice Noël, Nicole Clerx, Nicolas Jullien, Xavier Fettweis, and Michiel van den Broeke
The Cryosphere, 20, 427–452, https://doi.org/10.5194/tc-20-427-2026, https://doi.org/10.5194/tc-20-427-2026, 2026
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Due to increasing air temperatures, surface melt expands to higher elevations on the Greenland ice sheet. This is visible on satellite imagery in the form of rivers of meltwater running across the surface of the ice sheet. We compare model results of meltwater at high elevations on the ice sheet to satellite observations. We find that each of the models shows strengths and weaknesses. A detailed look into the model results reveals potential reasons for the differences between models.
Chloë Marie Paice, Xavier Fettweis, and Philippe Huybrechts
The Cryosphere, 20, 309–332, https://doi.org/10.5194/tc-20-309-2026, https://doi.org/10.5194/tc-20-309-2026, 2026
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To study Greenland ice sheet–atmosphere interactions, we coupled an ice sheet model to a regional climate model and performed simulations of differing coupling complexity over 1000 years under a high-warming climate scenario. They reveal that at first melt at the ice sheet margin is reduced by changing wind patterns. But over time, as the ice sheet melts and its surface lowers, precipitation patterns and cloudiness also change and amplify ice mass loss over the entire ice sheet.
Heiko Goelzer, Constantijn J. Berends, Fredrik Boberg, Gael Durand, Tamsin L. Edwards, Xavier Fettweis, Fabien Gillet-Chaulet, Quentin Glaude, Philippe Huybrechts, Sébastien Le clec'h, Ruth Mottram, Brice Noël, Martin Olesen, Charlotte Rahlves, Jeremy Rohmer, Michiel van den Broeke, and Roderik S. W. van de Wal
The Cryosphere, 19, 6887–6906, https://doi.org/10.5194/tc-19-6887-2025, https://doi.org/10.5194/tc-19-6887-2025, 2025
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We present an ensemble of ice sheet model projections for the Greenland ice sheet. The focus is on providing projections that improve our understanding of the range future sea-level rise and the inherent uncertainties over the next 100 to 300 years. Compared to earlier work we more fully account for some of the uncertainties in sea-level projections. We include a wider range of climate model output, more climate change scenarios and we extend projections schematically up to year 2300.
Thomas Dethinne, Nicolas Ghilain, Christoph Kittel, Benjamin Lecart, Xavier Fettweis, and François Jonard
EGUsphere, https://doi.org/10.5194/egusphere-2025-3907, https://doi.org/10.5194/egusphere-2025-3907, 2025
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This study replace standard vegetation input of a regional climate model with a satellite-based vegetation dataset to assess how vegetation influences climate during extreme events and to test the sensitivity of the model. The results show a non-linear sensitivity to vegetation, and using an observation-based vegetation input allows for a better representation of the extreme events, highlight the need for an advanced representation of vegetation in climate model to improve climate predictions.
Ove W. Haugvaldstad, Dirk Olivié, Trude Storelvmo, and Michael Schulz
Atmos. Chem. Phys., 25, 13199–13219, https://doi.org/10.5194/acp-25-13199-2025, https://doi.org/10.5194/acp-25-13199-2025, 2025
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Our study examines what would happen if desert dust in the atmosphere doubled, motivated by dust sedimentation records showing a large increase in dust levels since industrialization began. Using climate model simulations, we assess how more dust affects Earth's energy balance and rainfall. We found that models disagree on whether more dust overall cools or warms the planet. Additionally, more dust tends to reduce rainfall because it absorbs radiation and encourages the formation of ice clouds.
Lise Seland Graff, Jerry Tjiputra, Ada Gjermundsen, Andreas Born, Jens Boldingh Debernard, Heiko Goelzer, Yan-Chun He, Petra Margaretha Langebroek, Aleksi Nummelin, Dirk Olivié, Øyvind Seland, Trude Storelvmo, Mats Bentsen, Chuncheng Guo, Andrea Rosendahl, Dandan Tao, Thomas Toniazzo, Camille Li, Stephen Outten, and Michael Schulz
Earth Syst. Dynam., 16, 1671–1698, https://doi.org/10.5194/esd-16-1671-2025, https://doi.org/10.5194/esd-16-1671-2025, 2025
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The magnitude of future Arctic amplification is highly uncertain. Using the Norwegian Earth System Model, we explore the effect of improving the representation of clouds, ocean eddies, the Greenland ice sheet, sea ice, and ozone on the projected Arctic winter warming in a coordinated experiment set. These improvements all lead to enhanced projected Arctic warming, with the largest changes found in the sea ice retreat regions and the largest uncertainty found on the Atlantic side.
Kristiina Verro, Cecilia Äijälä, Roberta Pirazzini, Ruzica Dadic, Damien Maure, Willem Jan van de Berg, Giacomo Traversa, Christiaan T. van Dalum, Petteri Uotila, Xavier Fettweis, Biagio Di Mauro, and Milla Johansson
The Cryosphere, 19, 4409–4436, https://doi.org/10.5194/tc-19-4409-2025, https://doi.org/10.5194/tc-19-4409-2025, 2025
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Accurately representing Antarctic sea ice is essential for reliable climate and ocean model predictions. We evaluated how different models simulate the sea ice's sunlight reflectivity (called albedo) using field and satellite data. Models with simple albedo schemes performed well in limited cases but missed key processes. The advanced scheme in the MetROMS-UHel ocean model provided the most accurate results, including observed day–night albedo changes observed during a field campaign.
Weiran Li, Stef Lhermitte, Bert Wouters, Cornelis Slobbe, Max Brils, and Xavier Fettweis
The Cryosphere, 19, 3419–3442, https://doi.org/10.5194/tc-19-3419-2025, https://doi.org/10.5194/tc-19-3419-2025, 2025
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Due to recurrent melt and refreezing events in recent decades, the snow conditions over Greenland have changed. To observe this, we use a parameter (leading edge width; LeW) derived from satellite altimetry and analyse its spatial and temporal variations. By comparing the LeW variations with modelled firn parameters, we concluded that the 2012 melt event and the recent and increasingly frequent melt events have a long-lasting impact on the volume scattering of Greenland firn.
Zhengwen Yan, Jiangjun Ran, Pavel Ditmar, C. K. Shum, Roland Klees, Patrick Smith, and Xavier Fettweis
Earth Syst. Sci. Data, 17, 4253–4275, https://doi.org/10.5194/essd-17-4253-2025, https://doi.org/10.5194/essd-17-4253-2025, 2025
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The Gravity Recovery And Climate Experiment (GRACE) mission has greatly improved our understanding of changes in Earth's gravity field over time. A novel mass concentration (mascon) dataset, GCL-Mascon2024, was determined by leveraging the short-arc approach, advanced spatial constraints, a frequency-dependent noise processing strategy, and parameterization-integrating natural boundaries, aiming to enhance accuracy for monitoring mass transportation on Earth.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Tómas Zoëga, Trude Storelvmo, and Kirstin Krüger
Atmos. Chem. Phys., 25, 2989–3010, https://doi.org/10.5194/acp-25-2989-2025, https://doi.org/10.5194/acp-25-2989-2025, 2025
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We use an Earth system model to systematically investigate the climate response to high-latitude effusive volcanic eruptions as a function of eruption season and size, with a focus on the Arctic. We find that different seasons strongly modulate the climate response, with Arctic surface warming observed in winter and cooling in summer. Additionally, as eruptions increase in terms of sulfur dioxide emissions, the climate response becomes increasingly insensitive to variations in emission strength.
Ny Riana Randresihaja, Olivier Gourgue, Lauranne Alaerts, Xavier Fettweis, Jonathan Lambrechts, Miguel De Le Court, Marilaure Grégoire, and Emmanuel Hanert
EGUsphere, https://doi.org/10.5194/egusphere-2025-634, https://doi.org/10.5194/egusphere-2025-634, 2025
Preprint archived
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Coastal areas face rising flood threats as storms intensifies with climate change. With an advanced model of the Scheldt Estuary-North Sea, we studied how detailed atmospheric data must be to predict storm surge peaks in estuaries. We found that high-resolution atmospheric data gives the best results, and coarser data with same resolution as current global climate models give poorer results. We show that investing in localized, high-resolution atmospheric data can significantly improve results.
Astrid B. Gjelsvik, Robert O. David, Tim Carlsen, Franziska Hellmuth, Stefan Hofer, Zachary McGraw, Harald Sodemann, and Trude Storelvmo
Atmos. Chem. Phys., 25, 1617–1637, https://doi.org/10.5194/acp-25-1617-2025, https://doi.org/10.5194/acp-25-1617-2025, 2025
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Ice formation in clouds has a substantial impact on radiation and precipitation and must be realistically simulated in order to understand present and future Arctic climate. Rare aerosols known as ice-nucleating particles can play an important role in cloud ice formation, but their representation in global climate models is not well suited for the Arctic. In this study, the simulation of cloud phase is improved when the representation of these particles is constrained by Arctic observations.
Franziska Hellmuth, Tim Carlsen, Anne Sophie Daloz, Robert Oscar David, Haochi Che, and Trude Storelvmo
Atmos. Chem. Phys., 25, 1353–1383, https://doi.org/10.5194/acp-25-1353-2025, https://doi.org/10.5194/acp-25-1353-2025, 2025
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This article compares the occurrence of supercooled liquid-containing clouds (sLCCs) and their link to surface snowfall in CloudSat–CALIPSO, ERA5, and the CMIP6 models. Significant discrepancies were found, with ERA5 and CMIP6 consistently overestimating sLCC and snowfall frequency. This bias is likely due to cloud microphysics parameterization. This conclusion has implications for accurately representing cloud phase and snowfall in future climate projections.
Ragnhild Bieltvedt Skeie, Magne Aldrin, Terje K. Berntsen, Marit Holden, Ragnar Bang Huseby, Gunnar Myhre, and Trude Storelvmo
Earth Syst. Dynam., 15, 1435–1458, https://doi.org/10.5194/esd-15-1435-2024, https://doi.org/10.5194/esd-15-1435-2024, 2024
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Climate sensitivity and aerosol forcing are central quantities in climate science that are uncertain and contribute to the spread in climate projections. To constrain them, we use observations of temperature and ocean heat content as well as prior knowledge of radiative forcings over the industrialized period. The estimates are sensitive to how aerosol cooling evolved over the latter part of the 20th century, and a strong aerosol forcing trend in the 1960s–1970s is not supported by our analysis.
Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, Nina Raoult, Xavier Fettweis, and Philippe Conesa
The Cryosphere, 18, 5067–5099, https://doi.org/10.5194/tc-18-5067-2024, https://doi.org/10.5194/tc-18-5067-2024, 2024
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The evolution of the Greenland ice sheet is highly dependent on surface melting and therefore on the processes operating at the snow–atmosphere interface and within the snow cover. Here we present new developments to apply a snow model to the Greenland ice sheet. The performance of this model is analysed in terms of its ability to simulate ablation processes. Our analysis shows that the model performs well when compared with the MAR regional polar atmospheric model.
Britta Schäfer, Robert Oscar David, Paraskevi Georgakaki, Julie Thérèse Pasquier, Georgia Sotiropoulou, and Trude Storelvmo
Atmos. Chem. Phys., 24, 7179–7202, https://doi.org/10.5194/acp-24-7179-2024, https://doi.org/10.5194/acp-24-7179-2024, 2024
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Mixed-phase clouds, i.e., clouds consisting of ice and supercooled water, are very common in the Arctic. However, how these clouds form is often not correctly represented in standard weather models. We show that both ice crystal concentrations in the cloud and precipitation from the cloud can be improved in the model when aerosol concentrations are prescribed from observations and when more processes for ice multiplication, i.e., the production of new ice particles from existing ice, are added.
Alison Delhasse, Johanna Beckmann, Christoph Kittel, and Xavier Fettweis
The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024, https://doi.org/10.5194/tc-18-633-2024, 2024
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Aiming to study the long-term influence of an extremely warm climate in the Greenland Ice Sheet contribution to sea level rise, a new regional atmosphere–ice sheet model setup was established. The coupling, explicitly considering the melt–elevation feedback, is compared to an offline method to consider this feedback. We highlight mitigation of the feedback due to local changes in atmospheric circulation with changes in surface topography, making the offline correction invalid on the margins.
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
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How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
Laura J. Dietrich, Hans Christian Steen-Larsen, Sonja Wahl, Anne-Katrine Faber, and Xavier Fettweis
The Cryosphere, 18, 289–305, https://doi.org/10.5194/tc-18-289-2024, https://doi.org/10.5194/tc-18-289-2024, 2024
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The contribution of the humidity flux to the surface mass balance in the accumulation zone of the Greenland Ice Sheet is uncertain. Here, we evaluate the regional climate model MAR using a multi-annual dataset of eddy covariance measurements and bulk estimates of the humidity flux. The humidity flux largely contributes to the summer surface mass balance (SMB) in the accumulation zone, indicating its potential importance for the annual SMB in a warming climate.
Marco Tedesco, Paolo Colosio, Xavier Fettweis, and Guido Cervone
The Cryosphere, 17, 5061–5074, https://doi.org/10.5194/tc-17-5061-2023, https://doi.org/10.5194/tc-17-5061-2023, 2023
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We developed a technique to improve the outputs of a model that calculates the gain and loss of Greenland and consequently its contribution to sea level rise. Our technique generates “sharper” images of the maps generated by the model to better understand and quantify where losses occur. This has implications for improving models, understanding what drives the contributions of Greenland to sea level rise, and more.
Damien Maure, Christoph Kittel, Clara Lambin, Alison Delhasse, and Xavier Fettweis
The Cryosphere, 17, 4645–4659, https://doi.org/10.5194/tc-17-4645-2023, https://doi.org/10.5194/tc-17-4645-2023, 2023
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The Arctic is warming faster than the rest of the Earth. Studies have already shown that Greenland and the Canadian Arctic are experiencing a record increase in melting rates, while Svalbard has been relatively less impacted. Looking at those regions but also extending the study to Iceland and the Russian Arctic archipelagoes, we see a heterogeneity in the melting-rate response to the Arctic warming, with the Russian archipelagoes experiencing lower melting rates than other regions.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
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We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Casey J. Wall, Trude Storelvmo, and Anna Possner
Atmos. Chem. Phys., 23, 13125–13141, https://doi.org/10.5194/acp-23-13125-2023, https://doi.org/10.5194/acp-23-13125-2023, 2023
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Interactions between aerosol pollution and liquid clouds are one of the largest sources of uncertainty in the effective radiative forcing of climate over the industrial era. We use global satellite observations to decompose the forcing into components from changes in cloud-droplet number concentration, cloud water content, and cloud amount. Our results reduce uncertainty in these forcing components and clarify their relative importance.
Thomas Dethinne, Quentin Glaude, Ghislain Picard, Christoph Kittel, Patrick Alexander, Anne Orban, and Xavier Fettweis
The Cryosphere, 17, 4267–4288, https://doi.org/10.5194/tc-17-4267-2023, https://doi.org/10.5194/tc-17-4267-2023, 2023
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We investigate the sensitivity of the regional climate model
Modèle Atmosphérique Régional(MAR) to the assimilation of wet-snow occurrence estimated by remote sensing datasets. The assimilation is performed by nudging the MAR snowpack temperature. The data assimilation is performed over the Antarctic Peninsula for the 2019–2021 period. The results show an increase in the melt production (+66.7 %) and a decrease in surface mass balance (−4.5 %) of the model for the 2019–2020 melt season.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
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By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Andrew Gettelman, Hugh Morrison, Trude Eidhammer, Katherine Thayer-Calder, Jian Sun, Richard Forbes, Zachary McGraw, Jiang Zhu, Trude Storelvmo, and John Dennis
Geosci. Model Dev., 16, 1735–1754, https://doi.org/10.5194/gmd-16-1735-2023, https://doi.org/10.5194/gmd-16-1735-2023, 2023
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Clouds are a critical part of weather and climate prediction. In this work, we document updates and corrections to the description of clouds used in several Earth system models. These updates include the ability to run the scheme on graphics processing units (GPUs), changes to the numerical description of precipitation, and a correction to the ice number. There are big improvements in the computational performance that can be achieved with GPU acceleration.
Benjamin E. Smith, Brooke Medley, Xavier Fettweis, Tyler Sutterley, Patrick Alexander, David Porter, and Marco Tedesco
The Cryosphere, 17, 789–808, https://doi.org/10.5194/tc-17-789-2023, https://doi.org/10.5194/tc-17-789-2023, 2023
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We use repeated satellite measurements of the height of the Greenland ice sheet to learn about how three computational models of snowfall, melt, and snow compaction represent actual changes in the ice sheet. We find that the models do a good job of estimating how the parts of the ice sheet near the coast have changed but that two of the models have trouble representing surface melt for the highest part of the ice sheet. This work provides suggestions for how to better model snowmelt.
Jilu Li, Fernando Rodriguez-Morales, Xavier Fettweis, Oluwanisola Ibikunle, Carl Leuschen, John Paden, Daniel Gomez-Garcia, and Emily Arnold
The Cryosphere, 17, 175–193, https://doi.org/10.5194/tc-17-175-2023, https://doi.org/10.5194/tc-17-175-2023, 2023
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Alaskan glaciers' loss of ice mass contributes significantly to ocean surface rise. It is important to know how deeply and how much snow accumulates on these glaciers to comprehend and analyze the glacial mass loss process. We reported the observed seasonal snow depth distribution from our radar data taken in Alaska in 2018 and 2021, developed a method to estimate the annual snow accumulation rate at Mt. Wrangell caldera, and identified transition zones from wet-snow zones to ablation zones.
Raf M. Antwerpen, Marco Tedesco, Xavier Fettweis, Patrick Alexander, and Willem Jan van de Berg
The Cryosphere, 16, 4185–4199, https://doi.org/10.5194/tc-16-4185-2022, https://doi.org/10.5194/tc-16-4185-2022, 2022
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The ice on Greenland has been melting more rapidly over the last few years. Most of this melt comes from the exposure of ice when the overlying snow melts. This ice is darker than snow and absorbs more sunlight, leading to more melt. It remains challenging to accurately simulate the brightness of the ice. We show that the color of ice simulated by Modèle Atmosphérique Régional (MAR) is too bright. We then show that this means that MAR may underestimate how fast the Greenland ice is melting.
Britta Schäfer, Tim Carlsen, Ingrid Hanssen, Michael Gausa, and Trude Storelvmo
Atmos. Chem. Phys., 22, 9537–9551, https://doi.org/10.5194/acp-22-9537-2022, https://doi.org/10.5194/acp-22-9537-2022, 2022
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Cloud properties are important for the surface radiation budget. This study presents cold-cloud observations based on lidar measurements from the Norwegian Arctic between 2011 and 2017. Using statistical assessments and case studies, we give an overview of the macro- and microphysical properties of these clouds and demonstrate the capabilities of long-term cloud observations in the Norwegian Arctic from the ground-based lidar at Andenes.
Christoph Kittel, Charles Amory, Stefan Hofer, Cécile Agosta, Nicolas C. Jourdain, Ella Gilbert, Louis Le Toumelin, Étienne Vignon, Hubert Gallée, and Xavier Fettweis
The Cryosphere, 16, 2655–2669, https://doi.org/10.5194/tc-16-2655-2022, https://doi.org/10.5194/tc-16-2655-2022, 2022
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Model projections suggest large differences in future Antarctic surface melting even for similar greenhouse gas scenarios and warming rates. We show that clouds containing a larger amount of liquid water lead to stronger melt. As surface melt can trigger the collapse of the ice shelves (the safety band of the Antarctic Ice Sheet), clouds could be a major source of uncertainties in projections of sea level rise.
Sébastien Doutreloup, Xavier Fettweis, Ramin Rahif, Essam Elnagar, Mohsen S. Pourkiaei, Deepak Amaripadath, and Shady Attia
Earth Syst. Sci. Data, 14, 3039–3051, https://doi.org/10.5194/essd-14-3039-2022, https://doi.org/10.5194/essd-14-3039-2022, 2022
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This data set provides historical (1980–2014) and future (2015–2100) weather data for 12 cities in Belgium. This data set is intended for architects or building or energy designers. In particular, it makes available to all users hourly open-access weather data according to certain standards to recreate a Typical and an Extreme Meteorological Year. In addition, it provides hourly data on heatwaves from 1980 to 2100. Weather data were produced from the outputs of the MAR model simulations.
Kenneth D. Mankoff, Xavier Fettweis, Peter L. Langen, Martin Stendel, Kristian K. Kjeldsen, Nanna B. Karlsson, Brice Noël, Michiel R. van den Broeke, Anne Solgaard, William Colgan, Jason E. Box, Sebastian B. Simonsen, Michalea D. King, Andreas P. Ahlstrøm, Signe Bech Andersen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, https://doi.org/10.5194/essd-13-5001-2021, 2021
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We estimate the daily mass balance and its components (surface, marine, and basal mass balance) for the Greenland ice sheet. Our time series begins in 1840 and has annual resolution through 1985 and then daily from 1986 through next week. Results are operational (updated daily) and provided for the entire ice sheet or by commonly used regions or sectors. This is the first input–output mass balance estimate to include the basal mass balance.
Sorin Nicolae Vâjâiac, Andreea Calcan, Robert Oscar David, Denisa-Elena Moacă, Gabriela Iorga, Trude Storelvmo, Viorel Vulturescu, and Valeriu Filip
Atmos. Meas. Tech., 14, 6777–6794, https://doi.org/10.5194/amt-14-6777-2021, https://doi.org/10.5194/amt-14-6777-2021, 2021
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Warm clouds (with liquid droplets) play an important role in modulating the amount of incoming solar radiation to Earth’s surface and thus the climate. The most efficient way to study them is by in situ optical measurements. This paper proposes a new methodology for providing more detailed and reliable structural analyses of warm clouds through post-flight processing of collected data. The impact fine aerosol incorporation in water droplets might have on such measurements is also discussed.
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Short summary
The latest generation of climate models (Coupled Model Intercomparison Project Phase 6 – CMIP6) warm more over Greenland and the Arctic and thus also project a larger mass loss from the Greenland Ice Sheet (GrIS) compared to the previous generation of climate models (CMIP5). Our work suggests for the first time that part of the greater mass loss in CMIP6 over the GrIS is driven by a difference in the surface mass balance sensitivity from a change in cloud representation in the CMIP6 models.
The latest generation of climate models (Coupled Model Intercomparison Project Phase 6 – CMIP6)...
