Articles | Volume 16, issue 8
https://doi.org/10.5194/tc-16-3235-2022
© Author(s) 2022. 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-16-3235-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Aug 2022
Research article |
| 12 Aug 2022
| 12 Aug 2022
Improving model-satellite comparisons of sea ice melt onset with a satellite simulator
Abigail Smith
CORRESPONDING AUTHOR
Department of Atmospheric and Oceanic Sciences and Institute of Arctic and Alpine Research, University of Colorado Boulder, Boulder, Colorado, USA
now at: National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA
Alexandra Jahn
Department of Atmospheric and Oceanic Sciences and Institute of Arctic and Alpine Research, University of Colorado Boulder, Boulder, Colorado, USA
Clara Burgard
Max Planck Institute for Meteorology, Hamburg, Germany
now at: CNRS, IRD, Grenoble INP, IGE, Univ. Grenoble Alpes, 38000 Grenoble, France
Dirk Notz
Max Planck Institute for Meteorology, Hamburg, Germany
Center for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany
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Annelies Sticker, Francois Massonnet, Thierry Fichefet, Alexandra Jahn, David A. Bailey, and Benjamin Richaud
EGUsphere, https://doi.org/10.5194/egusphere-2026-4173, https://doi.org/10.5194/egusphere-2026-4173, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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Arctic sea ice has been shrinking for decades, and climate projections suggest this decline will continue, punctuated by episodes of rapid and abrupt sea ice loss. Using a climate model ensemble, our results show that thermodynamic processes, particularly melting at the base of the ice, are the dominant driver of these events. Dynamic processes contribute only a minor fraction. These findings lay the groundwork for developing early warning indicators of rapid Arctic sea ice loss.
Helen Ockenden, Clara Burgard, Pierre Mathiot, Christoph Kittel, Achille Gellens, Cécile Agosta, and Nicolas C. Jourdain
Geosci. Model Dev., 19, 7979–8002, https://doi.org/10.5194/gmd-19-7979-2026, https://doi.org/10.5194/gmd-19-7979-2026, 2026
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Since numerical computing is expensive, climate models must decide between having a high spatial resolution or running for long time periods. Here, we develop a simple neural network to emulate small-scale processes occurring beneath Antarctic ice shelves, which allows sub-shelf melt and ice–ocean interactions to be included in global ocean models which can run for multiple centuries. This neural network will help us to understand how ocean circulation may change in the future.
Andreas Wernecke, Thomas Lavergne, Stefan Kern, and Dirk Notz
The Cryosphere, 20, 3783–3793, https://doi.org/10.5194/tc-20-3783-2026, https://doi.org/10.5194/tc-20-3783-2026, 2026
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We analyse the types and size of uncertainties in satellite measurements of the global sea ice cover. These measurements give insights into the state of the climate system and quality of climate models. We derive uncertainties for one satellite product and compare it with other products. We find that offsets do play a role for measurements of the total sea ice cover, but also for estimates of its change. This calls for further investigations into the reasons for these offsets.
Christopher Wyburn-Powell and Alexandra Jahn
EGUsphere, https://doi.org/10.5194/egusphere-2026-2082, https://doi.org/10.5194/egusphere-2026-2082, 2026
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The Arctic Ocean is expected to become seasonally ice-free within a few decades. Previous research using one climate model showed that a major climate pattern called the Interdecadal Pacific Oscillation (IPO) could narrow predictions of when this will happen. Using a broader selection of the latest climate models, we show the IPO is not a reliable predictor of ice-free timing. However, the IPO may still influence the rate and location of Arctic sea ice reduction over the next two decades.
Gavin A. Schmidt, Kenneth D. Mankoff, Jonathan L. Bamber, Clara Burgard, Dustin Carroll, David M. Chandler, Violaine Coulon, Benjamin J. Davison, Matthew H. England, Paul R. Holland, Nicolas C. Jourdain, Qian Li, Juliana M. Marson, Pierre Mathiot, Clive R. McMahon, Twila A. Moon, Ruth Mottram, Sophie Nowicki, Anna Olivé Abelló, Andrew G. Pauling, Thomas Rackow, and Damien Ringeisen
Geosci. Model Dev., 18, 8333–8361, https://doi.org/10.5194/gmd-18-8333-2025, https://doi.org/10.5194/gmd-18-8333-2025, 2025
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The impact of increasing mass loss from the Greenland and Antarctic ice sheets has not so far been included in historical climate model simulations. This paper describes the protocols and data available for modeling groups to add this anomalous freshwater to their ocean modules to better represent the impacts of these fluxes on ocean circulation, sea ice, salinity and sea level.
Annelies Sticker, François Massonnet, Thierry Fichefet, Patricia DeRepentigny, Alexandra Jahn, David Docquier, Christopher Wyburn-Powell, Daphne Quint, Erica Shivers, and Makayla Ortiz
The Cryosphere, 19, 3259–3277, https://doi.org/10.5194/tc-19-3259-2025, https://doi.org/10.5194/tc-19-3259-2025, 2025
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Our study analyzes rapid ice loss events (RILEs) in the Arctic, which are significant reductions in sea ice extent. RILEs are expected throughout the year, varying in frequency and duration with the seasons. Our research gives a year-round analysis of their characteristics in climate models and suggests that summer RILEs could begin before the middle of the century. Understanding these events is crucial as they can have profound impacts on the Arctic environment.
Sian Megan Chilcott, Malte Meinshausen, and Dirk Notz
Geosci. Model Dev., 18, 4965–4982, https://doi.org/10.5194/gmd-18-4965-2025, https://doi.org/10.5194/gmd-18-4965-2025, 2025
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Climate models are expensive to run and often underestimate how sensitive Arctic sea ice is to climate change. To address this, we developed a simple model that emulates the response of sea ice to global warming. We find that the remaining carbon dioxide (CO2) emissions that will avoid a seasonally ice-free Arctic Ocean are lower than previous estimates of 821 Gt of CO2. Our model also provides insights into the future of winter sea ice, examining a larger ensemble than previously possible.
Erwin Lambert and Clara Burgard
The Cryosphere, 19, 2495–2505, https://doi.org/10.5194/tc-19-2495-2025, https://doi.org/10.5194/tc-19-2495-2025, 2025
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The effect of ocean warming on Antarctic ice-sheet melting is a major source of uncertainty in estimates of future sea level rise. We compare five melt models to show that ocean warming strongly increases melting. Despite their calibration based on present-day melting, the models disagree on the amount of melt increase. In some important regions, the difference reaches a factor 100. We conclude that using various melt models is important to accurately estimate uncertainties in future sea level rise.
Justine Caillet, Nicolas C. Jourdain, Pierre Mathiot, Fabien Gillet-Chaulet, Benoit Urruty, Clara Burgard, Charles Amory, Mondher Chekki, and Christoph Kittel
Earth Syst. Dynam., 16, 293–315, https://doi.org/10.5194/esd-16-293-2025, https://doi.org/10.5194/esd-16-293-2025, 2025
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Internal climate variability, resulting from processes intrinsic to the climate system, modulates the Antarctic response to climate change by delaying or offsetting its effects. Using climate and ice-sheet models, we highlight that irreducible internal climate variability significantly enlarges the likely range of Antarctic contribution to sea-level rise until 2100. Thus, we recommend considering internal climate variability as a source of uncertainty for future ice-sheet projections.
Saskia Kahl, Carolin Mehlmann, and Dirk Notz
The Cryosphere, 19, 129–141, https://doi.org/10.5194/tc-19-129-2025, https://doi.org/10.5194/tc-19-129-2025, 2025
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Ice mélange, a mixture of sea ice and icebergs, can impact sea-ice–ocean interactions. But climate models do not yet represent it due to computational limits. To address this shortcoming and include ice mélange into climate models, we suggest representing icebergs as particles. We integrate their feedback into mathematical equations used to model the sea-ice motion in climate models. The setup is computationally efficient due to the iceberg particle usage and enables a realistic representation.
Andreas Wernecke, Dirk Notz, Stefan Kern, and Thomas Lavergne
The Cryosphere, 18, 2473–2486, https://doi.org/10.5194/tc-18-2473-2024, https://doi.org/10.5194/tc-18-2473-2024, 2024
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The total Arctic sea-ice area (SIA), which is an important climate indicator, is routinely monitored with the help of satellite measurements. Uncertainties in observations of sea-ice concentration (SIC) partly cancel out when summed up to the total SIA, but the degree to which this is happening has been unclear. Here we find that the uncertainty daily SIA estimates, based on uncertainties in SIC, are about 300 000 km2. The 2002 to 2017 September decline in SIA is approx. 105 000 ± 9000 km2 a−1.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Gifford H. Miller, Simon L. Pendleton, Alexandra Jahn, Yafang Zhong, John T. Andrews, Scott J. Lehman, Jason P. Briner, Jonathan H. Raberg, Helga Bueltmann, Martha Raynolds, Áslaug Geirsdóttir, and John R. Southon
Clim. Past, 19, 2341–2360, https://doi.org/10.5194/cp-19-2341-2023, https://doi.org/10.5194/cp-19-2341-2023, 2023
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Receding Arctic ice caps reveal moss killed by earlier ice expansions; 186 moss kill dates from 71 ice caps cluster at 250–450, 850–1000 and 1240–1500 CE and continued expanding 1500–1880 CE, as recorded by regions of sparse vegetation cover, when ice caps covered > 11 000 km2 but < 100 km2 at present. The 1880 CE state approached conditions expected during the start of an ice age; climate models suggest this was only reversed by anthropogenic alterations to the planetary energy balance.
Lena Nicola, Dirk Notz, and Ricarda Winkelmann
The Cryosphere, 17, 2563–2583, https://doi.org/10.5194/tc-17-2563-2023, https://doi.org/10.5194/tc-17-2563-2023, 2023
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For future sea-level projections, approximating Antarctic precipitation increases through temperature-scaling approaches will remain important, as coupled ice-sheet simulations with regional climate models remain computationally expensive, especially on multi-centennial timescales. We here revisit the relationship between Antarctic temperature and precipitation using different scaling approaches, identifying and explaining regional differences.
Philipp de Vrese, Goran Georgievski, Jesus Fidel Gonzalez Rouco, Dirk Notz, Tobias Stacke, Norman Julius Steinert, Stiig Wilkenskjeld, and Victor Brovkin
The Cryosphere, 17, 2095–2118, https://doi.org/10.5194/tc-17-2095-2023, https://doi.org/10.5194/tc-17-2095-2023, 2023
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The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone. We used an adapted version of the Max Planck Institute (MPI) Earth System Model to show that differences in the representation of the soil hydrology in permafrost-affected regions could help explain a large part of this inter-model spread and have pronounced impacts on important elements of Earth systems as far to the south as the tropics.
Clara Burgard, Nicolas C. Jourdain, Ronja Reese, Adrian Jenkins, and Pierre Mathiot
The Cryosphere, 16, 4931–4975, https://doi.org/10.5194/tc-16-4931-2022, https://doi.org/10.5194/tc-16-4931-2022, 2022
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The ocean-induced melt at the base of the floating ice shelves around Antarctica is one of the largest uncertainty factors in the Antarctic contribution to future sea-level rise. We assess the performance of several existing parameterisations in simulating basal melt rates on a circum-Antarctic scale, using an ocean simulation resolving the cavities below the shelves as our reference. We find that the simple quadratic slope-independent and plume parameterisations yield the best compromise.
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Short summary
The timing of Arctic sea ice melt each year is an important metric for assessing how sea ice in climate models compares to satellite observations. Here, we utilize a new tool for creating more direct comparisons between climate model projections and satellite observations of Arctic sea ice, such that the melt onset dates are defined the same way. This tool allows us to identify climate model biases more clearly and gain more information about what the satellites are observing.
The timing of Arctic sea ice melt each year is an important metric for assessing how sea ice in...
