Articles | Volume 21, issue 1
https://doi.org/10.5194/cp-21-115-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-21-115-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Jan 2025
Research article |
| 16 Jan 2025
| 16 Jan 2025
A novel conceptual model for Dansgaard–Oeschger event dynamics based on ice-core data
Jonathan Ortved Melcher
Physics of Ice, Climate and Earth, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
Sune Halkjær
Physics of Ice, Climate and Earth, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
Peter Ditlevsen
Physics of Ice, Climate and Earth, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
Peter L. Langen
Department of Environmental Science, iClimate, Aarhus University, Roskilde, Denmark
Guido Vettoretti
Physics of Ice, Climate and Earth, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
Sune Olander Rasmussen
CORRESPONDING AUTHOR
Physics of Ice, Climate and Earth, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
Related authors
No articles found.
Kolja Kypke, Marisa Montoya, Alexander Robinson, Jorge Alvarez-Solas, Jan Swierczek-Jereczek, and Peter Ditlevsen
EGUsphere, https://doi.org/10.5194/egusphere-2025-4116, https://doi.org/10.5194/egusphere-2025-4116, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
Short summary
Using a state-of-the-art ice sheet model, simulations of the future evolution of the Greenland ice sheet under moderate warming display chaotic variability, with the resulting large-scale loss of the ice sheet (also known as ’tipping’) being delayed by hundreds of thousands of years in some instances. The source of this variability is two nearby ice streams which oscillate in a build-up and surge pattern. This is the first study of such chaos in the Greenland ice sheet.
Takahito Mitsui, Peter Ditlevsen, Niklas Boers, and Michel Crucifix
Earth Syst. Dynam., 16, 1569–1584, https://doi.org/10.5194/esd-16-1569-2025, https://doi.org/10.5194/esd-16-1569-2025, 2025
Short summary
Short summary
The late Pleistocene glacial cycles are dominated by a 100-kyr periodicity, rather than other major astronomical periods like 19, 23, 41, or 400 kyr. Various models propose distinct mechanisms to explain this, but their diversity may obscure the key factor behind the 100-kyr periodicity. We propose a timescale-matching hypothesis, suggesting that the ice-sheet climate system responds to astronomical forcing at ∼100 kyr because its intrinsic timescale is closer to 100 kyr than to other periods.
Nicolas Stoll, Ilka Weikusat, Daniela Jansen, Paul Bons, Kyra Darányi, Julien Westhoff, María-Gema Llorens, David Wallis, Jan Eichler, Tomotaka Saruya, Tomoyuki Homma, Sune Olander Rasmussen, Giulia Sinnl, Anders Svensson, Martyn Drury, Frank Wilhelms, Sepp Kipfstuhl, Dorthe Dahl-Jensen, and Johanna Kerch
The Cryosphere, 19, 3805–3830, https://doi.org/10.5194/tc-19-3805-2025, https://doi.org/10.5194/tc-19-3805-2025, 2025
Short summary
Short summary
A better understanding of ice flow requires more observational data. The EastGRIP core is the first ice core through an active ice stream. We discuss crystal orientation data determining the present deformation regimes. A comparison with other deep cores shows the unique properties of EastGRIP and shows that deep ice likely originates from the Eemian. We further show that the overall plug flow of NEGIS is characterised by many small-scale variations, which remain to be considered in ice flow models.
Tanja Denager, Jesper Riis Christiansen, Raphael Johannes Maria Schneider, Peter L. Langen, Thea Quistgaard, and Simon Stisen
EGUsphere, https://doi.org/10.5194/egusphere-2025-2503, https://doi.org/10.5194/egusphere-2025-2503, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
This study demonstrates that incorporating both temperature and temporal variability in water level in emission models significantly influences CO2 emission from peat soil. Especially the co-occurrence of elevated air temperature and low groundwater table significantly influence CO2 emissions under scenarios of rewetting and climate change.
Naoko Nagatsuka, Kumiko Goto-Azuma, Kana Nagashima, Koji Fujita, Yuki Komuro, Motohiro Hirabayashi, Jun Ogata, Kaori Fukuda, Yoshimi Ogawa-Tsukagawa, Kyotaro Kitamura, Ayaka Yonekura, Fumio Nakazawa, Yukihiko Onuma, Naoyuki Kurita, Sune Olander Rasmussen, Giulia Sinnl, Trevor James Popp, and Dorthe Dahl-Jensen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1522, https://doi.org/10.5194/egusphere-2025-1522, 2025
Preprint archived
Short summary
Short summary
We present the first continuous records of dust size, composition, and temporal variations in potential sources from the northeastern Greenland ice core (EGRIP) over the past 100 years. Using a multi-proxy provenance approach based on individual particle analysis, we identify the primary dust sources as the Asian (Gobi) and African (Sahara) deserts. Our findings show shifts in their contributions since the 1970s–1980s, highlighting the effectiveness of this approach during low dust periods.
Chloe A. Brashear, Tyler R. Jones, Valerie Morris, Bruce H. Vaughn, William H. G. Roberts, William B. Skorski, Abigail G. Hughes, Richard Nunn, Sune Olander Rasmussen, Kurt M. Cuffey, Bo M. Vinther, Todd Sowers, Christo Buizert, Vasileios Gkinis, Christian Holme, Mari F. Jensen, Sofia E. Kjellman, Petra M. Langebroek, Florian Mekhaldi, Kevin S. Rozmiarek, Jonathan W. Rheinlænder, Margit H. Simon, Giulia Sinnl, Silje Smith-Johnsen, and James W. C. White
Clim. Past, 21, 529–546, https://doi.org/10.5194/cp-21-529-2025, https://doi.org/10.5194/cp-21-529-2025, 2025
Short summary
Short summary
We use a series of spectral techniques to quantify the strength of high-frequency climate variability in northeastern Greenland to 50 000 ka before present. Importantly, we find that variability consistently decreases hundreds of years prior to Dansgaard–Oeschger warming events. Model simulations suggest a change in North Atlantic sea ice behavior contributed to this pattern, thus providing new information on the conditions which preceded abrupt climate change during the Last Glacial Period.
Sindhu Vudayagiri, Bo Vinther, Johannes Freitag, Peter L. Langen, and Thomas Blunier
Clim. Past, 21, 517–528, https://doi.org/10.5194/cp-21-517-2025, https://doi.org/10.5194/cp-21-517-2025, 2025
Short summary
Short summary
Air trapped in polar ice during snowfall reflects atmospheric pressure at the time of occlusion, serving as a proxy for elevation. However, melting, firn structure changes, and air pressure variability complicate this relationship. We measured total air content (TAC) in the RECAP ice core from Renland ice cap, eastern Greenland, spanning 121 000 years. Melt layers and short-term TAC variations, whose origins remain unclear, present challenges in interpreting elevation changes.
Frédéric Parrenin, Marie Bouchet, Christo Buizert, Emilie Capron, Ellen Corrick, Russell Drysdale, Kenji Kawamura, Amaëlle Landais, Robert Mulvaney, Ikumi Oyabu, and Sune Olander Rasmussen
Geosci. Model Dev., 17, 8735–8750, https://doi.org/10.5194/gmd-17-8735-2024, https://doi.org/10.5194/gmd-17-8735-2024, 2024
Short summary
Short summary
The Paleochrono-1.1 probabilistic dating model allows users to derive a common and optimized chronology for several paleoclimatic sites from various archives (ice cores, speleothems, marine cores, lake cores, etc.). It combines prior sedimentation scenarios with chronological information such as dated horizons, dated intervals, stratigraphic links and (for ice cores) Δdepth observations. Paleochrono-1.1 is available under an open-source license.
Emma Pearce, Dimitri Zigone, Coen Hofstede, Andreas Fichtner, Joachim Rimpot, Sune Olander Rasmussen, Johannes Freitag, and Olaf Eisen
The Cryosphere, 18, 4917–4932, https://doi.org/10.5194/tc-18-4917-2024, https://doi.org/10.5194/tc-18-4917-2024, 2024
Short summary
Short summary
Our study near EastGRIP camp in Greenland shows varying firn properties by direction (crucial for studying ice stream stability, structure, surface mass balance, and past climate conditions). We used dispersion curve analysis of Love and Rayleigh waves to show firn is nonuniform along and across the flow of an ice stream due to wind patterns, seasonal variability, and the proximity to the edge of the ice stream. This method better informs firn structure, advancing ice stream understanding.
Nicolaj Hansen, Andrew Orr, Xun Zou, Fredrik Boberg, Thomas J. Bracegirdle, Ella Gilbert, Peter L. Langen, Matthew A. Lazzara, Ruth Mottram, Tony Phillips, Ruth Price, Sebastian B. Simonsen, and Stuart Webster
The Cryosphere, 18, 2897–2916, https://doi.org/10.5194/tc-18-2897-2024, https://doi.org/10.5194/tc-18-2897-2024, 2024
Short summary
Short summary
We investigated a melt event over the Ross Ice Shelf. We use regional climate models and a firn model to simulate the melt and compare the results with satellite data. We find that the firn model aligned well with observed melt days in certain parts of the ice shelf. The firn model had challenges accurately simulating the melt extent in the western sector. We identified potential reasons for these discrepancies, pointing to limitations in the models related to representing the cloud properties.
Xiaofeng Wang, Lu An, Peter L. Langen, and Rongxing Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-2024, 691–696, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024, 2024
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
Short summary
Short summary
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.
Johannes Lohmann, Jiamei Lin, Bo M. Vinther, Sune O. Rasmussen, and Anders Svensson
Clim. Past, 20, 313–333, https://doi.org/10.5194/cp-20-313-2024, https://doi.org/10.5194/cp-20-313-2024, 2024
Short summary
Short summary
We present the first attempt to constrain the climatic impact of volcanic eruptions with return periods of hundreds of years by the oxygen isotope records of Greenland and Antarctic ice cores covering the last glacial period. A clear multi-annual volcanic cooling signal is seen, but its absolute magnitude is subject to the unknown glacial sensitivity of the proxy. Different proxy signals after eruptions during cooler versus warmer glacial stages may reflect a state-dependent climate response.
Naoko Nagatsuka, Kumiko Goto-Azuma, Koji Fujita, Yuki Komuro, Motohiro Hirabayashi, Jun Ogata, Kaori Fukuda, Yoshimi Ogawa-Tsukagawa, Kyotaro Kitamura, Ayaka Yonekura, Fumio Nakazawa, Yukihiko Onuma, Naoyuki Kurita, Sune Olander Rasmussen, Giulia Sinnl, Trevor James Popp, and Dorthe Dahl-Jensen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1666, https://doi.org/10.5194/egusphere-2023-1666, 2023
Preprint archived
Short summary
Short summary
We present a new high-temporal-resolution record of mineral composition in a northeastern Greenland ice-core (EGRIP) over the past 100 years. The ice core dust composition and its variation differed significantly from a northwestern Greenland ice core, which is likely due to differences in the geological sources of the dust. Our results suggest that the EGRIP ice core dust was constantly supplied from Northern Eurasia, North America, and Asia with minor contribution from Greenland coast.
Sune Olander Rasmussen, Dorthe Dahl-Jensen, Hubertus Fischer, Katrin Fuhrer, Steffen Bo Hansen, Margareta Hansson, Christine S. Hvidberg, Ulf Jonsell, Sepp Kipfstuhl, Urs Ruth, Jakob Schwander, Marie-Louise Siggaard-Andersen, Giulia Sinnl, Jørgen Peder Steffensen, Anders M. Svensson, and Bo M. Vinther
Earth Syst. Sci. Data, 15, 3351–3364, https://doi.org/10.5194/essd-15-3351-2023, https://doi.org/10.5194/essd-15-3351-2023, 2023
Short summary
Short summary
Timescales are essential for interpreting palaeoclimate data. The data series presented here were used for annual-layer identification when constructing the timescales named the Greenland Ice-Core Chronology 2005 (GICC05) and the revised version GICC21. Hopefully, these high-resolution data sets will be useful also for other purposes.
Giulia Sinnl, Florian Adolphi, Marcus Christl, Kees C. Welten, Thomas Woodruff, Marc Caffee, Anders Svensson, Raimund Muscheler, and Sune Olander Rasmussen
Clim. Past, 19, 1153–1175, https://doi.org/10.5194/cp-19-1153-2023, https://doi.org/10.5194/cp-19-1153-2023, 2023
Short summary
Short summary
The record of past climate is preserved by several archives from different regions, such as ice cores from Greenland or Antarctica or speleothems from caves such as the Hulu Cave in China. In this study, these archives are aligned by taking advantage of the globally synchronous production of cosmogenic radionuclides. This produces a new perspective on the global climate in the period between 20 000 and 25 000 years ago.
Giulia Sinnl, Mai Winstrup, Tobias Erhardt, Eliza Cook, Camilla Marie Jensen, Anders Svensson, Bo Møllesøe Vinther, Raimund Muscheler, and Sune Olander Rasmussen
Clim. Past, 18, 1125–1150, https://doi.org/10.5194/cp-18-1125-2022, https://doi.org/10.5194/cp-18-1125-2022, 2022
Short summary
Short summary
A new Greenland ice-core timescale, covering the last 3800 years, was produced using the machine learning algorithm StratiCounter. We synchronized the ice cores using volcanic eruptions and wildfires. We compared the new timescale to the tree-ring timescale, finding good alignment both between the common signatures of volcanic eruptions and of solar activity. Our Greenlandic timescales is safe to use for the Late Holocene, provided one uses our uncertainty estimate.
Jiamei Lin, Anders Svensson, Christine S. Hvidberg, Johannes Lohmann, Steffen Kristiansen, Dorthe Dahl-Jensen, Jørgen Peder Steffensen, Sune Olander Rasmussen, Eliza Cook, Helle Astrid Kjær, Bo M. Vinther, Hubertus Fischer, Thomas Stocker, Michael Sigl, Matthias Bigler, Mirko Severi, Rita Traversi, and Robert Mulvaney
Clim. Past, 18, 485–506, https://doi.org/10.5194/cp-18-485-2022, https://doi.org/10.5194/cp-18-485-2022, 2022
Short summary
Short summary
We employ acidity records from Greenland and Antarctic ice cores to estimate the emission strength, frequency and climatic forcing for large volcanic eruptions from the last half of the last glacial period. A total of 25 volcanic eruptions are found to be larger than any eruption in the last 2500 years, and we identify more eruptions than obtained from geological evidence. Towards the end of the glacial period, there is a notable increase in volcanic activity observed for Greenland.
Fredrik Boberg, Ruth Mottram, Nicolaj Hansen, Shuting Yang, and Peter L. Langen
The Cryosphere, 16, 17–33, https://doi.org/10.5194/tc-16-17-2022, https://doi.org/10.5194/tc-16-17-2022, 2022
Short summary
Short summary
Using the regional climate model HIRHAM5, we compare two versions (v2 and v3) of the global climate model EC-Earth for the Greenland and Antarctica ice sheets. We are interested in the surface mass balance of the ice sheets due to its importance when making estimates of future sea level rise. We find that the end-of-century change in the surface mass balance for Antarctica is 420 Gt yr−1 (v2) and 80 Gt yr−1 (v3), and for Greenland it is −290 Gt yr−1 (v2) and −1640 Gt yr−1 (v3).
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
Short summary
Short summary
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.
Nicolaj Hansen, Peter L. Langen, Fredrik Boberg, Rene Forsberg, Sebastian B. Simonsen, Peter Thejll, Baptiste Vandecrux, and Ruth Mottram
The Cryosphere, 15, 4315–4333, https://doi.org/10.5194/tc-15-4315-2021, https://doi.org/10.5194/tc-15-4315-2021, 2021
Short summary
Short summary
We have used computer models to estimate the Antarctic surface mass balance (SMB) from 1980 to 2017. Our estimates lies between 2473.5 ± 114.4 Gt per year and 2564.8 ± 113.7 Gt per year. To evaluate our models, we compared the modelled snow temperatures and densities to in situ measurements. We also investigated the spatial distribution of the SMB. It is very important to have estimates of the Antarctic SMB because then it is easier to understand global sea level changes.
Tamara Annina Gerber, Christine Schøtt Hvidberg, Sune Olander Rasmussen, Steven Franke, Giulia Sinnl, Aslak Grinsted, Daniela Jansen, and Dorthe Dahl-Jensen
The Cryosphere, 15, 3655–3679, https://doi.org/10.5194/tc-15-3655-2021, https://doi.org/10.5194/tc-15-3655-2021, 2021
Short summary
Short summary
We simulate the ice flow in the onset region of the Northeast Greenland Ice Stream to determine the source area and past accumulation rates of ice found in the EastGRIP ice core. This information is required to correct for bias in ice-core records introduced by the upstream flow effects. Our results reveal that the increasing accumulation rate with increasing upstream distance is predominantly responsible for the constant annual layer thicknesses observed in the upper 900 m of the ice core.
Johannes Lohmann, Daniele Castellana, Peter D. Ditlevsen, and Henk A. Dijkstra
Earth Syst. Dynam., 12, 819–835, https://doi.org/10.5194/esd-12-819-2021, https://doi.org/10.5194/esd-12-819-2021, 2021
Short summary
Short summary
Tipping of one climate subsystem could trigger a cascade of subsequent tipping points and even global-scale climate tipping. Sequential shifts of atmosphere, sea ice and ocean have been recorded in proxy archives of past climate change. Based on this we propose a conceptual model for abrupt climate changes of the last glacial. Here, rate-induced tipping enables tipping cascades in systems with relatively weak coupling. An early warning signal is proposed that may detect such a tipping.
Ulas Im, Kostas Tsigaridis, Gregory Faluvegi, Peter L. Langen, Joshua P. French, Rashed Mahmood, Manu A. Thomas, Knut von Salzen, Daniel C. Thomas, Cynthia H. Whaley, Zbigniew Klimont, Henrik Skov, and Jørgen Brandt
Atmos. Chem. Phys., 21, 10413–10438, https://doi.org/10.5194/acp-21-10413-2021, https://doi.org/10.5194/acp-21-10413-2021, 2021
Short summary
Short summary
Future (2015–2050) simulations of the aerosol burdens and their radiative forcing and climate impacts over the Arctic under various emission projections show that although the Arctic aerosol burdens are projected to decrease significantly by 10 to 60 %, regardless of the magnitude of aerosol reductions, surface air temperatures will continue to increase by 1.9–2.6 ℃, while sea-ice extent will continue to decrease, implying reductions of greenhouse gases are necessary to mitigate climate change.
Fredrik Boberg, Ruth Mottram, Nicolaj Hansen, Shuting Yang, and Peter L. Langen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-331, https://doi.org/10.5194/tc-2020-331, 2020
Manuscript not accepted for further review
Short summary
Short summary
Using the regional climate model HIRHAM5, we compare two versions (v2 and v3) of the global climate model EC-Earth for the Greenland and Antarctica ice sheets. We are interested in the surface mass balance of the ice sheets due to its importance when making estimates of the future sea level rise. We find that the end-of-century change of the surface mass balance for Antarctica is +150 Gt yr−1 (v2) and −710 Gt yr−1 (v3) and for Greenland the numbers are −210 Gt yr−1 (v2) and −1150 Gt yr−1 (v3).
Seyedhamidreza Mojtabavi, Frank Wilhelms, Eliza Cook, Siwan M. Davies, Giulia Sinnl, Mathias Skov Jensen, Dorthe Dahl-Jensen, Anders Svensson, Bo M. Vinther, Sepp Kipfstuhl, Gwydion Jones, Nanna B. Karlsson, Sergio Henrique Faria, Vasileios Gkinis, Helle Astrid Kjær, Tobias Erhardt, Sarah M. P. Berben, Kerim H. Nisancioglu, Iben Koldtoft, and Sune Olander Rasmussen
Clim. Past, 16, 2359–2380, https://doi.org/10.5194/cp-16-2359-2020, https://doi.org/10.5194/cp-16-2359-2020, 2020
Short summary
Short summary
We present a first chronology for the East Greenland Ice-core Project (EGRIP) over the Holocene and last glacial termination. After field measurements and processing of the ice-core data, the GICC05 timescale is transferred from the NGRIP core to the EGRIP core by means of matching volcanic events and common patterns (381 match points) in the ECM and DEP records. The new timescale is named GICC05-EGRIP-1 and extends back to around 15 kyr b2k.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
Short summary
Short summary
We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Baptiste Vandecrux, Ruth Mottram, Peter L. Langen, Robert S. Fausto, Martin Olesen, C. Max Stevens, Vincent Verjans, Amber Leeson, Stefan Ligtenberg, Peter Kuipers Munneke, Sergey Marchenko, Ward van Pelt, Colin R. Meyer, Sebastian B. Simonsen, Achim Heilig, Samira Samimi, Shawn Marshall, Horst Machguth, Michael MacFerrin, Masashi Niwano, Olivia Miller, Clifford I. Voss, and Jason E. Box
The Cryosphere, 14, 3785–3810, https://doi.org/10.5194/tc-14-3785-2020, https://doi.org/10.5194/tc-14-3785-2020, 2020
Short summary
Short summary
In the vast interior of the Greenland ice sheet, snow accumulates into a thick and porous layer called firn. Each summer, the firn retains part of the meltwater generated at the surface and buffers sea-level rise. In this study, we compare nine firn models traditionally used to quantify this retention at four sites and evaluate their performance against a set of in situ observations. We highlight limitations of certain model designs and give perspectives for future model development.
Cited articles
Ansel, J., Yang, E., He, H., Gimelshein, N., Jain, A., Voznesensky, M., Bao, B., Bell, P., Berard, D., Burovski, E., Chauhan, G., Chourdia, A., Constable, W., Desmaison, A., DeVito, Z., Ellison, E., Feng, W., Gong, J., Gschwind, M., Hirsh, B., Huang, S., Kalambarkar, K., Kirsch, L., Lazos, M., Lezcano, M., Liang, Y., Liang, J., Lu, Y., Luk, C. K., Maher, B., Pan, Y., Puhrsch, C., Reso, M., Saroufim, M., Siraichi, M. Y., Suk, H., Zhang, S., Suo, M., Tillet, P., Zhao, X., Wang, E., Zhou, K., Zou, R., Wang, X., Mathews, A., Wen, W., Chanan, G., Wu, P., and Chintala, S.: PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation, in: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2, ACM [code], La Jolla CA USA, 929–947, ISBN 9798400703850, https://doi.org/10.1145/3620665.3640366, 2024. a, b
Bellomo, K., Meccia, V. L., D’Agostino, R., Fabiano, F., Larson, S. M., von Hardenberg, J., and Corti, S.: Impacts of a weakened AMOC on precipitation over the Euro-Atlantic region in the EC-Earth3 climate model, Clim. Dynam., 61, 3397–3416, https://doi.org/10.1007/s00382-023-06754-2, 2023. a
Broecker, W. S.: Paleocean circulation during the Last Deglaciation: A bipolar seesaw?, Paleoceanography, 13, 119–121, https://doi.org/10.1029/97PA03707, 1998. a
Capron, E., Landais, A., Chappellaz, J., Schilt, A., Buiron, D., Dahl-Jensen, D., Johnsen, S. J., Jouzel, J., Lemieux-Dudon, B., Loulergue, L., Leuenberger, M., Masson-Delmotte, V., Meyer, H., Oerter, H., and Stenni, B.: Millennial and sub-millennial scale climatic variations recorded in polar ice cores over the last glacial period, Clim. Past, 6, 345–365, https://doi.org/10.5194/cp-6-345-2010, 2010. a, b
Cessi, P.: A Simple Box Model of Stochastically Forced Thermohaline Flow, J. Phys. Oceanogr., 24, 1911–1920, https://doi.org/10.1175/1520-0485(1994)024<1911:ASBMOS>2.0.CO;2, 1994. a
Cimatoribus, A. A., Drijfhout, S. S., and Dijkstra, H. A.: Meridional overturning circulation: stability and ocean feedbacks in a box model, Clim. Dynam., 42, 311–328, https://doi.org/10.1007/s00382-012-1576-9, 2014. a
Dijkstra, H. A.: Characterization of the multiple equilibria regime in a global ocean model, Tellus A, 59, 695–705, https://doi.org/10.1111/j.1600-0870.2007.00267.x, 2007. a
Ditlevsen, P. D.: Observation of α-stable noise induced millennial climate changes from an ice-core record, Geophys. Res. Lett., 26, 1441–1444, https://doi.org/10.1029/1999GL900252, 1999. a
Ditlevsen, P. D., Ditlevsen, S., and Andersen, K.: The fast climate fluctuations during the stadial and interstadial climate states, Ann. Glaciol., 35, 457–462, https://doi.org/10.3189/172756402781816870, 2002. a
Frankignoul, C., Gastineau, G., and Kwon, Y.-O.: The Influence of the AMOC Variability on the Atmosphere in CCSM3, J. Climate, 26, 9774–9790, https://doi.org/10.1175/JCLI-D-12-00862.1, 2013. a
Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C., Jayne, S. R., Lawrence, D. M., Neale, R. B., Rasch, P. J., Vertenstein, M., Worley, P. H., Yang, Z.-L., and Zhang, M.: The Community Climate System Model Version 4, J. Climate, 24, 4973–4991, https://doi.org/10.1175/2011JCLI4083.1, 2011. a
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del Río, J. F., Wiebe, M., Peterson, P., Gérard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., and Oliphant, T. E.: Array programming with NumPy, Nature, 585, 357–362, https://doi.org/10.1038/s41586-020-2649-2, 2020. a
Henry, L. G., McManus, J. F., Curry, W. B., Roberts, N. L., Piotrowski, A. M., and Keigwin, L. D.: North Atlantic ocean circulation and abrupt climate change during the last glaciation, Science, 353, 470–474, https://doi.org/10.1126/science.aaf5529, 2016. a
Hoyer, S. and Hamman, J.: xarray: N-D labeled Arrays and Datasets in Python, Journal of Open Research Software, 5, 10, https://doi.org/10.5334/jors.148, 2017. a
Hunter, J. D.: Matplotlib: A 2D Graphics Environment, Computing in Science & Engineering, 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Kidger, P., Foster, J., Li, X., and Lyons, T. J.: Neural SDEs as Infinite-Dimensional GANs, in: Proceedings of the 38th International Conference on Machine Learning, PMLR, 5453–5463, https://doi.org/10.48550/arXiv.2102.03657, 2021. a, b
Kindler, P., Guillevic, M., Baumgartner, M., Schwander, J., Landais, A., and Leuenberger, M.: Temperature reconstruction from 10 to 120 kyr b2k from the NGRIP ice core, Clim. Past, 10, 887–902, https://doi.org/10.5194/cp-10-887-2014, 2014. a
Klockmann, M., Mikolajewicz, U., and Marotzke, J.: Two AMOC States in Response to Decreasing Greenhouse Gas Concentrations in the Coupled Climate Model MPI-ESM, J. Climate, 31, 7969–7984, https://doi.org/10.1175/JCLI-D-17-0859.1, 2018. a
Kowalczyk, P. and Glendinning, P.: Boundary-equilibrium bifurcations in piecewise-smooth slow-fast systems, Chaos, 21, 023126, https://doi.org/10.1063/1.3596708, 2011. a, b
Kwasniok, F.: Analysis and modelling of glacial climate transitions using simple dynamical systems, Philos. T. R. Soc. A, 371, 20110472, https://doi.org/10.1098/rsta.2011.0472, 2013. a, b
Li, C. and Born, A.: Coupled atmosphere-ice-ocean dynamics in Dansgaard-Oeschger events, Quaternary Sci. Rev., 203, 1–20, https://doi.org/10.1016/j.quascirev.2018.10.031, 2019. a
Li, X., Wong, T.-K. L., Chen, R. T. Q., and Duvenaud, D.: Scalable Gradients for Stochastic Differential Equations, arXiv [preprint], https://doi.org/10.48550/arXiv.2001.01328, 2020. a, b
Malmierca-Vallet, I., Sime, L. C., and the D–O community members: Dansgaard–Oeschger events in climate models: review and baseline Marine Isotope Stage 3 (MIS3) protocol, Clim. Past, 19, 915–942, https://doi.org/10.5194/cp-19-915-2023, 2023. a
Melcher, J. and Halkjær, S.: JonathanMelcher/2023_paper_Melcher_Halkjaer: Updates pre submission (v1.0.1), Zenodo [code], https://doi.org/10.5281/zenodo.12720710, 2024a. a
Melcher, J. and Halkjær, S.: Simulated values for making figures, sid data host [data set], https://sid.erda.dk/cgi-sid/ls.py?share_id=E1YJOoNQGY (last access: 5 November 2024), 2024b. a
Nadeau, L.-P. and Jansen, M. F.: Overturning Circulation Pathways in a Two-Basin Ocean Model, J. Phys. Oceanogr., 50, 2105–2122, https://doi.org/10.1175/JPO-D-20-0034.1, 2020. a
Pedro, J. B., Jochum, M., Buizert, C., He, F., Barker, S., and Rasmussen, S. O.: Beyond the bipolar seesaw: Toward a process understanding of interhemispheric coupling, Quaternary Sci. Rev., 192, 27–46, https://doi.org/10.1016/j.quascirev.2018.05.005, 2018. a, b, c
Pedro, J. B., Andersson, C., Vettoretti, G., Voelker, A. H. L., Waelbroeck, C., Dokken, T. M., Jensen, M. F., Rasmussen, S. O., Sessford, E. G., Jochum, M., and Nisancioglu, K. H.: Dansgaard-Oeschger and Heinrich event temperature anomalies in the North Atlantic set by sea ice, frontal position and thermocline structure, Quaternary Sci. Rev., 289, 107599, https://doi.org/10.1016/j.quascirev.2022.107599, 2022. a
Pratap, S., Markonis, Y., and R. Blöcher, J.: Understanding Atlantic Meridional Overturning Circulation and linked variations in precipitation and temperature distribution during the warmer climate, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-129, https://doi.org/10.5194/egusphere-egu23-129, 2023. a
Rasmussen, S. O., Bigler, M., Blockley, S. P., Blunier, T., Buchardt, S. L., Clausen, H. B., Cvijanovic, I., Dahl-Jensen, D., Johnsen, S. J., Fischer, H., Gkinis, V., Guillevic, M., Hoek, W. Z., Lowe, J. J., Pedro, J. B., Popp, T., Seierstad, I. K., Steffensen, J. P., Svensson, A. M., Vallelonga, P., Vinther, B. M., Walker, M. J. C., Wheatley, J. J., and Winstrup, M.: A stratigraphic framework for abrupt climatic changes during the Last Glacial period based on three synchronized Greenland ice-core records: refining and extending the INTIMATE event stratigraphy, Quaternary Sci. Rev., 106, 14–28, https://doi.org/10.1016/j.quascirev.2014.09.007, 2014. a, b, c, d
Roberts, A. and Saha, R.: Relaxation oscillations in an idealized ocean circulation model, Clim. Dynam., 48, 2123–2134, https://doi.org/10.1007/s00382-016-3195-3, 2017. a, b
Schulz, M.: On the 1470-year pacing of Dansgaard-Oeschger warm events, Paleoceanography, 17, 4-1–4-9, https://doi.org/10.1029/2000PA000571, 2002. a
Stocker, T. F. and Johnsen, S. J.: A minimum thermodynamic model for the bipolar seesaw, Paleoceanography, 18, 1087, https://doi.org/10.1029/2003PA000920, 2003. a
Vettoretti, G. and Peltier: Thermohaline instability and the formation of glacial North Atlantic super polynyas at the onset of Dansgaard-Oeschger warming events, Geophys. Res. Lett., 43, 5336–5344, https://doi.org/10.1002/2016GL068891, 2016. a
Vettoretti, G. and Peltier: Fast Physics and Slow Physics in the Nonlinear Dansgaard-Oeschger Relaxation Oscillation, J. Climate, 31, 3423–3449, https://doi.org/10.1175/JCLI-D-17-0559.1, 2018. a
Short summary
We introduce a new model that simulates Dansgaard–Oeschger events, dramatic and irregular climate shifts within past ice ages. The model consists of simplified equations inspired by ocean current dynamics. We fine-tune this model to capture the Dansgaard–Oeschger events with unprecedented accuracy, providing deeper insights into past climate patterns. This helps us understand and predict complex climate changes, aiding future climate change resilience efforts.
We introduce a new model that simulates Dansgaard–Oeschger events, dramatic and irregular...
