Articles | Volume 17, issue 9
https://doi.org/10.5194/tc-17-4133-2023
© Author(s) 2023. 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-17-4133-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Sep 2023
Research article |
| 22 Sep 2023
| 22 Sep 2023
Forced and internal components of observed Arctic sea-ice changes
Geophysical Institute, University of Bergen and Bjerknes Centre for Climate Research, Bergen, Norway
David B. Bonan
California Institute of Technology, Pasadena, California, USA
Marius Årthun
Geophysical Institute, University of Bergen and Bjerknes Centre for Climate Research, Bergen, Norway
Lea Svendsen
Geophysical Institute, University of Bergen and Bjerknes Centre for Climate Research, Bergen, Norway
Robert C. J. Wills
Department of Atmospheric Sciences, University of Washington, Seattle, Washington, USA
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
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David B. Bonan, Jakob Dörr, Robert C. J. Wills, Andrew F. Thompson, and Marius Årthun
The Cryosphere, 18, 2141–2159, https://doi.org/10.5194/tc-18-2141-2024, https://doi.org/10.5194/tc-18-2141-2024, 2024
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Antarctic sea ice has exhibited variability over satellite records, including a period of gradual expansion and a period of sudden decline. We use a novel statistical method to identify sources of variability in observed Antarctic sea ice changes. We find that the gradual increase in sea ice is likely related to large-scale temperature trends, and periods of abrupt sea ice decline are related to specific flavors of equatorial tropical variability known as the El Niño–Southern Oscillation.
Ole Rieke, Marius Årthun, and Jakob Simon Dörr
The Cryosphere, 17, 1445–1456, https://doi.org/10.5194/tc-17-1445-2023, https://doi.org/10.5194/tc-17-1445-2023, 2023
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The Barents Sea is the region of most intense winter sea ice loss, and future projections show a continued decline towards ice-free conditions by the end of this century but with large fluctuations. Here we use climate model simulations to look at the occurrence and drivers of rapid ice change events in the Barents Sea that are much stronger than the average ice loss. A better understanding of these events will contribute to improved sea ice predictions in the Barents Sea.
David B. Bonan, Jakob Dörr, Robert C. J. Wills, Andrew F. Thompson, and Marius Årthun
The Cryosphere, 18, 2141–2159, https://doi.org/10.5194/tc-18-2141-2024, https://doi.org/10.5194/tc-18-2141-2024, 2024
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Antarctic sea ice has exhibited variability over satellite records, including a period of gradual expansion and a period of sudden decline. We use a novel statistical method to identify sources of variability in observed Antarctic sea ice changes. We find that the gradual increase in sea ice is likely related to large-scale temperature trends, and periods of abrupt sea ice decline are related to specific flavors of equatorial tropical variability known as the El Niño–Southern Oscillation.
Tapio Schneider, L. Ruby Leung, and Robert C. J. Wills
EGUsphere, https://doi.org/10.5194/egusphere-2024-20, https://doi.org/10.5194/egusphere-2024-20, 2024
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This paper lays out an approach to achieve substantial progress in climate modeling, balancing increases in resolution with advances in process-based modeling and the use of AI to learn from Earth observations.
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Earth Syst. Dynam., 14, 413–431, https://doi.org/10.5194/esd-14-413-2023, https://doi.org/10.5194/esd-14-413-2023, 2023
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Understanding whether the El Niño–Southern Oscillation (ENSO) is likely to change in the future is important due to its widespread impacts. By using large ensembles, we can robustly isolate the time-evolving response of ENSO variability in 14 climate models. We find that ENSO variability evolves in a nonlinear fashion in many models and that there are large differences between models. These nonlinear changes imply that ENSO impacts may vary dramatically throughout the 21st century.
Ole Rieke, Marius Årthun, and Jakob Simon Dörr
The Cryosphere, 17, 1445–1456, https://doi.org/10.5194/tc-17-1445-2023, https://doi.org/10.5194/tc-17-1445-2023, 2023
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The Barents Sea is the region of most intense winter sea ice loss, and future projections show a continued decline towards ice-free conditions by the end of this century but with large fluctuations. Here we use climate model simulations to look at the occurrence and drivers of rapid ice change events in the Barents Sea that are much stronger than the average ice loss. A better understanding of these events will contribute to improved sea ice predictions in the Barents Sea.
Ingo Bethke, Yiguo Wang, François Counillon, Noel Keenlyside, Madlen Kimmritz, Filippa Fransner, Annette Samuelsen, Helene Langehaug, Lea Svendsen, Ping-Gin Chiu, Leilane Passos, Mats Bentsen, Chuncheng Guo, Alok Gupta, Jerry Tjiputra, Alf Kirkevåg, Dirk Olivié, Øyvind Seland, Julie Solsvik Vågane, Yuanchao Fan, and Tor Eldevik
Geosci. Model Dev., 14, 7073–7116, https://doi.org/10.5194/gmd-14-7073-2021, https://doi.org/10.5194/gmd-14-7073-2021, 2021
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The Norwegian Climate Prediction Model version 1 (NorCPM1) is a new research tool for performing climate reanalyses and seasonal-to-decadal climate predictions. It adds data assimilation capability to the Norwegian Earth System Model version 1 (NorESM1) and has contributed output to the Decadal Climate Prediction Project (DCPP) as part of the sixth Coupled Model Intercomparison Project (CMIP6). We describe the system and evaluate its baseline, reanalysis and prediction performance.
Philipp Anhaus, Lars H. Smedsrud, Marius Årthun, and Fiammetta Straneo
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-35, https://doi.org/10.5194/tc-2019-35, 2019
Revised manuscript not accepted
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Atlantic Water flows towards the Arctic and under floating glaciers on Greenland. Observations in a rift on the 79 North Glacier show presence of such water with temperature of 1 °C at 600 m. We simulate how this warm water melts the floating ice. Melt rates are largest where the glacier starts floating, are smaller where the water rises, and increase linearly with rising ocean temperature. Our results improve the understanding of ocean processes driving melting of floating glaciers.
Related subject area
Discipline: Sea ice | Subject: Climate Interactions
Network connectivity between the winter Arctic Oscillation and summer sea ice in CMIP6 models and observations
The contribution of melt ponds to enhanced Arctic sea-ice melt during the Last Interglacial
Analyzing links between simulated Laptev Sea sea ice and atmospheric conditions over adjoining landmasses using causal-effect networks
Clouds damp the radiative impacts of polar sea ice loss
William Gregory, Julienne Stroeve, and Michel Tsamados
The Cryosphere, 16, 1653–1673, https://doi.org/10.5194/tc-16-1653-2022, https://doi.org/10.5194/tc-16-1653-2022, 2022
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This research was conducted to better understand how coupled climate models simulate one of the large-scale interactions between the atmosphere and Arctic sea ice that we see in observational data, the accurate representation of which is important for producing reliable forecasts of Arctic sea ice on seasonal to inter-annual timescales. With network theory, this work shows that models do not reflect this interaction well on average, which is likely due to regional biases in sea ice thickness.
Rachel Diamond, Louise C. Sime, David Schroeder, and Maria-Vittoria Guarino
The Cryosphere, 15, 5099–5114, https://doi.org/10.5194/tc-15-5099-2021, https://doi.org/10.5194/tc-15-5099-2021, 2021
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The Hadley Centre Global Environment Model version 3 (HadGEM3) is the first coupled climate model to simulate an ice-free summer Arctic during the Last Interglacial (LIG), 127 000 years ago, and yields accurate Arctic surface temperatures. We investigate the causes and impacts of this extreme simulated ice loss and, in particular, the role of melt ponds.
Zoé Rehder, Anne Laura Niederdrenk, Lars Kaleschke, and Lars Kutzbach
The Cryosphere, 14, 4201–4215, https://doi.org/10.5194/tc-14-4201-2020, https://doi.org/10.5194/tc-14-4201-2020, 2020
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To better understand the connection between sea ice and permafrost, we investigate how sea ice interacts with the atmosphere over the adjacent landmass in the Laptev Sea region using a climate model. Melt of sea ice in spring is mainly controlled by the atmosphere; in fall, feedback mechanisms are important. Throughout summer, lower-than-usual sea ice leads to more southward transport of heat and moisture, but these links from sea ice to the atmosphere over land are weak.
Ramdane Alkama, Patrick C. Taylor, Lorea Garcia-San Martin, Herve Douville, Gregory Duveiller, Giovanni Forzieri, Didier Swingedouw, and Alessandro Cescatti
The Cryosphere, 14, 2673–2686, https://doi.org/10.5194/tc-14-2673-2020, https://doi.org/10.5194/tc-14-2673-2020, 2020
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The amount of solar energy absorbed by Earth is believed to strongly depend on clouds. Here, we investigate this relationship using satellite data and 32 climate models, showing that this relationship holds everywhere except over polar seas, where an increased reflection by clouds corresponds to an increase in absorbed solar radiation at the surface. This interplay between clouds and sea ice reduces by half the increase of net radiation at the surface that follows the sea ice retreat.
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Short summary
The Arctic sea-ice cover is retreating due to climate change, but this retreat is influenced by natural (internal) variability in the climate system. We use a new statistical method to investigate how much internal variability has affected trends in the summer and winter Arctic sea-ice cover using observations since 1979. Our results suggest that the impact of internal variability on sea-ice retreat might be lower than what climate models have estimated.
The Arctic sea-ice cover is retreating due to climate change, but this retreat is influenced by...
