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1. Antarctic Sea Ice Area in CMIP6

Author

Roach, Lettie A, Dörr, Jakob, Holmes, Caroline R, Massonnet, François, Blockley, Edward W, Notz, Dirk, Rackow, Thomas, Raphael, Marilyn N, O'Farrell, Siobhan P, Bailey, David A, and Bitz, Cecilia M

Subjects
Climate Action, sea ice, CMIP6, Antarctica, climate models, Southern Ocean, model evaluation, Meteorology & Atmospheric Sciences
Abstract

Fully coupled climate models have long shown a wide range of Antarctic sea ice states and evolution over the satellite era. Here, we present a high-level evaluation of Antarctic sea ice in 40 models from the most recent phase of the Coupled Model Intercomparison Project (CMIP6). Many models capture key characteristics of the mean seasonal cycle of sea ice area (SIA), but some simulate implausible historical mean states compared to satellite observations, leading to large intermodel spread. Summer SIA is consistently biased low across the ensemble. Compared to the previous model generation (CMIP5), the intermodel spread in winter and summer SIA has reduced, and the regional distribution of sea ice concentration has improved. Over 1979–2018, many models simulate strong negative trends in SIA concurrently with stronger-than-observed trends in global mean surface temperature (GMST). By the end of the 21st century, models project clear differences in sea ice between forcing scenarios.

Published
2020

6. Sources of low-frequency variability in observed Antarctic sea ice.

Author

Bonan, David B., Dörr, Jakob, Wills, Robert C. J., Thompson, Andrew F., and Årthun, Marius

Subjects
*ANTARCTIC ice, *ANTARCTIC oscillation, *SEA ice, *WESTERLIES, *OCEAN temperature, EL Nino
Abstract

Antarctic sea ice has exhibited significant variability over the satellite record, including a period of prolonged and gradual expansion, as well as a period of sudden decline. A number of mechanisms have been proposed to explain this variability, but how each mechanism manifests spatially and temporally remains poorly understood. Here, we use a statistical method called low-frequency component analysis to analyze the spatiotemporal structure of observed Antarctic sea ice concentration variability. The identified patterns reveal distinct modes of low-frequency sea ice variability. The leading mode, which accounts for the large-scale, gradual expansion of sea ice, is associated with the Interdecadal Pacific Oscillation and resembles the observed sea surface temperature trend pattern that climate models have trouble reproducing. The second mode is associated with the central Pacific El Niño–Southern Oscillation (ENSO) and the Southern Annular Mode and accounts for most of the sea ice variability in the Ross Sea. The third mode is associated with the eastern Pacific ENSO and Amundsen Sea Low and accounts for most of the pan-Antarctic sea ice variability and almost all of the sea ice variability in the Weddell Sea. The third mode is also related to periods of abrupt Antarctic sea ice decline that are associated with a weakening of the circumpolar westerlies, which favors surface warming through a shoaling of the ocean mixed layer and decreased northward Ekman heat transport. Broadly, these results suggest that climate model biases in long-term Antarctic sea ice and large-scale sea surface temperature trends are related to each other and that eastern Pacific ENSO variability is a key ingredient for abrupt Antarctic sea ice changes. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Sources of low-frequency variability in observed Antarctic sea ice.

Author

Bonan, David B., Dörr, Jakob, Wills, Robert C. J., Thompson, Andrew F., and Årthun, Marius

Subjects
ANTARCTIC ice, ANTARCTIC oscillation, WESTERLIES, EL Nino, SEA ice, OCEANIC mixing
Abstract

Antarctic sea ice gradually increased from the late 1970s until 2016, when it experienced an abrupt decline. A number of mechanisms have been proposed for both the gradual increase and abrupt decline of Antarctic sea ice, but how each mechanism manifests spatially and temporally remains poorly understood. Here, we use a statistical method called low-frequency component analysis to analyze the spatial-temporal structure of observed Antarctic sea-ice concentration variability. The identified patterns reveal distinct modes of low-frequency sea ice variability. The leading mode, which accounts for the large-scale, gradual expansion of sea ice, is associated with the Interdecadal Pacific Oscillation and resembles the observed sea-surface temperature trend pattern that climate models have trouble reproducing. The second mode is associated with the central Pacific El Niño–Southern Oscillation (ENSO) and the Southern Annular Mode, and accounts for most of the sea ice variability in the Ross Sea. The third mode is associated with the eastern Pacific ENSO and Amundsen Sea Low, and accounts for most of the pan-Antarctic sea-ice variability and almost all of the sea ice variability in the Weddell Sea. This mode is associated with periods of abrupt Antarctic sea-ice decline and is related to a weakening of the circumpolar westerlies, which favors surface warming through a shoaling of the ocean mixed layer and decreased northward Ekman heat convergence. Broadly, these results suggest that climate model biases in long-term Antarctic sea-ice and global sea-surface temperature trends are related to each other and that eastern Pacific ENSO variability causes abrupt sea ice changes. [ABSTRACT FROM AUTHOR]

Published
2023
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16. Arctic Sea Ice in CMIP6

Author

Notz, Dirk, Dörr, Jakob, Bailey, David A, Blockley, Ed, Bushuk, Mitchell, Boldingh Debernard, Jens, Dekker, Evelien, DeRepentigny, Patricia, Docquier, David, Fučkar, Neven S., Fyfe, John C., Jahn, Alexandra, Holland, Marika, Hunke, Elizabeth, Iovino, Doroteaciro, Khosravi, Narges, Gurvan, Madec, Massonnet, François, O'Farrell, Siobhan, Petty, Alek, Rana, Arun, Roach, Lettie, Rosenblum, Erica, Rousset, Clement, Semmler, Tido, Stroeve, Julienne, Toyoda, Takahiro, Tremblay, Bruno, Tsujino, Hiroyuki, Vancoppenolle, Martin, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Computational Research Division [LBNL Berkeley] (CRD), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Centre Georges Lemaître for Earth and Climate Research [Louvain] (TECLIM), Earth and Life Institute [Louvain-La-Neuve] (ELI), Université Catholique de Louvain = Catholic University of Louvain (UCL)-Université Catholique de Louvain = Catholic University of Louvain (UCL), Environment and Climate Change Canada, Institute of Arctic and Alpine Research (INSTAAR), University of Colorado [Boulder], Oceanography Section [Boulder], National Center for Atmospheric Research [Boulder] (NCAR), Los Alamos National Laboratory (LANL), Euro-Mediterranean Center on Climate Change (CMCC), Nucleus for European Modeling of the Ocean (NEMO R&D ), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), National Snow and Ice Data Center (NSIDC), Department of Atmospheric and Oceanic Sciences [Montréal], McGill University = Université McGill [Montréal, Canada], Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), UCL - SST/ELI/ELIC - Earth & Climate, Institute of Arctic Alpine Research [University of Colorado Boulder] (INSTAAR), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)

Subjects
model evaluation, Climate Research, 010504 meteorology & atmospheric sciences, sea ice, CMIP6, Arctic, climate models, model evaluation, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], 551.41, 010502 geochemistry & geophysics, 01 natural sciences, Klimatforskning, Arctic, climate models, Sea ice, 14. Life underwater, CMIP6, 0105 earth and related environmental sciences, geography, geography.geographical_feature_category, Global warming, Ensemble average, Arctic ice pack, sea ice, The arctic, Geophysics, 13. Climate action, Internal variability, Climatology, Environmental science, General Earth and Planetary Sciences, Climate model
Abstract

We examine CMIP6 simulations of Arctic sea‐ice area and volume. We find that CMIP6 models produce a wide spread of mean Arctic sea‐ice area, capturing the observational estimate within the multimodel ensemble spread. The CMIP6 multimodel ensemble mean provides a more realistic estimate of the sensitivity of September Arctic sea‐ice area to a given amount of anthropogenic CO2 emissions and to a given amount of global warming, compared with earlier CMIP experiments. Still, most CMIP6 models fail to simulate at the same time a plausible evolution of sea‐ice area and of global mean surface temperature. In the vast majority of the available CMIP6 simulations, the Arctic Ocean becomes practically sea‐ice free (sea‐ice area, Plain Language Summary: We examine simulations of Arctic sea ice from the latest generation of global climate models. We find that the observed evolution of Arctic sea‐ice area lies within the spread of model simulations. In particular, the latest generation of models performs better than models from previous generations at simulating the sea‐ice loss for a given amount of CO2 emissions and for a given amount of global warming. In most simulations, the Arctic Ocean becomes practically sea‐ice free (sea‐ice area, Key Points: CMIP6 model simulations of Arctic sea‐ice area capture the observational record in the multimodel ensemble spread. The sensitivity of Arctic sea ice to changes in the forcing is better captured by CMIP6 models than by CMIP5 and CMIP3 models. The majority of available CMIP6 simulations lose most September sea ice for the first time before 2050 in all scenarios., National Science Foundation (NSF) http://dx.doi.org/10.13039/100000001, National Center for Atmospheric Research http://dx.doi.org/10.13039/100005323, NSF http://dx.doi.org/10.13039/100000001, CSIRO http://dx.doi.org/10.13039/501100000943, Earth Systems and Climate Change Hub of the Australian Government's National Environmental Science Program, European Union's Horizon 2020 Research and Innovation programme, 727862 APPLICATE, Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme, Research Concile of Norway, Arctic Across Scales Project, Natural Sciences and Engineering Council of Canada http://dx.doi.org/10.13039/501100000038, Fond de recherche du Qubec‐Nature et Technologies, Canadian Meteorological and Oceanographic Society http://dx.doi.org/10.13039/501100002789, EU Horizon 2020 OSeaIce project, German Ministry for Education and Research, H2020 MSCA IF, Regional and Global Modeling and Analysis program, NSF‐OPP, Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659, National Science Foundation http://dx.doi.org/10.13039/100000001, National Oceanic and Atmospheric Administration http://dx.doi.org/10.13039/100000192, Canada C150 Chair Program, Bundesministerium für Bildung und Forschung (BMBF) http://dx.doi.org/10.13039/501100002347, Department for Business, Energy and Industrial Strategy (BEIS) http://dx.doi.org/10.13039/100011693, Deutsche Forschungsgemeinschaft (DFG) http://dx.doi.org/10.13039/501100001659, EC | H2020 | H2020 Priority Excellent Science | H2020 Marie Skłodowska‐Curie Actions (MSCA) http://dx.doi.org/10.13039/100011102, F.R.S. ‐ FNRS | Fonds pour la Formation la Recherche dans l'Industrie et dans l'Agriculture (FRIA), Knut och Alice Wallenbergs Stiftelse (Knut and Alice Wallenberg Foundation) http://dx.doi.org/10.13039/501100004063, Max Planck Society http://dx.doi.org/10.13039/501100004189, Research Council of Norway http://dx.doi.org/10.13039/501100005416, U.S. Department of Energy (DOE) http://dx.doi.org/10.13039/100000015

Published
2020
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19. Rapid Sea Ice Changes in the Future Barents Sea.

Author

Rieke, Ole, Årthun, Marius, and Dörr, Jakob Simon

Abstract

Winter Arctic sea ice loss is strongest in the Barents Sea. The anthropogenic ice decline is superimposed by pronounced internal variability that represents a large source of uncertainty in future climate projections. A notable manifestation of internal variability are periods of rapid ice loss or growth that greatly exceed the anthropogenic trend. These rapid ice change events are associated with large displacements of the sea ice edge which could potentially have both local and remote impacts on the climate system. In this study we accordingly present the first investigation of the frequency and drivers of these rapid ice change events in the future Barents Sea, using multi-member ensemble simulations from CMIP5 and CMIP6. A majority of rapid sea ice changes are triggered by trends in ocean heat transport or surface heat fluxes. Rapid ice change events are a common feature of the future Barents Sea until the region becomes close to ice free. As their evolution over time is closely tied to the average sea ice conditions, rapid ice changes in the Barents Sea serve as a precursor for future changes in adjacent seas. [ABSTRACT FROM AUTHOR]

Published
2022
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21. Antarctic Sea Ice Area in CMIP6

Author

Roach, Lettie A., Dörr, Jakob, Holmes, Caroline R., Massonnet, Franҫois, Blockley, Edward W., Notz, Dirk, Rackow, Thomas, Raphael, Marilyn N., O'Farrell, Siobhan, Bailey, David A., Bitz, Cecilia M., Roach, Lettie A., Dörr, Jakob, Holmes, Caroline R., Massonnet, Franҫois, Blockley, Edward W., Notz, Dirk, Rackow, Thomas, Raphael, Marilyn N., O'Farrell, Siobhan, Bailey, David A., and Bitz, Cecilia M.

Published
2020

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