Historical and Projected Antarctic Sea Ice Trends Across High‐Resolution Coupled Model Hierarchies

Abstract Coupled climate models generally simulate a decline in Antarctic sea ice extent (SIE) over the satellite period, failing to capture the observed near‐zero trend. Recent work has suggested that high‐resolution ocean models could ameliorate this issue via improved representation of mesoscale ocean processes, which may delay simulated Antarctic SIE decline. We investigate this hypothesis using two high‐resolution hierarchies of coupled climate models developed at GFDL and NCAR, which span atmospheric resolutions of 0.25–1 and ice‐ocean resolutions of 0.1–1, as well as three generations of Coupled Model Intercomparison Project (CMIP) models. Across the high‐resolution hierarchies and CMIP ensembles, we find no clear relationship between ocean and atmospheric resolution and Antarctic SIE trends over both the satellite period and the remainder of the 21st century. Climate models that reproduce observed trends in individual ensemble members are those that exhibit large amplitude multi‐decadal Southern Ocean climate variability.

Authors

Institutions

Publication Details

Journal
Geophysical Research Letters
Published
2026-08-20
DOI
https://doi.org/10.1029/2026gl124043
Primary Topic
Arctic and Antarctic ice dynamics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Historical and Projected Antarctic Sea Ice Trends Across High‐Resolution Coupled Model Hierarchies

Thomas Rackow, Yan‐Ting Chen, Yongfei Zhang, Helge Goessling et al.
Geophysical Research Letters
Arctic and Antarctic ice dynamics
article

Historical and Projected Antarctic Sea Ice Trends Across High‐Resolution Coupled Model Hierarchies

Thomas Rackow, Yan‐Ting Chen, Yongfei Zhang, Helge Goessling, William J. Hurlin, Mitchell Bushuk, William King Gregory, David Bonan, Stephen M. Griffies
article en

Abstract

Abstract Coupled climate models generally simulate a decline in Antarctic sea ice extent (SIE) over the satellite period, failing to capture the observed near‐zero trend. Recent work has suggested that high‐resolution ocean models could ameliorate this issue via improved representation of mesoscale ocean processes, which may delay simulated Antarctic SIE decline. We investigate this hypothesis using two high‐resolution hierarchies of coupled climate models developed at GFDL and NCAR, which span atmospheric resolutions of 0.25–1 and ice‐ocean resolutions of 0.1–1, as well as three generations of Coupled Model Intercomparison Project (CMIP) models. Across the high‐resolution hierarchies and CMIP ensembles, we find no clear relationship between ocean and atmospheric resolution and Antarctic SIE trends over both the satellite period and the remainder of the 21st century. Climate models that reproduce observed trends in individual ensemble members are those that exhibit large amplitude multi‐decadal Southern Ocean climate variability.

Geophysical Research LettersVol. 53(16)
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (DE), Centre National de la Recherche Scientifique (FR), National Oceanic and Atmospheric Administration (US), Cooperative Institute for Research in Environmental Sciences (US), NOAA Geophysical Fluid Dynamics Laboratory (US), Princeton University (US), University of Washington (US), Sorbonne Université (FR), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (FR), Oldham Council (GB), Institut de Recherche pour le Développement (FR)
Cooperative Institute for Climate, Ocean, and Ecosystem Studies, University of Washington, U.S. Department of Commerce
Climate action
Openalex Percentile: Top 13%
Arctic and Antarctic ice dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.