Antarctic sea ice multidecadal variability triggered by Southern Annular Mode and deep convection DOI Creative Commons
Yushi Morioka,

Syukuro Manabe,

Liping Zhang

et al.

Communications Earth & Environment, Journal Year: 2024, Volume and Issue: 5(1)

Published: Nov. 8, 2024

Antarctic sea ice exerts great influence on Earth's climate by controlling the exchange of heat, momentum, freshwater, and gases between atmosphere ocean. extent has undergone a multidecadal slight increase followed substantial decline since 2016. Here we utilize 300-yr data assimilation reconstruction two NOAA/GFDL five CMIP6 model simulations to demonstrate variability extent. Stronger westerlies associated with Southern Annular Mode (SAM) enhance upwelling warm saline water from subsurface The consequent salinity weakens upper-ocean stratification, induces deep convection, in turn brings more surface. This salinity-convection feedback triggered SAM provides favorable conditions for decrease. Processes acting reverse are found cause increase, although it evolves slower than Multidecadal anomalies preceded wind which may induce melting, according combined approach using prolonged reconstructions coupled

Language: Английский

Clouds Are Crucial to Capture Antarctic Sea Ice Variability DOI Creative Commons
G Cesana, Lettie A. Roach, Edward Blanchard‐Wrigglesworth

et al.

Geophysical Research Letters, Journal Year: 2025, Volume and Issue: 52(3)

Published: Feb. 4, 2025

Abstract Models from the Coupled Model Intercomparison Project phase 6 (CMIP6) typically struggle to reproduce observed Antarctic sea ice trends, a bias that is substantially alleviated when constraining winds. We use wind‐nudged simulations two CMIP models investigate influence of clouds on area (SIA). find nudging model winds in coupled toward reanalysis, addition improving SIA variability, crucial realistic anomalies cloud radiative effect (CRE) and cover. Biases variability properties at edge—characterized by CRE anomalies—help explain remaining discrepancies between simulated SIA; 1 anomaly corresponds negative 0.43 anomaly. Finally, we most CMIP6 show positive trends biases, which should contribute enhanced decline, long‐standing models.

Language: Английский

Citations

1
Living with uncertainty: Using multi-model large ensembles to assess emperor penguin extinction risk for the IUCN Red List DOI Creative Commons
Stéphanie Jenouvrier,

Alice Eparvier,

Bilgecan Şen

et al.

Biological Conservation, Journal Year: 2025, Volume and Issue: unknown, P. 111037 - 111037

Published: March 1, 2025

Language: Английский

Citations

1
The future extent of the Anthropocene epoch: A synthesis DOI Creative Commons
Colin Summerhayes, Jan Zalasiewicz, Martin J. Head

et al.

Global and Planetary Change, Journal Year: 2024, Volume and Issue: unknown, P. 104568 - 104568

Published: Sept. 1, 2024

Language: Английский

Citations

8
A twenty-first century structural change in Antarctica’s sea ice system DOI Creative Commons
Marilyn Raphael, Thomas Maierhofer, Ryan L. Fogt

et al.

Communications Earth & Environment, Journal Year: 2025, Volume and Issue: 6(1)

Published: Feb. 21, 2025

Language: Английский

Citations

0
Changes in seasonality and extent of Antarctic sea ice cover over the satellite record DOI

C. C. Bajish,

S. Kshitija,

Babula Jena

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
Brief communication: New perspectives on the skill of modelled sea ice trends in light of recent Antarctic sea ice loss DOI Creative Commons
Caroline Holmes, Thomas J. Bracegirdle, Paul R. Holland

et al.

˜The œcryosphere, Journal Year: 2024, Volume and Issue: 18(12), P. 5641 - 5652

Published: Dec. 5, 2024

Abstract. Most climate models do not reproduce the 1979–2014 increase in Antarctic sea ice cover. This was a contributing factor successive Intergovernmental Panel on Climate Change reports allocating low confidence to model projections of over 21st century. We show that recent rapid declines bring observed area trends back into line with and confirm discrepancies exist for earlier periods. demonstrates exhibit different skill timescales discuss possible interpretations this linear trend assessment given abrupt nature changes implications future research.

Language: Английский

Citations

1
Penguins coping with a changing ocean DOI
David G. Ainley, Rory P. Wilson

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

Language: Английский

Citations

0
Deep Learning for Antarctic Sea Ice Anomaly Detection and Prediction: A Two-Module Framework DOI Creative Commons
Maloy Kumar Devnath, Sudip Chakraborty, Vandana P. Janeja

et al.

Published: Oct. 29, 2024

The Antarctic sea ice cover plays a crucial role in regulating global climate and level rise. recent retreat of the Sea Ice Extent accelerated melting sheets (which causes rise) raise concerns about impact change. Understanding spatial patterns anomalous events is for improving models predicting future rise, as serves protective barrier sheets. This paper proposes two-module framework based on Deep Learning that utilizes satellite imagery to identify predict non-anomalous regions ice. first module focuses identifying current day by analyzing difference between consecutive images over time. second then leverages day's information predicts next regions. approach aims improve our ability monitor critical changes cover.

Language: Английский

Citations

0
Antarctic sea ice multidecadal variability triggered by Southern Annular Mode and deep convection DOI Creative Commons
Yushi Morioka,

Syukuro Manabe,

Liping Zhang

et al.

Communications Earth & Environment, Journal Year: 2024, Volume and Issue: 5(1)

Published: Nov. 8, 2024

Antarctic sea ice exerts great influence on Earth's climate by controlling the exchange of heat, momentum, freshwater, and gases between atmosphere ocean. extent has undergone a multidecadal slight increase followed substantial decline since 2016. Here we utilize 300-yr data assimilation reconstruction two NOAA/GFDL five CMIP6 model simulations to demonstrate variability extent. Stronger westerlies associated with Southern Annular Mode (SAM) enhance upwelling warm saline water from subsurface The consequent salinity weakens upper-ocean stratification, induces deep convection, in turn brings more surface. This salinity-convection feedback triggered SAM provides favorable conditions for decrease. Processes acting reverse are found cause increase, although it evolves slower than Multidecadal anomalies preceded wind which may induce melting, according combined approach using prolonged reconstructions coupled

Language: Английский

Citations

0