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Sea ice in both polar regions is an important indicator of the expression of global climate change and its polar amplification. Consequently, broad interest exists on sea ice coverage, variability and long-term change. However, its predictability is complex and it depends strongly on different atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we applied a robust statistical model based on different oceanic and atmospheric parameters to calculate an estimate of the September sea ice extent (SSIE) on a monthly timescale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive/critical regions in global coupled climate models with a focus on sea ice formation. [ABSTRACT FROM AUTHOR]

Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad interest exists on sea ice coverage, variability and long term change. However, its predictability is complex and it depends on various atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we developed a robust statistical model based on oceanic and different atmospheric variables to calculate an estimate of the September sea ice extent (SSIE) on monthly time scale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' atmospheric and oceanic conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation. [ABSTRACT FROM AUTHOR]

In austral spring 2016 the Antarctic region experienced anomalous sea ice retreat in all sectors, with sea ice extent in October and November 2016 being the lowest in the Southern Hemisphere over the observational period (1979-present). The extreme sea ice retreat was accompanied by widespread warming along the coastal areas as well as in the interior of the Antarctic continent. This exceptional event occurred along with a strong negative phase of the Southern Annular Mode (SAM) and the moistest and warmest spring on record, over large areas covering the Indian Ocean, the Ross Sea and the Weddell Sea. In October 2016, the positive anomalies of the totally integrated water vapor (IWV) and 2m air temperature (T2m) over the Indian Ocean, western Pacific, Bellingshausen Sea and southern part of Ross Sea were unprecedented in the last 39 years. In October and November 2016, when the largest magnitude of negative daily sea ice concentration anomalies was observed, repeated episodes of poleward advection of warm and moist air took place. These results suggest the importance of moist and warm air intrusions into the Antarctic region as one of the main contributors to this exceptional sea ice retreat event. [ABSTRACT FROM AUTHOR]

In austral spring 2016 the Antarctic region experienced anomalous sea ice retreat in all sectors, with sea ice extent in October and November 2016 being the lowest in the Southern Hemisphere over the observational record (1979-present). The extreme sea ice retreat was accompanied by widespread warming along the coastal areas as well as in the interior of the Antarctic continent. This exceptional event occurred along with a strong negative phase of the Southern Annular Mode (SAM) and the wettest and warmest spring on record, over large areas covering the Indian ocean, the Ross Sea and the Weddell Sea. In October 2016, the positive anomalies of the totally integrated water vapor (IWV) and 2 m air temperature (TT) over the Indian Ocean, Western Pacific, Bellingshausen Sea and southern part of Ross Sea were unprecedented in the last 39 years. In October and November 2016, when the lowest daily sea ice concentration anomalies were observed, repeated episodes of poleward advection of warm and moist air took place, with the most intense episode occurring at the end of November 2016. These results suggest the importance of moist and warm air intrusions into the Antarctic region as one of the main contributors to this exceptional sea ice retreat event. [ABSTRACT FROM AUTHOR]

Due to its involvement in numerous feedbacks, sea ice plays a crucial role not only for polar climate but also at global scale. We analyse state-of-the-art observed, reconstructed, and modelled sea-ice concentration (SIC) together with sea surface temperature (SST) to disentangle the influence of different forcing factors on the variability of these coupled fields. Canonical Correlation Analysis provides distinct pairs of coupled Arctic SIC–Atlantic SST variability which are linked to prominent oceanic and atmospheric modes of variability over the period 1854–2017. The first pair captures the behaviour of the Atlantic meridional overturning circulation (AMOC) while the third and can be associated with the North Atlantic Oscillation (NAO) in a physically consistent manner. The dominant global SIC–Atlantic SST coupled mode highlights the contrast between the responses of Arctic and Antarctic sea ice to changes in AMOC over the 1959–2021 period. Model results indicate that coupled SST–SIC patterns can be associated with changes in ocean circulation. We conclude that a correct representation of AMOC-induced coupled SST–SIC variability in climate models is essential to understand the past, present and future sea-ice evolution. [ABSTRACT FROM AUTHOR]