Antarctica InSync Theme 7: Variability, Extremes and Tipping in a Changing Antarctic Climate

Antarctica is changing faster than our current observation networks can robustly assess or predict. Recent extreme events – major ice-shelf collapse, unprecedented heatwaves and abrupt, record-low winter sea ice – show that rare extremes can rapidly reshape the Antarctic system. These changes matter well beyond the polar regions: Antarctica influences global sea level, ocean circulation, and the whole climate system. This white paper sets out the case for Antarctica InSync (2027–2030) to deliver a four-year, coordinated observational baseline ahead of the International Polar Year 2031/32, so it is possible to distinguish temporary anomalies from long-term shifts, detect early warning signs of tipping points, and improve the evidence base for risk management.

The result is more reliable projections, better attribution of drivers, and earlier detection of destabilising trajectories – directly supporting policy decisions on climate adaptation, coastal planning, and the design of international monitoring commitments, specifically targeting the following four focus areas bridging ocean-atmosphere-ice interactions and climate variability:
• Snow, firn and SMB: Fund coordinated field and satellite-calibration measurements to reduce the largest uncertainty in sea-level projections: how snowfall, melt, refreezing and runoff will change.
• Atmosphere and water cycle: Expand weather, precipitation and water-isotope observations to track storms and moisture transport inland – essential for forecasting extremes and future snowfall/rainfall shifts.
• Ocean–sea ice–atmosphere coupling: Invest in marginal-ice-zone and ice shelves fronts observations to understand how sea-ice loss and ocean warming amplify extremes, alter heat/moisture exchange, destabilise ice shelves and weaken deep-water formation.
• Variability and warming detection: Combine new observations and ice-core and marine records to separate human-driven trends from natural variability and identify early warning signals of irreversible change.