This Pacific-origin water brings both heat and unique biogeochemical properties, contributing to a changing Arctic ecosystem. ![]() Upward turbulent mixing of these sub-surface pockets of heat is likely accelerating sea ice melt in the region. Though some heat is lost to the atmosphere during autumn cooling, a significant fraction of the incoming warm, salty water subducts (dives beneath) below a cooler fresher layer of near-surface water, subsequently extending hundreds of kilometers into the Beaufort Gyre. Unprecedented quantities of heat are entering the Pacific sector of the Arctic Ocean through Bering Strait, particularly during summer months. Supplementary materials accompanying this paper appear on-line. We also show that our statistical model can generate good forecasts of aggregate quantities such as overall and regional sea ice volume. We show that existing forecasts produced by ensembles of deterministic dynamic models can have large errors and poor calibration. Point predictions and prediction intervals from our model offer comparable accuracy and improved calibration compared with existing forecasts. Using the most complete estimates of sea ice thickness currently available, we apply our method to forecast Arctic sea ice thickness. ![]() Our approach combines a contour model to predict the ice-covered region with a Gaussian random field to model ice thickness conditional on the ice-covered region. We propose a statistical spatio-temporal two-stage model for sea ice thickness and use it to generate probabilistic forecasts up to three months into the future. Predicting changes in Arctic sea ice thickness is vital in a changing Arctic for making decisions about shipping and resource management in the region. ![]() In recent decades, warming temperatures have caused sharp reductions in the volume of sea ice in the Arctic Ocean.
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