the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Ensemble-based estimation of sea-ice volume variations in the Baffin Bay
Longjiang Mu
Frank Kauker
Robert Ricker
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The East Siberian Sea has nearly 80% of the subsea permafrost worldwide. The cold layer with a temperature around −1.5 ºC above the sea floor prevents heat transporting from above to melt permafrost and release methane from sediments. However, we observed a warming trend at the seafloor caused by wave-induced vertical mixing in the shelf. The intensified mixing can transport enormous heat downward, leading to warming of more than 3 °C at the bottom, putting the subsea permafrost in high risk.
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Sea ice forecasts are operationally produced using physically based models, but these forecasts are often not accurate enough for maritime operations. In this study, we developed a statistical correction technique using machine learning in order to improve the skill of short-term (up to 10 d) sea ice concentration forecasts produced by the TOPAZ4 model. This technique allows for the reduction of errors from the TOPAZ4 sea ice concentration forecasts by 41 % on average.