Iceberg drift and melting rates in the northwestern Weddell Sea, Antarctica: Novel automated regional estimates through machine learning

ANAIS DA ACADEMIA BRASILEIRA DE CIENCIAS(2022)

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摘要
Global warming and its consequences on polar regions have been thoroughly discussed in recent times. One of those consequences is the freshwater flux and the associated cooling and freshening that result from iceberg melting. Despite the potential impact, large uncertainties exist resulting mostly from the complexity to follow icebergs from space, which make the few existing estimates essentially model-based. This study takes advantage of state-of-art machine learning methods to present novel prevalent trajectories and potential freshwater input from 450 icebergs ranging from 1 to 2765 km(2) across the northwestern Weddell Sea, Antarctica. The main results highlight the predominance of a northward flux and the entrance of icebergs up to 10 km(2) into Bransfield Strait associated with the main current systems along the Antarctic Peninsula. The present analysis on such a large number of icebergs unveils an average drift speed of 3.4 +/- 2.7 km day(-1) and an average disintegration rate of similar to 62% per year, representing an integrated potential regional freshwater input of 133.62 Gt yr(-1). Altogether, this study adds new knowledge to the complex problem of autonomous applications for iceberg detection and tracking, further exploring such methods on a very dynamic region of singular importance for the ocean and climate studies.
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关键词
icebergs, Southern Ocean, Antarctica, SAR, machine learning
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