A new study by University of Florida researchers reveals that while climate change is causing widespread ice shelf loss in Antarctica, the frequency and size of major iceberg calving events have not significantly changed. The study, published in the journal [Journal Name], used 47 years of satellite data to analyze extreme calving events, finding no evidence of an increase in their size or frequency over time. While smaller calving events are becoming more common, the researchers suggest that the primary threat to Antarctic ice shelves is 'death by a thousand cuts' from numerous small calving events.
A recent study conducted by University of Florida geologists and geographers has shed new light on the effects of climate change on Antarctic ice shelves. The study, led by Assistant Professor Emma MacKie and Assistant Professor Katy Serafin, along with a collaborator at the Colorado School of Mines, found that while there has been broad ice shelf loss due to warming temperatures, the frequency and size of major iceberg calving events have not changed significantly.
\Calving, when chunks of ice break off from ice shelves to form icebergs, is common and increasingly influenced by climate change. For extremely large icebergs, this process is typically slow, often starting with small rifts that spread across the ice shelf before fully breaking off. These rifts can be detected as they form and grow using satellite data, but their random nature and the risks associated with sending scientists to observe them in-person make it extremely difficult to predict when future rifts or calving events may occur. \Major calving events are particularly challenging to study. While smaller calving events occur frequently, large events -- where over 100 square kilometers of ice break away -- are exceptionally rare. This study is the first of its kind to focus on these large calving events. Even with 47 years' worth of satellite data from 1976 to 2023, the team was still faced with a small sample size. This challenge was addressed with extreme value theory, a type of statistical analysis used when studying rare natural disasters like major earthquakes, extreme floods, or volcanic eruptions. Serafin, an expert on extreme flooding, was no stranger to this type of data analysis. 'Statistical models relating event size and frequency are tools that have been used for estimating rare flood events, like a 100-year flood, for decades,' said Serafin.'Now that satellite imagery can more consistently track large calving events, we thought we'd test whether we could apply the same tools for understanding how likely these massive calving events are.' Using this method, the team analyzed extreme calving events found in the satellite record and developed a model to predict the likelihood of these events over time. \While creating their models, researchers also developed scenarios to predict how large calving events could be. By their estimates, a once in a decade iceberg could be as large as 6,100 square kilometers, only slightly larger than an extreme calving event in 2017, when an iceberg roughly the size of Delaware broke off the Antarctic ice sheet. A once in a century eventcould produce an iceberg about 45,000 square kilometers, slightly larger than the entire country of Denmark. 'A once in a century iceberg would be several times larger than any in the observational record and would have a significant impact on ice-sheet stability and ocean processes,' said MacKie. The team found no evidence that large icebergs have increased in size over the last half century, with the peak iceberg surface areas occurring between 1986 and 2000. This indicates that extreme calving events do not correlate with climate change, although overall ice shelf loss has increased due to climate change. While extreme calving events continue to be rare and may be part of a larger natural cycle, more numerous small calving events have dominated Antarctic ice shelf loss over the last half century.
Climate Change Antarctica Ice Shelves Iceberg Calving Satellite Data Extreme Value Theory
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