NASA has developed a new forecasting model that allows researchers to make better estimates of the rate of loss of Arctic sea ice.
Each year in spring scientists are faced with the tricky task of estimating exactly how much ice will disappear from its maximum wintertime extent. Such information is vital for the navy, shipping companies and native people who depend on sea ice for hunting.
NASA satellites have been measuring sea ice in the Arctic since 1979, so the simplest approach to making an estimate is to assume a continuation of the long-term trend but that risks missing outlier years with a higher or lower ice extent.
So researchers have developed a new model that analyses the physical characteristics of the sea ice cover as the melt season develops which enables them to compare it to long-term ternds.
“What we have shown is that we can use information collected in the spring and onwards to determine if we should see more or less ice come the end of summer than expected from the long-term decline,” said Alek Petty, lead author of the new paper, which was published recently in the journal Earth’s Future.
The study used satellite measurements of sea ice coverage and melt onset – the time when open sea appears in the Arctic Ocean. Petty’s team discovered that forecasts based on melt onset were most reliable in early spring, while sea ice coverage-based predictions for the minimum extent in September, were more reliable from June onwards.
The team tested their technique by running the numbers for each year of the satellite record, comparing the results of the estimates against both the actual minimum extent for that year and what the long-term trend would have predicted.
“We found that our forecast model does much better than the linear trend at capturing what actually happened to the sea ice in any specific year,” Petty said. “Our model is very good at catching the highs and the lows. The absolute values? Not exactly, but it tends to do very well at seeing when the sea ice extent is going to go up and when it’s going to go down compared to what we might be expecting for that year.”
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