Recovery mechanism for Arctic ice. Global climate change is progressively reducing the Arctic Ocean’s summer ice cover. That retreat harbors an obvious positive-feedback mechanism: Because ice is more reflective than open water, the shrinking cover means more absorption of solar radiation, leading, in turn, to more loss of ice. (See the article by Ron Kwok and Norbert Untersteiner on page 36.) That raises the prospect of a possible tipping point at which the thus-far relatively gradual retreat of summer ice “runs away,” leaving the Arctic Ocean perennially free of summer ice long before the date—sometime late in this century—generally deduced from climate models. But might not those models be made to reveal such threshold behavior by subjecting them to strong perturbations? Steffen Tietsche and coworkers at the Max Planck Institute for Meteorology in Hamburg, Germany, tried that with a widely used climate model. What would happen, they asked, if by a random fluctuation in some year, the Arctic Ocean became completely free of ice on 1 July? The figure, plotting ice cover in September, when it’s typically least, shows the result (in blue) when that initial perturbation is imposed in a particular year. In every case, the September cover reverts to its gradually falling unperturbed level (black curve) within about two years. Tietsche and company attribute such prompt recovery primarily to a negative-feedback mechanism that damps the albedo reinforcement: During the long, dark winter, the lack of insulating ice produces an anomalously warm arctic atmosphere, whose top radiates heat away faster and whose sides receive less wind-driven heat from temperate latitudes. So, they conclude, a tipping point at which the loss of summer sea ice becomes sudden and irreversible is unlikely. (S. Tietsche et al., Geophys. Res. Lett. 38, L02707, 2011, doi:10.1029/2010GL045698.)
The finding that the Saturnian moon may host layers of icy slush instead of a global ocean could change how planetary scientists think about other icy moons as well.
Modeling the shapes of tree branches, neurons, and blood vessels is a thorny problem, but researchers have just discovered that much of the math has already been done.
January 29, 2026 12:52 PM
This Content Appeared In
Volume 64, Number 4
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