Forecasting seasonal sea ice

New research by a team of scientists that includes NCAR’s Marika Holland takes a close look at making seasonal forecasts of Arctic sea ice coverage. The study was published in Geophysical Research Letters in September.

The researchers used the NCAR-based Community Climate System Model (CCSM), which has successfully simulated the Arctic sea ice decline observed over the past few decades. (Watch a video of Holland discussing CCSM visualizations that show possible future impacts of climate change on sea ice.) They found that there is the potential to predict sea ice coverage for a given summer by assessing the sea ice and ocean conditions from the previous September. This is because initial conditions in a model affect how the ice responds to weather conditions for the few years that follow.

Forecasting conditions beyond about 3–5 years into the future, however, depends on understanding how longer-term climate trends are influencing the ice, since the effect of greenhouse gas increases eventually overrides initial starting conditions and becomes the primary influence on the ice pack.

Many scientists believe that the Arctic could be ice-free in the summer by the middle of this century. According to the National Snow and Ice Data Center, when the ice reached its annual low in mid-September 2011, its extent was 36% less than the average minimum for 1979–2000 and was just a fraction above the record low, set in 2007. Losses in ice volume have been even more dramatic than for extent.

The practice of predicting sea ice has long been maintained by Inuit elders, whose communities depend on the ice for travel and hunting. More recently, the shipping and resource extraction industries have taken an interest in forecasting sea ice, with an eye toward whether the Northwest and Northeast passages—which provide fast travel between the Atlantic and Pacific oceans—might be ice-free in the summer.

E. Blanchard-Wrigglesworth, C. M. Bitz, M. M. Holland, “Influence of initial conditions and climate forcing on predicting Arctic sea ice,” Geophysical Research Letters, 10.1029/2011GL048807


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