Sea ice plays an important role in the Earth's climate system and provides an important habitat component for several marine mammal species. Scientists recently developed a new modeling approach to estimate the thickness of Arctic sea ice. It's the only hemisphere-scale model based entirely on relationships among historical observations. Developed by scientists with the U.S. Geological Survey (USGS) and the Russian Academy of Sciences, Moscow, the new model is described in the February 15 issue of Journal of Climate (v. 21 no. 4, p. 716-729).
Reductions in Arctic sea ice during the past decade have elevated scientific and societal questions about the likelihoods of future scenarios. Is the recent sea-ice decline an indicator of anthropogenic forcing that will lead the Arctic to an unprecedented future of reduced ice cover, or is the decline simply an ephemeral expression of natural low-frequency climate oscillations that will eventually return the Arctic to prior conditions? This unanswered question has significant ramifications for Arctic ecology as well as the Earth's climate system, and it is being rigorously investigated by numerous scientists throughout the world.
One of those scientists is USGS research wildlife biologist Dave Douglas, who developed and implemented the new model with colleagues Gennady Belchansky and Nikita Platonov of the Russian Academy of Sciences. The authors began collaborating on sea-ice studies nearly 20 years ago because sea ice is the primary habitat for populations of polar bear and Pacific walrus that extend across the United States-Russian border.
Using the new technique, the thickness of Arctic sea ice was estimated monthly from 1982 to 2003. Results showed that average ice thickness and total ice volume fluctuated together during the early study period, peaking in the late 1980s and then declining until the mid-1990s. Thereafter, ice thickness slightly increased, but the total volume of sea ice did not. The authors propose that the total ice volume stayed constant during the study's latter years because while the ice was thickening in the high latitudes of the Arctic, the surrounding sea ice was melting. Sea ice, however, can become only so thick, and if Arctic sea ice continues to melt, the total volume of sea ice in the Arctic will decrease.
The most dramatic losses in sea-ice cover have occurred since 2003, and as scientists acquire newer data, they will apply the new model to study recent years of ice thickness and volume change.
The modeling approach uses sea-ice-motion data to follow parcels of ice backward in time at monthly intervals for as long as 3 years while accumulating a history of the solar radiation and air temperature to which the ice was exposed. The model was constructed by fitting these data with an ice parcel's known thickness to determine how the thickness of sea ice changes in response to different environmental conditions. Data on the known thickness were obtained from historical surface-coring studies, as well as ice-draft measurements made by military submarines during Arctic cruises.
"Sea ice is affected by the accumulation of environmental factors to which it has been exposed," said USGS Director Mark Myers. "Understanding the natural variability of sea-ice thickness is critical for improving global-climate models. Sea ice regulates energy exchange and plays an important role in the Earth's climate system."
The new model, built on historical observations, complements thermodynamic models that simulate ice thickness. Science benefits from having different models; comparing different model outputs can help improve predictive capabilities. Many scientists worldwide are using satellite and ground observations of the Arctic's atmosphere, ice, and ocean to gain a better understanding of how changes at the top of the world affect ecosystems both locally and globally.
For additional information about this research, listen to a podcast interview with David Douglas, visit the USGS "Remote Sensing and Sea Ice Research" Web site, and (or) read the recently published article: Belchansky, G.I., Douglas, D.C., and Platonov, N.G., 2008, Fluctuating Arctic sea ice thickness changes estimated by an in-situ learned and empirically forced neural network model: Journal of Climate, v. 21 no. 4, p. 716-729, doi: 10.1175/2007JCLI1787.1 [URL http://ams.allenpress.com/perlserv/?request=get-archive&issn=1520-0442].
in this issue:
New Method to Estimate Sea-Ice Thickness