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JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 109, C10017, doi:10.1029/2004JC002388, 2004

Spatial and temporal multiyear sea ice distributions in the Arctic: A neural network analysis of SSM/I data, 1988–2001

Gennady I. Belchansky

Space Monitoring and Ecoinformation Systems Sector, Institute of Ecology, Russian Academy of Sciences, Moscow, Russia


David C. Douglas

U.S. Geological Survey, Juneau, Alaska, USA


Ilia V. Alpatsky

Space Monitoring and Ecoinformation Systems Sector, Institute of Ecology, Russian Academy of Sciences, Moscow, Russia


Nikita G. Platonov

Space Monitoring and Ecoinformation Systems Sector, Institute of Ecology, Russian Academy of Sciences, Moscow, Russia


Abstract

Arctic multiyear sea ice concentration maps for January 1988–2001 were generated from SSM/I brightness temperatures (19H, 19V, and 37V) using modified multiple layer perceptron neural networks. Learning data for the neural networks were extracted from ice maps derived from Okean and ERS satellite imagery to capitalize on the stability of active radar multiyear ice signatures. Evaluations of three learning algorithms and several topologies indicated that networks constructed with error back propagation learning and 3-20-1 topology produced the most consistent and physically plausible results. Operational neural networks were developed specifically with January learning data, and then used to estimate daily multiyear ice concentrations from daily-averaged SSM/I brightness temperatures during January. Monthly mean maps were produced for analysis by averaging the respective daily estimates. The 14-year series of January multiyear ice distributions revealed dense and persistent cover in the central Arctic surrounded by expansive regions of highly fluctuating interannual cover. Estimates of total multiyear ice area by the neural network were intermediate to those of other passive microwave algorithms, but annual fluctuations and trends were similar among all algorithms. When compared to Radarsat estimates of multiyear ice concentration in the Beaufort and Chukchi Seas (1997–1999), average discrepancies were small (0.9–2.5%) and spatial coherency was reasonable, indicating the neural network's Okean and ERS learning data facilitated passive microwave inversion that emulated backscatter signatures. During 1988–2001, total January multiyear ice area declined at a significant linear rate of −54.3 × 103 km2 yr−1 (−1.4% yr−1). The most persistent and extensive decline in multiyear ice concentration (−3.3% yr−1) occurred in the southern Beaufort and Chukchi Seas. In autumn 1996, a large multiyear ice recruitment of over 106 km2 (mostly in the Siberian Arctic) fully replenished the previous 8-year decline in total area, but it was followed by an accelerated and compensatory decline during the subsequent 4 years. Seventy-five percent of the interannual variation in January multiyear sea ice area was explained by linear regression on two atmospheric parameters: the previous winter's (JFM) Arctic Oscillation index as a proxy to melt duration and the previous year's average sea level pressure gradient across the Fram Strait as a proxy to annual ice export. Consecutive year changes (1994–2001) in January multiyear ice volume were significantly correlated with duration of the intervening melt season (R 2 = 0.73, −80.0 km3 d−1), emphasizing a large thermodynamic influence on the Arctic's mass sea ice balance during summers with anomalous melt durations.

Received 16 March 2004; accepted 3 August 2004; published 30 October 2004.

Keywords: SSM/I; ERS; Okean; passive microwave; multiyear; sea ice.

Index Terms: 1640 Global Change: Remote sensing; 4207 Oceanography: General: Arctic and Antarctic oceanography; 4215 Oceanography: General: Climate and interannual variability (3309).

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Citation: Belchansky, G. I., D. C. Douglas, I. V. Alpatsky, and N. G. Platonov (2004), Spatial and temporal multiyear sea ice distributions in the Arctic: A neural network analysis of SSM/I data, 1988–2001, J. Geophys. Res., 109, C10017, doi:10.1029/2004JC002388.