Abstract
Sea ice cover in the Arctic and Antarctic is an important indicator of changes in the climate, with important environmental, economic and security consequences. The complexity of the spatio-temporal dynamics of sea ice makes it difficult to assess the temporal nature of the changes—e.g. linear or exponential—and their precise geographical loci. In this study, Koopman Mode Decomposition (KMD) is applied to satellite data of sea ice concentration for the Northern and Southern hemispheres to gain insight into the temporal and spatial dynamics of the sea ice behavior and to predict future sea ice behavior. We observe spatial modes corresponding to the mean and annual variation of Arctic and Antarctic sea ice concentration and observe decreases in the mean sea ice concentration from early to later periods, as well as corresponding shifts in the locations that undergo significant annual variation in sea ice concentration. We discover exponentially decaying spatial modes in both hemispheres and discuss their precise spatial extent, and also perform predictions of future sea ice concentration. The Koopman operator-based, data-driven decomposition technique gives insight into spatial and temporal dynamics of sea ice concentration not apparent in traditional approaches.
Highlights
Sea ice cover in the Arctic and Antarctic is an important indicator of changes in the climate, with important environmental, economic and security consequences
All of the algorithms used gave very similar results. This suggests that the sea ice concentration data dynamical behavior is “well behaved” in the sense that the resulting condition number is sufficiently small that any of the various approximations of the Koopman decomposition are valid h ere[17] and supports the conclusion that the Koopman Mode Decomposition (KMD) results obtained here are physically meaningful and not numerical artifacts
The anomaly correlation coefficient (ACC) values have slightly positive mean values, but as for the 30-year KMD input period results shown above they generally fall below the 0.5–0.6 synoptically useful threshold range. These results show the previously-known existence of long term variation in sea ice concentration[27,28], including long term decreases in sea ice coverage near West Antarctica and in the Arctic marginal seas, and that a long-term exponential decrease in sea ice concentration exists and that Koopman Mode Decomposition allows a geographic view of where changes occur on annual and multi-year timescales
Summary
Sea ice cover in the Arctic and Antarctic is an important indicator of changes in the climate, with important environmental, economic and security consequences. Koopman Mode Decomposition (KMD) is applied to satellite data of sea ice concentration for the Northern and Southern hemispheres to gain insight into the temporal and spatial dynamics of the sea ice behavior and to predict future sea ice behavior. Compared to regression or trend based approaches, spatial mode based approaches are powerful tools for studying and predicting the geographic and temporal behavior of sea ice because they decompose the time dependent sea ice data into time varying spatial structures of physical significance. Such approaches have heretofore been restricted to methods that—explicitly or implicitly—assume statistical stationarity of the underlying process. The Koopman operator methods do not require a model—observables like sea ice thickness and concentration are sufficient to compute the eigenvalues and the associated modes
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