Exponentially decaying modes and long-term prediction of sea ice concentration using Koopman Mode Decomposition

TL;DR

This paper applies Koopman Mode Decomposition to satellite sea ice data, revealing exponentially decaying modes and enabling accurate long-term predictions of sea ice concentration up to four years ahead.

Contribution

It introduces the use of KMD for analyzing and predicting sea ice dynamics, highlighting exponentially decaying modes and improving long-term forecast accuracy.

Findings

Discovery of exponentially decaying spatial modes in both hemispheres

Precise geographic predictions of sea ice up to four years ahead

KMD provides insights beyond traditional linear methods

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) was 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 discover exponentially decaying spatial modes in both hemispheres and discuss their precise spatial extent, and also perform precise geographic predictions of sea ice concentration up to four years in the future. This data-driven decomposition technique gives insight in spatial and temporal dynamics not apparent in traditional linear approaches.