Analysis of Iceberg Drift Trajectories Using the Multivariate Empirical Mode Decomposition
Journal article, Peer reviewed
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Original versionISOPE - International Offshore and Polar Engineering Conference. Proceedings. 2018, 2018-June 1653-1660.
In this study we show how to detect and extract the tidal and inertial oscillation from iceberg velocity data by using the multivariate empirical model decomposition. Due to the similar frequencies of both oscillations in regions subject to drifting icebergs, this is an extremely challenging filtering problem. The method is tested on two iceberg drift trajectories from the east coast of Canada, one at about 51◦N and one at about 76.5 ◦N. The two icebergs differ in latitudinal location, such that the inertial and tidal oscillations in the first data set have a slightly different frequency and in the other they are approximately the same. For the latter case a second filtering stage has to be included that uses tidal current information from a tidal current model. Finally we show how the multivariate empirical model decomposition can be used to analyze connections between current, wind and iceberg velocities. This information may help to improve either the ocean current and meteorological models or the iceberg drift model.