Banesh, DivyaWendelberger, JoannePetersen, MarkAhrens, JamesHamann, BerndKarsten Rink and Dirk Zeckzer and Roxana Bujack and Stefan Jänicke2018-06-022018-06-022018978-3-03868-063-5https://doi.org/10.2312/envirvis.20181134https://diglib.eg.org:443/handle/10.2312/envirvis20181134The detection and analysis of mesoscale ocean eddies is a complex task, made more difficult when simulated or observational ocean data are massive. We present the statistical approach of change point detection as a means to help scientists efficiently extract relevant scientific information. We demonstrate the value of change point detection for the characterization of eddy behavior in simulated ocean data. Our results show that change point detection helps with the identification of significant parameter values used in an algorithm or determination of time points that correspond to eddy activity of interest.Mathematics of computingTime series analysisExploratory data analysisRegression analysisComputing methodologiesObject detectionImage processing10.2312/envirvis.2018113427-33