Inderscience Publishers

Handling of a large dataset: application of Time Series Analysis to oceanographic studies

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This paper describes the application of the specific Time Series Analysis techniques (TSA), Autocorrelation analysis (AC), Crosscorrelation analysis (CC) and Power Spectral Density (PSD) to elaborate a large set of oceanographic data, such as marine pressure, flow and current. The data were collected by ad hoc oceanographic instrumentations in two different sites of the Italian seas as digitised data. The application of AC, CC and PSD performed by means of Matlab software programs, allowed to verify the real-time trend and cyclical events present in the data with higher accuracy than the accuracy obtained by conventional data-time plots. So, this paper underlines and encourages the correct use and application of TSA techniques to analyse a large dataset like oceanographic monitoring data. The lists of Matlab routines used in this paper are also given.

Keywords: high dimensional data, Matlab, oceanography, time series analysis, TSA, large datasets, oceanographic data, marine pressure, flow, current, Italy, oceanographic monitoring

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