Abstract
This paper describes the results of applying s statistical method for long term and seasonal trend analysis and uncertainty evaluation of the data from deep-ocean noise data. The analysis method uses a flexible discrete model that incorporates terms that capture seasonal variations in the data together with a moving-average statistical model to describe the serial correlation of residual deviations, with uncertainties validated using bootstrap resampling.The measured data originate from a number of the hydro-acoustic monitoring stations of the CTBTO and span up to a maximum of 15 years. The analysis focuses on the data from Cape Leeuwin Southern Ocean), Wake Island (Pacific Ocean), Ascension Island (Atlantic Ocean), and Diego Garcia (Indian Ocean). The trend analysis is applied to time series representing monthly and daily aggregated statistical levels for five frequency bands to obtain estimates for the change in sound pressure level with associated coverage intervals. The features of the data are described, including the differences observed in the seasonal variation and the long-term trends, with the latter often exhibiting negative gradients. A tentative discussion is initiated of the potential causes of some of the observed trends and fluctuations.
Published Version
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