2019_programme: EVALUATION OF LONG-TERM TRENDS IN DEEP-OCEAN NOISE IN THE SOUTHERN OCEAN USING CTBTO HYDROACOUSTIC DATA

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  • Session: 08. Comprehensive nuclear test-ban treaty monitoring
    Organiser(s): Haralabus George, Zampolli Mario, Nielsen Peter
  • Lecture: EVALUATION OF LONG-TERM TRENDS IN DEEP-OCEAN NOISE IN THE SOUTHERN OCEAN USING CTBTO HYDROACOUSTIC DATA [invited]
    Paper ID: 917
    Author(s): Robinson Stephen, Harris Peter, Wang Lian , Livina Valerie, Cheong Sei-Him
    Presenter: Robinson Stephen
    Presentation type: oral
    Abstract: The variation in the ambient sound levels in the deep ocean has been the subject of a number of recent studies, with particular interest in the identification of long term trends. This paper describes a statistical method for performing long term trend analysis and uncertainty evaluation of the estimated trends from deep-ocean noise data. The measured data used here originate from the Southern Ocean and span up to a maximum of 15 years, from 2003 to 2018. The data were obtained from the hydro-acoustic monitoring stations of the CTBTO. 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 main features of the approach used include (a) using a model that includes terms to represent explicitly seasonal behaviour, (b) using daily aggregation intervals derived from 1 minute SPL averages, and (c) applying a non-parametric approach to validate the uncertainties of trend estimates that avoids the need to make an assumption about that distribution of those differences. 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. Statistically significant reductions in SPL are observed for all statistical percentiles for the different frequency bands as a result of negative trends in the examined time series. Strong seasonal variation is also observed, with a high degree of correlation with climatic factors such as sea surface temperature, Antarctic ice coverage and wind speed.
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  • Corresponding author: Mr Robinson Stephen
    Affiliation: NPL
    Country: United Kingdom
    e-mail:

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