Seasonal comparison of underwater ambient noise observed in the deep area of the South China Sea

Abstract

Seasonal statistics on underwater ambient noise in the deep area of the South China Sea (SCS) were analyzed on the basis of the experimental observation data. The depth dependence, correlation with environmental parameters, empirical expression and probability density function (PDF) of noise levels (NL) in summer were compared with those in winter. Average of NLs at receiver depths shallower than 800 m in summer are 6 dB greater than those in winter at <400 Hz, and the difference between them are less than 2 dB at >1 kHz. A parameterized fitting model was utilized to determine the noise spectrum levels at different wind speed (WS) conditions and was compared with the Wenz curves, which are consistent with the NLs in winter at >wind force 3. The correlation coefficient between NLs and WS or significant wave height (SWH) were described according to the reanalysis database of the National Center for Environmental Prediction (NCEP) and WAVEWATCH III. In addition, a four-parameter logarithm model was used to model the relationship between NLs and WS or SWH. Empirical expression between NLs and spectrum levels at 1 kHz was acquired in SCS. The Weibull and Burr distributions were applied for the evaluation of PDF of NLs in summer and winter. Low-frequency NLs were dominated by distant shipping noise and their PDF satisfied the Burr distribution. High-frequency NLs were dominated by breaking waves or wind agitation and their PDF satisfied the Burr and Gaussian distributions simultaneously. The experimental observation duration was closely related to the PDF of high-frequency NLs. Standard deviation, skewness and kurtosis of NLs were also analyzed. Finally, frequency correlation and spectra correlation matrices were utilized in analyzing the noise sources mechanism, and discussing the reason for the statistical difference of NLs in summer and winter. The NL statistical differences was due to oceanic environment variation and noise source mechanism simultaneously.