Large scale studies of underwater noise during rain are important for assessing the ocean environment and enabling remote sensing of rain rates over the open ocean. In this study, approximately 3.5 yrs of acoustical and meteorological data recorded at the northeast Pacific continental margin are evaluated. The acoustic data are recorded at a sampling rate of 64 kHz and depths of 81 and 581 m at the continental shelf and slope, respectively. Rain rates and wind speeds are provided by surface buoys located in the vicinity of each hydrophone. Average power spectra have been computed for different rain rates and wind speeds, and linear and nonlinear regression have been performed. The main findings are (1) the linear regression slopes highly depends on the frequency range, rain rate, wind speed, and measurement depth; (2) noise levels during rain between 200 Hz and 10 kHz significantly increase with increasing wind speed; and (3) the highest correlation between the spectral level and rain rate occurs at 13 kHz, thus, coinciding with the spectral peak due to small raindrops. The results of this study indicate that previously proposed algorithms for estimating rain rates from acoustic data are not universally applicable but rather have to be adapted for different locations.

中文翻译：

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表征东北太平洋大陆边缘降雨期间的水下噪声

下雨期间水下噪声的大规模研究对于评估海洋环境和实现公海降雨率的遥感非常重要。在这项研究中，评估了在东北太平洋大陆边缘记录的大约 3.5 年的声学和气象数据。声学数据分别以 64 kHz 的采样率和 81 米和 581 米的深度记录在大陆架和斜坡上。降雨率和风速由位于每个水听器附近的表面浮标提供。计算了不同降雨率和风速的平均功率谱，并进行了线性和非线性回归。主要发现是（1）线性回归斜率高度依赖于频率范围、降雨率、风速和测量深度；(2) 200 Hz 至 10 kHz 之间的雨时噪声级随着风速的增加而显着增加；(3) 频谱电平和降雨率之间的最高相关性出现在 13 kHz，因此，由于小雨滴与频谱峰值重合。这项研究的结果表明，先前提出的根据声学数据估计降雨率的算法并非普遍适用，而是必须针对不同的位置进行调整。