The prediction of wind-generated noise spectral levels at one frequency is typically based on a linear regression function, which is defined over the logarithm of the 10-m wind speed. However, despite its widespread success, the linear regression model does not pay attention to its prediction uncertainty because it makes point predictions. The main reasons for the uncertainty in the predicted value of the wind-generated noise level are that it cannot be uniquely determined by 10-m wind speed and its measurements may be corrupted by other sources of ambient noise. To quantify the uncertainty in predictions in this scenario, a Bayesian treatment of linear regression models and its associated predictive distribution are applied, making distribution predictions instead of point predictions. Once the predictive distribution for one frequency has been fixed, its linear variants are used to obtain predictive distributions for other frequencies. The data for the ocean ambient noise and 10-m wind speed are collected from two deep-water experiments, conducted in the South China Sea, and reanalysis data sets of the European Centre For Medium-Range Weather Forecasts, respectively. Empirical expressions for the predictive distribution of noise spectra (0.5–10 kHz) at wind speeds from 3.3 to 14 m/s have been developed. The results indicate decreasing uncertainties with an increasing wind speed.

中文翻译：

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从风速预测风生噪声谱的不确定性

一个频率下风生噪声频谱水平的预测通常基于线性回归函数，该函数定义为 10 米风速的对数。然而，尽管获得了广泛的成功，线性回归模型并没有关注其预测的不确定性，因为它是做点预测的。风生噪声水平预测值不确定的主要原因是它不能由 10 米风速唯一确定，并且其测量值可能会被其他环境噪声源破坏。为了量化这种情况下预测的不确定性，应用了线性回归模型的贝叶斯处理及其相关的预测分布，进行分布预测而不是点预测。一旦确定了一个频率的预测分布，就可以使用其线性变体来获得其他频率的预测分布。海洋环境噪声和 10 米风速的数据分别来自在南海进行的两次深水实验和欧洲中期天气预报中心的再分析数据集。已开发出风速为 3.3 至 14 m/s 时噪声谱（0.5-10 kHz）预测分布的经验表达式。结果表明不确定性随着风速的增加而减少。和欧洲中期天气预报中心的再分析数据集。已开发出风速为 3.3 至 14 m/s 时噪声谱（0.5-10 kHz）预测分布的经验表达式。结果表明不确定性随着风速的增加而减少。和欧洲中期天气预报中心的再分析数据集。已开发出风速为 3.3 至 14 m/s 时噪声谱（0.5-10 kHz）预测分布的经验表达式。结果表明不确定性随着风速的增加而减少。