Energy dissipation rates are an important characteristic of turbulence; however, their magnitude in observational profiles can be incorrectly determined owing to their irregular appearance during vertical evolution. By analysing the data obtained from oceanic turbulence measurements, we demonstrate that the vertical sequences of energy dissipation rates exhibit a scaling property. Utilising this property, we propose a method to estimate the population mean for a profile. For scaling in the observed profiles, we demonstrate that our data exhibit a statistical property consistent with that exhibited by the universal multifractal model. Meanwhile, the population mean and its uncertainty can be estimated by inverting the probability distribution obtained by Monte Carlo simulations of a cascade model; to this end, observational constraints from several moments are imposed over each vertical sequence. This approach enables us to determine, to some extent, whether a profile shows an occasionally large mean or whether the population mean itself is large. Thus, it will contribute to the refinement of the regional estimation of the ocean energy budget, where only a small amount of turbulence observation data is available.

能量耗散率是湍流的重要特征。然而，由于它们在垂直演化过程中的不规则外观，它们在观测剖面中的大小可能无法正确确定。通过分析从海洋湍流测量获得的数据，我们证明了能量耗散率的垂直序列显示出缩放特性。利用此属性，我们提出了一种估计轮廓的总体平均值的方法。为了在观察到的轮廓中进行缩放，我们证明了我们的数据表现出与通用多重分形模型相同的统计特性。同时，通过对级联模型的蒙特卡洛模拟获得的概率分布求逆，可以估算出总体均值及其不确定性。为此，在每个垂直序列上施加了来自几个时刻的观测约束。这种方法使我们能够在某种程度上确定轮廓是否显示偶尔的均值或总体均值本身是否很大。因此，它将有助于完善海洋能收支的区域估计，因为那里只有少量的湍流观测数据。