The Monin–Obukhov similarity theory-based wind speed and potential temperature profiles are inherently coupled to each other. We have developed hybrid approaches to disentangle them, and as a direct consequence, the estimation of Obukhov length (and associated turbulent fluxes) from either wind-speed or temperature measurements becomes an effortless task. Additionally, our approaches give rise to two easily measurable indices of atmospheric stability. We compare these approaches with the traditional gradient and profile methods that require both wind-speed and temperature profile data. Using Monte-Carlo-type numerical experiments we demonstrate that, if the input profiles are free of any random errors, the performance of the proposed hybrid approaches is almost equivalent to the profile method and better than the gradient method. However, the proposed hybrid approaches are less competitive in comparison to their traditional counterparts in the presence of random errors.

中文翻译：

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估计表面通量的混合剖面-梯度方法

基于 Monin-Obukhov 相似性理论的风速和潜在温度曲线本质上是相互耦合的。我们开发了混合方法来解开它们，因此直接结果是，根据风速或温度测量值估算 Obukhov 长度（以及相关的湍流通量）成为一项轻松的任务。此外，我们的方法产生了两个易于测量的大气稳定性指数。我们将这些方法与需要风速和温度剖面数据的传统梯度和剖面方法进行比较。我们使用蒙特卡罗类型的数值实验证明，如果输入轮廓没有任何随机误差，则所提出的混合方法的性能几乎等同于轮廓方法，并且优于梯度方法。然而，