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Exploiting the structure of MWR-derived temperature profile for stable boundary-layer height estimation

机译:利用MWR得出的温度剖面结构稳定边界层高度估算

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A method for the estimation of Stable Boundary Layer Height (SBLH) using curvature of the potential temperature profiles retrieved by a Microwave Radiometer (MWR) is presented. The vertical resolution of the MWR-derived temperature profile decreases with the height. A spline interpolation is carried-out to obtain a uniformly discretized temperature profile. The curvature parameter is calculated from the first and second order derivatives of the interpolated potential temperature profile. The first minima of the curvature parameter signifies the point where the temperature profile starts changing from the stable to the residual conditions. The performance of the method is analyzed by comparing it against physically idealized models of the stable boundary-layer temperature profile available in the literature. There are five models which include stable-mixed, mixed-linear, linear, polynomial and exponential. For a given temperature profile these five models are fitted using the non-linear least-squares approach. The best fitting model is chosen as the one which fits with the minimum root-mean-square error. Comparison of the SBLH estimates from curvature-based method with the physically idealized models shows that the method works qualitatively and quantitatively well with lower variation. Potential application of this approach is the situation where given temperature profiles are significantly deviant from the idealized models. The method is applied to data from a Humidity-and-Temperature Profiler (HATPRO) MWR collected during the HD(CP)~2 Observational Prototype Experiment (HOPE) campaign at Jiilich, Germany. Radiosonde data, whenever available, is used as the ground-truth.
机译:提出了一种使用微波辐射计(MWR)检索到的潜在温度曲线的曲率估算稳定边界层高度(SBLH)的方法。 MWR衍生的温度曲线的垂直分辨率随高度降低。进行样条插值以获得均匀离散的温度曲线。曲率参数是根据插值势温度曲线的一阶和二阶导数计算的。曲率参数的第一个最小值表示温度曲线开始从稳定状态变为残差状态的点。通过将其与文献中可用的稳定边界层温度曲线的物理理想模型进行比较,分析了该方法的性能。有五种模型,包括稳定混合,线性混合,线性,多项式和指数。对于给定的温度曲线,使用非线性最小二乘法拟合这五个模型。选择最佳拟合模型作为最适合最小均方根误差的模型。将基于曲率的方法的SBLH估计值与物理理想化模型进行的比较表明,该方法在定性和定量方面都能很好地工作,且变化较小。这种方法的潜在应用是给定温度曲线明显偏离理想模型的情况。该方法适用于在德国Jiilich进行的HD(CP)〜2观测原型实验(HOPE)活动中收集的湿度和温度剖面仪(HATPRO)MWR的数据。只要有空,无线电探空仪数据就用作地面真相。

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