Observing Profiles of Derived Kinematic Field Quantities Using a Network of Profiling Sites Journal of Atmospheric and Oceanic Technology

Observations of thermodynamic and kinematic parameters associated with derivatives of the thermodynamics and wind fields, namely, advection, vorticity, divergence, and deformation, can be obtained by applying Green’s theorem to a network of observing sites. The five nodes that comprise the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) profiling network, spaced 50–80 km apart, are used to obtain measurements of these parameters over a finite region. To demonstrate the applicability of this technique at this location, it is first applied to gridded model output from the High-Resolution Rapid Refresh (HRRR) numerical weather prediction model, using profiles from the locations of ARM network sites, so that values calculated from this method can be directly compared to finite difference calculations. Good agreement is found between both approaches as well as between the model and values calculated from the observations. Uncertainties for the observations are obtained via a Monte Carlo process in which the profiles are randomly perturbed in accordance with their known error characteristics. The existing size of the ARM network is well suited to capturing these parameters, with strong correlations to model values and smaller uncertainties than a more closely spaced network, yet it is small enough that it avoids the tendency for advection to go to zero over a large area.

通过对观测站点网络应用格林定理（Green’s theorem），可获取与热力学和风场导数相关的热力学与运动学参数——即平流（advection）、涡度（vorticity）、散度（divergence）与变形场（deformation）——的观测值。本研究采用间距50–80 km的大气辐射测量（ARM）南大平原（SGP）廓线观测网的5个站点，在有限区域内获取上述参数的测量数据。为验证该技术在该区域的适用性，首先将其应用于高分辨率快速刷新（HRRR）数值天气预报模式的格点化模式输出数据，通过提取ARM观测网各站点位置处的气象廓线，使得本方法计算得到的参数值可直接与有限差分（finite difference）计算结果进行比对。结果表明，两种计算方法之间以及模式数据与观测计算值之间均具有良好的一致性。观测数据的不确定性通过蒙特卡洛（Monte Carlo）方法获取：依据已知的误差特征对气象廓线进行随机扰动，以此得到不确定性范围。当前ARM观测网的规模十分适配上述参数的捕获需求，其与模式数据的相关性较强，且相较于更密集的观测网具有更小的不确定性；同时其规模又足够小，可避免平流在大区域内趋近于零的现象。