Knowledge of the effects of small-scale fluctuations in temperature on light transmission in the atmosphere is necessary for the calibration of remote sensing instruments as well as for the understanding of turbulent heat transport in the atmospheric boundary layer. Recent developments in small unmanned aircraft systems (sUAS) have allowed for direct, spatial in situ estimation of temperature in the ABL at very high temporal and spatial resolutions. Structure functions are estimated from vertical profiles of temperature collected using an ultrasonic anemometer mounted on an sUAS. Using geostatistical methodologies specifically developed for spatially non-stationary and spatially dependent random variables, we estimate temperature structure from six profiles reaching roughly 500 m in altitude A mean function is specified to account for the variation in temperature with altitude and the structure function is estimated from the residuals. A 2/3 scaling exponent is fitted to the resulting curves commensurate with the inertial subrange of turbulence. The resulting structure functions of residuals are able to resolve the inertial subrange on most profiles at a range of separation distances. We find that geostatistical methods for spatially non-stationary random variables are well suited in certain cases to describing the vertical structure of temperature in the boundary layer.

中文翻译：

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使用小型无人机系统对大气边界层温度结构进行高分辨率估计和空间插值

了解小尺度温度波动对大气中光传输的影响对于校准遥感仪器以及理解大气边界层中的湍流热传输是必要的。小型无人机系统 (sUAS) 的最新发展允许以非常高的时间和空间分辨率对 ABL 中的温度进行直接、空间原位估计。结构函数是根据使用安装在 sUAS 上的超声波风速计收集的垂直温度分布来估计的。使用专门为空间非平稳和空间相关随机变量开发的地质统计学方法，我们从海拔约 500 m 的六个剖面估计温度结构 指定平均函数来解释温度随高度的变化，并根据残差估计结构函数。2/3 比例指数被拟合到与湍流惯性子范围相称的结果曲线上。所得的残差结构函数能够在一定距离范围内解析大多数剖面上的惯性子范围。我们发现空间非平稳随机变量的地统计方法在某些情况下非常适合描述边界层温度的垂直结构。2/3 比例指数被拟合到与湍流惯性子范围相称的结果曲线上。由此产生的残差结构函数能够在一定距离范围内解析大多数剖面上的惯性子范围。我们发现空间非平稳随机变量的地统计方法在某些情况下非常适合描述边界层温度的垂直结构。2/3 比例指数被拟合到与湍流惯性子范围相称的结果曲线上。所得的残差结构函数能够在一定距离范围内解析大多数剖面上的惯性子范围。我们发现空间非平稳随机变量的地统计方法在某些情况下非常适合描述边界层温度的垂直结构。