High-Resolution Estimation and Spatial Interpolation of Temperature Structure in the Atmospheric Boundary Layer Using a Small Unmanned Aircraft System
High-Resolution Estimation and Spatial Interpolation of Temperature Structure in the Atmospheric Boundary Layer Using a Small Unmanned Aircraft System
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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
DOI：
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发表时间：
2020
影响因子：
4.3
通讯作者：
J. Jacob
中科院分区：
文献类型：
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作者：
Benjamin L. Hemingway;Amy E. Frazier;B. Elbing;J. Jacob
了解小规模温度波动对大气中光传输的影响，对于校准遥感仪器以及了解大气边界层中湍流热传输是必要的。最近的发展，在小型无人驾驶飞机系统（sUAS）允许直接，空间原位估计温度在ABL在非常高的时间和空间分辨率。结构功能估计从使用安装在sUAS上的超声波风速计收集的温度的垂直剖面。使用专门为空间非平稳和空间相关的随机变量开发的地质统计学方法，我们估计温度结构从六个配置文件达到约500米的高度A平均函数被指定为占温度随高度的变化和结构函数估计的残差。一个2/3的标度指数拟合到与湍流的惯性子范围相称的所得曲线。由此产生的结构函数的残差是能够解决的惯性子范围内的大多数配置文件在一个范围内的分离距离。我们发现，空间非平稳随机变量的地质统计方法是非常适合在某些情况下描述的边界层中的温度的垂直结构。
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.
闪烁仪与无人机同时观测温度结构参数的差异
影响因子：
4.3
作者：
F. Beyrich;A.F. Moene;J. Bange;A. Platis;S. Martin;B. Maronga
通讯作者：
B. Maronga