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Vertical Sampling Scales for Atmospheric Boundary Layer Measurements from Small Unmanned Aircraft Systems (sUAS)

机译:小型无人机系统(sUAS)大气边界层测量的垂直采样标尺

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The lowest portion of the Earth’s atmosphere, known as the atmospheric boundary layer (ABL), plays an important role in the formation of weather events. Simple meteorological measurements collected from within the ABL, such as temperature, pressure, humidity, and wind velocity, are key to understanding the exchange of energy within this region, but conventional surveillance techniques such as towers, radar, weather balloons, and satellites do not provide adequate spatial and/or temporal coverage for monitoring weather events. Small unmanned aircraft, or aerial, systems (sUAS) provide a versatile, dynamic platform for atmospheric sensing that can provide higher spatio-temporal sampling frequencies than available through most satellite sensing methods. They are also able to sense portions of the atmosphere that cannot be measured from ground-based radar, weather stations, or weather balloons and have the potential to fill gaps in atmospheric sampling. However, research on the vertical sampling scales for collecting atmospheric measurements from sUAS and the variabilities of these scales across atmospheric phenomena (e.g., temperature and humidity) is needed. The objective of this study is to use variogram analysis, a common geostatistical technique, to determine optimal spatial sampling scales for two atmospheric variables (temperature and relative humidity) captured from sUAS. Results show that vertical sampling scales of approximately 3 m for temperature and 1.5–2 m for relative humidity were sufficient to capture the spatial structure of these phenomena under the conditions tested. Future work is needed to model these scales across the entire ABL as well as under variable conditions.
机译:地球大气的最低部分,称为大气边界层(ABL),在天气事件的形成中起着重要作用。从ABL内部收集的简单气象数据(例如温度,压力,湿度和风速)是了解该区域内能量交换的关键,但是常规监视技术(例如塔,雷达,气象气球和卫星)却并非如此提供足够的空间和/或时间覆盖范围以监视天气事件。小型无人飞机或空中系统(sUAS)为大气感应提供了一个多功能的动态平台,与大多数卫星感应方法相比,该平台可以提供更高的时空采样频率。它们还能够感应无法通过地面雷达,气象站或气象气球测量到的大气部分,并有可能填补大气采样中的空白。但是,需要研究用于从sUAS收集大气测量值的垂直采样标度,以及这些标度在整个大气现象(例如温度和湿度)中的变化。本研究的目的是使用变异函数分析(一种通用的地统计技术)来确定从sUAS捕获的两个大气变量(温度和相对湿度)的最佳空间采样比例。结果表明,在测试条件下,垂直采样比例大约为3 m(温度)和1.5–2 m(相对湿度)足以捕获这些现象的空间结构。需要在整个ABL上以及在可变条件下对这些比例进行建模。

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