Drone-Based Vertical Atmospheric Temperature Profiling in Urban Environments

IF 4.4 2区 地球科学 Q1 REMOTE SENSING
Drones Pub Date : 2023-10-24 DOI:10.3390/drones7110645
Jokūbas Laukys, Bernardas Maršalka, Ignas Daugėla, Gintautas Stankūnavičius
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引用次数: 0

Abstract

The accurate and detailed measurement of the vertical temperature, humidity, pressure, and wind profiles of the atmosphere is pivotal for high-resolution numerical weather prediction, the determination of atmospheric stability, as well as investigation of small-scale phenomena such as urban heat islands. Traditional approaches, such as weather balloons, have been indispensable but are constrained by cost, environmental impact, and data sparsity. In this article, we investigate uncrewed aerial systems (UASs) as an innovative platform for in situ atmospheric probing. By comparing data from a drone-mounted semiconductor temperature sensor (TMP117) with traditional radiosonde measurements, we spotlight the UAS-collected atmospheric data’s accuracy and such system suitability for atmospheric surface layer measurement. Our research encountered challenges linked with the inherent delays in achieving ambient temperature readings. However, by applying specific data processing techniques, including smoothing methodologies like the Savitzky–Golay filter, iterative smoothing, time shift, and Newton’s law of cooling, we have improved the data accuracy and consistency. In this article, 28 flights were examined and certain patterns between different methodologies and sensors were observed. Temperature differentials were assessed over a range of 100 m. The article highlights a notable accuracy achievement of 0.16 ± 0.014 °C with 95% confidence when applying Newton’s law of cooling in comparison to a radiosonde RS41’s data. Our findings demonstrate the potential of UASs in capturing accurate high-resolution vertical temperature profiles. This work posits that UASs, with further refinements, could revolutionize atmospheric data collection.
基于无人机的城市环境垂直大气温度廓形
准确而详细地测量大气的垂直温度、湿度、压力和风廓线对于高分辨率数值天气预报、确定大气稳定性以及调查城市热岛等小尺度现象至关重要。传统的方法,如气象气球,是必不可少的,但受到成本、环境影响和数据稀疏性的限制。在本文中,我们研究了无人空中系统(UASs)作为一种创新的原位大气探测平台。通过将无人机搭载的半导体温度传感器(TMP117)数据与传统无线电探空仪测量数据进行比较,我们强调了无人机收集的大气数据的准确性以及该系统对大气表层测量的适用性。我们的研究遇到了与获得环境温度读数的固有延迟相关的挑战。然而,通过应用特定的数据处理技术,包括平滑方法,如Savitzky-Golay滤波器、迭代平滑、时移和牛顿冷却定律,我们提高了数据的准确性和一致性。在本文中,对28次飞行进行了检查,并观察到不同方法和传感器之间的某些模式。在100米范围内评估了温差。本文强调了与无线电探空仪RS41的数据相比,应用牛顿冷却定律时,具有95%置信度的0.16±0.014°C的显着精度成就。我们的发现证明了UASs在捕获精确的高分辨率垂直温度曲线方面的潜力。这项工作假设,经过进一步的改进,UASs可以彻底改变大气数据收集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Drones
Drones Engineering-Aerospace Engineering
CiteScore
5.60
自引率
18.80%
发文量
331
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