2019
DOI: 10.3390/s19122720
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Moving towards a Network of Autonomous UAS Atmospheric Profiling Stations for Observations in the Earth’s Lower Atmosphere: The 3D Mesonet Concept

Abstract: The deployment of small unmanned aircraft systems (UAS) to collect routine in situ vertical profiles of the thermodynamic and kinematic state of the atmosphere in conjunction with other weather observations could significantly improve weather forecasting skill and resolution. High-resolution vertical measurements of pressure, temperature, humidity, wind speed and wind direction are critical to the understanding of atmospheric boundary layer processes integral to air–surface (land, ocean and sea ice) exchanges … Show more

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Cited by 50 publications
(38 citation statements)
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References 45 publications
(61 reference statements)
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“…An important step toward harmonization of regulations in Europe was made by EASA (European Union Aviation Safety Agency) with the aim of a common ground across Europe. Besides, the UAV community is on a steep learning curve concerning the technology and the variety of applications (e.g., Chilson et al 2019). Another challenge for an UAV network is the ability for an automatic operation.…”
Section: Potential For a Global Observing Systemmentioning
confidence: 99%
See 1 more Smart Citation
“…An important step toward harmonization of regulations in Europe was made by EASA (European Union Aviation Safety Agency) with the aim of a common ground across Europe. Besides, the UAV community is on a steep learning curve concerning the technology and the variety of applications (e.g., Chilson et al 2019). Another challenge for an UAV network is the ability for an automatic operation.…”
Section: Potential For a Global Observing Systemmentioning
confidence: 99%
“…The spatial network density of a future observation system for an application in NWP is commonly estimated using Observing System Simulation Experiments (OSSE). An example for a UAV Meso-Network has recently been published by Chilson et al (2019). They assimilated PBL profiles of a hypothetical network of 110 UAV with a spacing of about 35 km.…”
Section: Potential For a Global Observing Systemmentioning
confidence: 99%
“…How the ABL evolves with space and time influences phenomena that impact public health and safety [1][2][3][4][5]. For example, the transport of air pollutants, pollen and spores [6][7][8][9], wind power supply to smart grid systems [10][11][12][13][14], forecast of local weather [2][3][4][5], air traffic control at airports [15][16][17][18], the spread and management of wildfires [19][20][21][22], and emissions mitigation of greenhouse gases [23][24][25][26] are all affected by the dynamic state of the ABL. Therefore, mitigation of adverse conditions affected by the dynamic state of the ABL requires accurate measurements of wind velocity over micro-and mesoscale domains [2,27,28].…”
Section: Introductionmentioning
confidence: 99%
“…Advancing capabilities for wind sensing with multirotor unmanned aircraft systems (UAS) can help fill the existing gap in ABL observations [3][4][5]. This is due to the effectiveness of multirotor UAS for probing the ABL over complex terrain or water where reliable operation of in situ or remote sensors is prohibitively difficult or difficult.…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, numerous atmospheric UAS data collection studies have been published, including air pollution (Šmídl & Hofman, ; Malaver Rojas et al, ), wild fire detection (Wegener et al, ), collection of meteorological measurements at sea (Machado, ), facilitation in climate control for crop monitoring (Roldán, Joossen, Sanz, del Cerro, & Barrientos, ), and many other applications (Villa, Gonzalez, Miljievic, Ristovski, & Morawska, ). There have also been a number of studies published on atmospheric boundary layer monitoring using fixed wing UASs (Elston et al, ) and multi‐rotor UASs (Chilson et al, ), all with sensors attached directly to the aircraft. The UAS configuration for this study allows for undisturbed air to be accessed by the sensor.…”
Section: Introductionmentioning
confidence: 99%