Measurement of turbulent water vapor fluxes using a lightweight unmanned aerial vehicle system

Abstract. We present here the first application of a lightweight unmanned aerial vehicle (UAV) system designed to measure turbulent properties and vertical latent heat fluxes (λE). Such measurements are crucial to improve our understanding of linkages between surface moisture supply and boundary layer clouds and phenomena such as atmospheric rivers. The application of UAVs allows for measurements on spatial scales complimentary to satellite, aircraft, and tower derived fluxes. Key system components are: a turbulent gust probe; a fast response water vapor sensor; an inertial navigation system (INS) coupled to global positioning system (GPS); and a 100 Hz data logging system. We present measurements made in the continental boundary layer at the National Aeronautics and Space Administration (NASA) Dryden Research Flight Facility located in the Mojave Desert. Two flights consisting of several horizontal straight flux run legs up to ten kilometers in length and between 330 and 930 m above ground level (m a.g.l.) are compared to measurement from a surface tower. Surface measured λE ranged from −53 W m−2 to 41 W m−2, and the application of a Butterworth High Pass Filter (HPF) to the datasets improved agreement to within +/−12 W m−2 for 86% of flux runs, by removing improperly sampled low frequency flux contributions. This result, along with power and co-spectral comparisons and consideration of the differing spatial scales indicates the system is able to resolve vertical fluxes for the measurement conditions encountered. Challenges remain, and the outcome of these measurements will be used to inform future sampling strategies and further system development.

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Measurement of turbulent water vapor fluxes using a lightweight unmanned aerial vehicle system

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-4-5529-2011 ◽

2011 ◽

Vol 4 (4) ◽

pp. 5529-5568 ◽

Cited By ~ 2

Author(s):

R. M. Thomas ◽

K. Lehmann ◽

H. Nguyen ◽

D. L. Jackson ◽

D. Wolfe ◽

...

Keyword(s):

Boundary Layer ◽

Water Vapor ◽

Unmanned Aerial Vehicle ◽

System Development ◽

Spatial Scales ◽

Ground Level ◽

Heat Fluxes ◽

Data Logging ◽

Pass Filter ◽

Aerial Vehicle

Abstract. We present here the first application of a lightweight unmanned aerial vehicle (UAV) system designed to measure turbulent properties and vertical latent heat fluxes (λE). Such measurements are crucial to improve our understanding of linkages between surface moisture supply and boundary layer clouds and phenomena such as atmospheric rivers. The application of UAVs allows for measurements on spatial scales complimentary to satellite, aircraft, and tower derived fluxes. Key system components are: a turbulent gust probe; a fast response water vapor sensor; an inertial navigation system (INS) coupled to global positioning system (GPS); and a 100 Hz data logging system. We present measurements made in the continental boundary layer at the National Aeronautics and Space Administration (NASA) Dryden Research Flight Facility located in the Mojave Desert. Two flights consisting of several horizontal straight flux run legs up to ten kilometers in length and between 330 and 930 m above ground level (m a.g.l.) are compared to measurement from a surface tower. Surface measured λE ranged from −53 W m−2 to 41 W m−2, and the application of a Butterworth High Pass Filter (HPF) to the datasets improved agreement to within ± 12 W m−2 for 86 % of flux runs, by removing improperly sampled low frequency flux contributions. This result, along with power and co-spectral comparisons and consideration of the differing spatial scales indicates the system is able to resolve vertical fluxes for the measurement conditions encountered. Challenges remain, and the outcome of these measurements will be used to inform future sampling strategies and further system development.

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Subcloud and Cloud-Base Latent Heat Fluxes during Shallow Cumulus Convection

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-19-0122.1 ◽

2019 ◽

Vol 77 (3) ◽

pp. 1081-1100 ◽

Cited By ~ 1

Author(s):

Neil P. Lareau

Keyword(s):

Boundary Layer ◽

Water Vapor ◽

Latent Heat ◽

Surface Fluxes ◽

Heat Fluxes ◽

Cloud Base ◽

Cumulus Convection ◽

Mixing Ratio ◽

Convective Boundary ◽

Water Vapor Mixing Ratio

Abstract Doppler and Raman lidar observations of vertical velocity and water vapor mixing ratio are used to probe the physics and statistics of subcloud and cloud-base latent heat fluxes during cumulus convection at the ARM Southern Great Plains (SGP) site in Oklahoma, United States. The statistical results show that latent heat fluxes increase with height from the surface up to ~0.8Zi (where Zi is the convective boundary layer depth) and then decrease to ~0 at Zi. Peak fluxes aloft exceeding 500 W m−2 are associated with periods of increased cumulus cloud cover and stronger jumps in the mean humidity profile. These entrainment fluxes are much larger than the surface fluxes, indicating substantial drying over the 0–0.8Zi layer accompanied by moistening aloft as the CBL deepens over the diurnal cycle. We also show that the boundary layer humidity budget is approximately closed by computing the flux divergence across the 0–0.8Zi layer. Composite subcloud velocity and water vapor anomalies show that clouds are linked to coherent updraft and moisture plumes. The moisture anomaly is Gaussian, most pronounced above 0.8Zi and systematically wider than the velocity anomaly, which has a narrow central updraft flanked by downdrafts. This size and shape disparity results in downdrafts characterized by a high water vapor mixing ratio and thus a broad joint probability density function (JPDF) of velocity and mixing ratio in the upper CBL. We also show that cloud-base latent heat fluxes can be both positive and negative and that the instantaneous positive fluxes can be very large (~10 000 W m−2). However, since cloud fraction tends to be small, the net impact of these fluxes remains modest.

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Morphological Band Registration of Multispectral Cameras for Water Quality Analysis with Unmanned Aerial Vehicle

Remote Sensing ◽

10.3390/rs12122024 ◽

2020 ◽

Vol 12 (12) ◽

pp. 2024 ◽

Cited By ~ 1

Author(s):

Wonkook Kim ◽

Sunghun Jung ◽

Yongseon Moon ◽

Stephen C. Mangum

Keyword(s):

Unmanned Aerial Vehicle ◽

Red Tide ◽

Spatial Scales ◽

Quality Analysis ◽

Geometric Transformation ◽

Concentration Estimation ◽

Individual Bands ◽

Aerial Vehicle ◽

Short Time ◽

The Impact

Multispectral imagery contains abundant spectral information on terrestrial and oceanic targets, and retrieval of the geophysical variables of the targets is possible when the radiometric integrity of the data is secured. Multispectral cameras typically require the registration of individual band images because their lens locations for individual bands are often displaced from each other, thereby generating images of different viewing angles. Although this type of displacement can be corrected through a geometric transformation of the image coordinates, a mismatch or misregistration between the bands still remains, owing to the image acquisition timing that differs by bands. Even a short time difference is critical for the image quality of fast-moving targets, such as water surfaces, and this type of deformation cannot be compensated for with a geometric transformation between the bands. This study proposes a novel morphological band registration technique, based on the quantile matching method, for which the correspondence between the pixels of different bands is not sought by their geometric relationship, but by the radiometric distribution constructed in the vicinity of the pixel. In this study, a Micasense Rededge-M camera was operated on an unmanned aerial vehicle and multispectral images of coastal areas were acquired at various altitudes to examine the performance of the proposed method for different spatial scales. To assess the impact of the correction on a geophysical variable, the performance of the proposed method was evaluated for the chlorophyll-a concentration estimation. The results showed that the proposed method successfully removed the noisy spatial pattern caused by misregistration while maintaining the original spatial resolution for both homogeneous scenes and an episodic scene with a red tide outbreak.

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Development of an unmanned aerial vehicle to study atmospheric boundary-layer turbulent structure

Journal of Physics Conference Series ◽

10.1088/1742-6596/1925/1/012068 ◽

2021 ◽

Vol 1925 (1) ◽

pp. 012068

Author(s):

D G Chechin ◽

A Yu Artamonov ◽

N Ye Bodunkov ◽

M Yu Kalyagin ◽

A M Shevchenko ◽

...

Keyword(s):

Boundary Layer ◽

Atmospheric Boundary Layer ◽

Unmanned Aerial Vehicle ◽

Turbulent Structure ◽

Aerial Vehicle

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Analysis Of Aerial Photography With Drone Type Fixed Wing In Kotabaru, Lampung

Journal of Applied Geospatial Information ◽

10.30871/jagi.v2i1.738 ◽

2018 ◽

Vol 2 (1) ◽

pp. 102-107

Author(s):

Indreswari Suroso ◽

Erwhin Irmawan

Keyword(s):

Unmanned Aerial Vehicle ◽

Aerial Photography ◽

Ground Level ◽

Aerial Photographs ◽

Aerial Photos ◽

Above Ground Level ◽

The World ◽

Air Capture ◽

Aerial Vehicle ◽

Operational Time

In the world of photography is very closely related to the unmanned aerial vehicle called drones. Drones mounted camera so that the plane is pilot controlled from the mainland. Photography results were seen by the pilot after the drone aircraft landed. Drones are unmanned drones that are controlled remotely. Unmanned Aerial Vehicle (UAV), is a flying machine that operates with remote control by the pilot. Methode for this research are preparation assembly of drone, planning altitude flying, testing on ground, camera of calibration, air capture, result of aerial photos and analysis of result aerial photos. There are two types of drones, multicopter and fixed wing. Fixed wing has an airplane like shape with a wing system. Fixed wing use bettery 4000 mAh . Fixed wing drone in this research used mapping in This drone has a load ability of 1 kg and operational time is used approximately 30 minutes for an areas 20 to 50 hectares with a height of 100 m to 200 m and payload 1 kg above ground level. The aerial photographs in Kotabaru produce excellent aerial photographs that can help mapping the local government in the Kotabaru region.

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Lidar measurements characterizing the thermodynamic and dynamic structure of the boundary layer up to the turbulence scale

10.5194/egusphere-egu2020-7191 ◽

2020 ◽

Author(s):

Andreas Behrendt ◽

Diego Lange ◽

Florian Späth ◽

Shravan Kumar Muppa ◽

Simon Metzendorf ◽

...

Keyword(s):

Boundary Layer ◽

Water Vapor ◽

Climate Models ◽

Spatial Scales ◽

Pulse Repetition Frequency ◽

Pulse Repetition ◽

Raman Signal ◽

Single Shot ◽

Backscatter Signal ◽

Scanning Lidar

One weakness of today's weather and climate models is the inaccurate representation and parameterization of the boundary layer processes and land-atmosphere (L-A) feedback. In order to investigate these processes, scanning lidar systems allow the observation not only of wind with Doppler lidar but also of humidity and temperature. It is expected that advances in the understanding of LA feedback and boundary-layer exchange will significantly contribute to better simulations of clouds and precipitation on all temporal and spatial scales.In this contribution, we present recent thermodynamic measurements in the surface layer, atmospheric boundary layer and free troposphere with very high resolution achieved during several field campaigns like the Land-Atmosphere Feedback Experiment (LAFE) in 2017, ScaleX in 2019, EUREC4A in 2020, and at the Land-Atmosphere Feedback Observatory (LAFO) in 2020.University of Hohenheim (UHOH) operates besides two scanning Doppler lidars (HALO Photonics StreamlineXR), three lidars for thermodynamic profiling which have been developed within the last 15 years by the Institute of Physics and Meteorology itself. These are two scanning lidar systems which are semi-automated and a fully-automated vertical pointing lidar system.The water vapor differential absorption lidar (DIAL) of UHOH is a mobile system with a laser power of up to 10 W at 818 nm with a pulse repetition rate of 300 Hz. The receiver consists of an 80-cm telescope. The raw resolution of the atmospheric backscatter signals is 15 m and single shot. The resolution of the data product, the water vapor number density or absolute humidity, is typically 1 to 10 s and 40 to 200 m.The UHOH Rotational Raman Lidar measures temperature and water vapor mixing ratio. Also this system is mobile. So far, we used as transmitter a flash-lamp-pumped Nd:YAG laser with 12 W at 355 nm at 50 Hz. This laser is currently being exchanged against a similar laser with 20 W at the same pulse repetition frequency. The light backscattered from the atmosphere is received with a 40 cm telescope. Four channels detect the elastic backscatter signal, two rotational Raman signals, and the water vapor Raman signal. The signal intensities are detected in analog and photon counting mode with raw resolutions of 7.5 m and 10 s. Typical resolutions of the data products are 100 m and 10 s.A compact and automated further development of this system, ARTHUS for Atmospheric Raman Temperature and Humidity Sounder, uses already this powerful diode-pumped laser transmitter (20 W at 355 nm, 200 Hz).Measurement examples of all instruments will be presented and an outlook to future developments will be discussed.

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Greenhouse gas analyzer for measurements of carbon dioxide, methane, and water vapor aboard an unmanned aerial vehicle

Sensors and Actuators B Chemical ◽

10.1016/j.snb.2012.04.036 ◽

2012 ◽

Vol 169 ◽

pp. 128-135 ◽

Cited By ~ 55

Author(s):

Elena S.F. Berman ◽

Matthew Fladeland ◽

Jimmy Liem ◽

Richard Kolyer ◽

Manish Gupta

Keyword(s):

Carbon Dioxide ◽

Water Vapor ◽

Greenhouse Gas ◽

Unmanned Aerial Vehicle ◽

Gas Analyzer ◽

Aerial Vehicle

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Development of an Unmanned Aerial Vehicle for the Measurement of Turbulence in the Atmospheric Boundary Layer

Atmosphere ◽

10.3390/atmos8100195 ◽

2017 ◽

Vol 8 (10) ◽

pp. 195 ◽

Cited By ~ 31

Author(s):

Brandon Witte ◽

Robert Singler ◽

Sean Bailey

Keyword(s):

Boundary Layer ◽

Wind Speed ◽

Atmospheric Boundary Layer ◽

Unmanned Aerial Vehicle ◽

Sensor Data ◽

Velocity Sensor ◽

Aerial Vehicle ◽

Probe Velocity ◽

Convective State ◽

Using Data

This paper describes the components and usage of an unmanned aerial vehicle developed for measuring turbulence in the atmospheric boundary layer. A method of computing the time-dependent wind speed from a moving velocity sensor data is provided. The physical system built to implement this method using a five-hole probe velocity sensor is described along with the approach used to combine data from the different on-board sensors to allow for extraction of the wind speed as a function of time and position. The approach is demonstrated using data from three flights of two unmanned aerial vehicles (UAVs) measuring the lower atmospheric boundary layer during transition from a stable to convective state. Several quantities are presented and show the potential for extracting a range of atmospheric boundary layer statistics.

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