An official website of the United States government
Abstract Lack of high‐resolution observations in the inner‐core of tropical cyclones remains a key issue when constructing an accurate initial state of the storm structure. The major implication of an improper initial state is the poor predictability of the future state of the storm. The size and associated hazard from strong winds at the inner‐core make it impossible to sample this region entirely. However, targeting regions of the inner‐core where forecasted atmospheric measurements have high uncertainty can significantly improve the accuracy of measurements for the initial state of the storm. This study provides a scheme for targeted high‐resolution observations for small Unmanned Aircraft Systems (sUAS) platforms (e.g., Coyote sUAS) to improve the estimates of the atmospheric measurement in the inner‐core structure. The benefit of observation is calculated based on the high‐fidelity state‐of‐the‐art hurricane ensemble data assimilation system. Potential locations with the mostinformativemeasurements are identified through exploration of various simulation‐based solutions depending on the state variables (e.g., pressure, temperature, wind speed, relative humidity) and a combined representation of those variables. A sampling‐based sUAS path planning algorithm considers energy usage when locating the regions of highly uncertain prediction of measurements, allowing sUAS to maximize the benefit of observation. Robustness analysis of our algorithm for multiple scenarios of sUAS drop and goal locations shows satisfactory performance against benchmark similar to current NOAA field campaign. With optimized sUAS observations, a data assimilation analysis shows significant improvements of up to 4% in the tropical cyclone structure estimates after resolving uncertainties at targeted locations.
more »
« less
Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science during the LAPSE-RATE Campaign
Small unmanned aircraft systems (sUAS) are rapidly transforming atmospheric research. With the advancement of the development and application of these systems, improving knowledge of best practices for accurate measurement is critical for achieving scientific goals. We present results from an intercomparison of atmospheric measurement data from the Lower Atmospheric Process Studies at Elevation—a Remotely piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. We evaluate a total of 38 individual sUAS with 23 unique sensor and platform configurations using a meteorological tower for reference measurements. We assess precision, bias, and time response of sUAS measurements of temperature, humidity, pressure, wind speed, and wind direction. Most sUAS measurements show broad agreement with the reference, particularly temperature and wind speed, with mean value differences of 1.6 ± 2.6 ∘ C and 0.22 ± 0.59 m/s for all sUAS, respectively. sUAS platform and sensor configurations were found to contribute significantly to measurement accuracy. Sensor configurations, which included proper aspiration and radiation shielding of sensors, were found to provide the most accurate thermodynamic measurements (temperature and relative humidity), whereas sonic anemometers on multirotor platforms provided the most accurate wind measurements (horizontal speed and direction). We contribute both a characterization and assessment of sUAS for measuring atmospheric parameters, and identify important challenges and opportunities for improving scientific measurements with sUAS.
more »
« less
- PAR ID:
- 10095260
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Date Published:
- Journal Name:
- Sensors
- Volume:
- 19
- Issue:
- 9
- ISSN:
- 1424-8220
- Page Range / eLocation ID:
- 2179
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract. The DataHawk2 (DH2) is a small, fixed-wing, uncrewed aircraft system, or UAS,developed at the University of Colorado (CU) primarily for taking detailedthermodynamic measurements of the atmospheric boundary layer. The DH2 weighs1.7 kg and has a wingspan of 1.3 m, with a flight endurance of approximately60 min, depending on configuration. In the DH2's most modern form, theaircraft carries a Vaisala RSS-421 sensor for pressure, temperature, andrelative humidity measurements, two CU-developed infrared temperaturesensors, and a CU-developed fine-wire array, in addition to sensors requiredto support autopilot function (pitot tube with pressure sensor, GPSreceiver, inertial measurement unit), from which wind speed and directioncan also be estimated. This paper presents a description of the DH2,including information on its design and development work, and puts the DH2 intocontext with respect to other contemporary UASs. Data from recent field work(MOSAiC, the Multidisciplinary drifting Observatory for the Study of ArcticClimate) is presented and compared with radiosondes deployed during thatcampaign to provide an overview of sensor and system performance. These datashow good agreement across pressure, temperature, and relative humidity aswell as across wind speed and direction. Additional examples of measurementsprovided by the DH2 are given from a variety of previous campaigns inlocations ranging from the continental United States to Japan and northernAlaska. Finally, a look toward future system improvements and upcomingresearch campaign participation is given.more » « less
-
Abstract Accurate prediction of tropical cyclone (TC) intensity remains a significant challenge partially due to physics deficiencies in forecast models. Improvement of boundary layer physics in the turbulent “gray zone” requires a better understanding of spatiotemporal variations of turbulent properties in low-level high-wind regions. To fill the gap, this study utilizes Anduril’s Altius 600, a small uncrewed aircraft system (sUAS), that collected data in the eye and eyewall regions of category 5 Hurricane Ian (2022) at altitudes below 1.4 km. The highest observed wind speed (WSPD) exceeded 105 m s−1at 650-m altitude. The Altius measured turbulent kinetic energy (TKE) and momentum fluxes that were in good agreement with previous crewed aircraft observations. This study explores the scale-awareness turbulent structure by quantifying turbulence-scale (100 m–2 km) and mesoscale (2–10 km) contributions to the total flux and TKE. The results show that mesoscale eddies dominate the horizontal wind variances compared to turbulent eddies. The horizontal wind variances contribute 70%–90% of the total TKE, while the vertical wind variances contribute 10%–30% of the total TKE. Spectral and wavelet analyses demonstrate eddy scales from a few hundred meters up to 10 km, with unique distributions depending on where observations were taken (e.g., eye vs eyewall). These findings underscore the complex and multiscale nature of TKE and momentum fluxes in intense hurricanes and highlight the critical need for advanced observational tools within the high-wind hurricane boundary layer environment. Significance StatementIt is crucial to improve the understanding of turbulent processes in the low-level high-wind regions of tropical cyclones (TCs) for accurate intensity forecasts. Traditional data collection methods involving crewed aircraft are too risky to access these critical regions. This study demonstrates the use of a small uncrewed aircraft system (sUAS) to collect data at low levels within an intense Hurricane Ian (2022). The wind speed measured by the sUAS exceeded 105 m s−1. Important turbulence parameters are estimated and presented as a function of wind speed, height, and radial locations. We found that mesoscale (2–10 km) eddies contributed to a significant portion of the total momentum transfer relative to turbulence-scale (100 m–2 km) eddies. This work demonstrates the usefulness of sUASs for improving the basic understanding of key physical processes in the high-wind hurricane boundary layer.more » « less
-
Abstract This study documents the capabilities of the StreamSonde, a lightweight (24 g) instrument manufactured by Skyfora that measures atmospheric temperature, pressure, humidity, and wind velocity. Unique features of the StreamSonde are its wind speed accuracy enabled by a dual-band Global Navigation Satellite System (GNSS) receiver, the ability to vary the terminal fall velocity, a theoretical maximum communication distance between the instrument and the deployment aircraft of 250 km, and the ability to simultaneously operate up to eight instruments (50 in the future). Skyfora’s GNSS receiver receives signals on two bands from U.S. global positioning system (GPS) (L1/L5), European Galileo (E1/E5a), and Chinese BeiDou (B1I/B2a) satellites to calculate the wind speed. The combination of dual GNSS and lower terminal fall velocity results in more accurate wind retrievals than from single-band GPS potentially allowing us calculate turbulence quantities, especially near the surface. StreamSondes were launched as dropsondes from the NOAA P-3 aircraft in both clear-air low-wind testing environments and in Hurricane Nigel (2023). The pressure, temperature, humidity (in clear air), and derived wind velocity collected by the StreamSonde compare favorably to the widely used RD41 dropsonde that was developed at the National Center for Atmospheric Research (NCAR) and is manufactured by Vaisala. At coreleased drops in Hurricane Nigel, mean absolute differences between RD41 dropsondes and StreamSondes are generally below 1°C for air temperature, 1.5 m s−1for wind speed, and 6° for wind direction. The benefits of using the StreamSonde instrument along with planned improvements to the platform are discussed. Significance StatementThis study presents proof of concept for operational deployment of a new, lightweight atmospheric profiler called the StreamSonde in a tropical cyclone. It uses advanced positioning technology to accurately measure three-dimensional wind velocity, has an adjustable terminal velocity, and can be deployed in “swarms” of sensors that have up to eight (50 in the future) instruments simultaneously active. The versatility of this emerging technology makes it useable for many meteorological applications.more » « less
-
Small uncrewed aerial systems (sUASs) can be used to quantify emissions of greenhouse and other gases, providing flexibility in quantifying these emissions from a multitude of sources, including oil and gas infrastructure, volcano plumes, wildfire emissions, and natural sources. However, sUAS-based emission estimates are sensitive to the accuracy of wind speed and direction measurements. In this study, we examined how filtering and correcting sUAS-based wind measurements affects data accuracy by comparing data from a miniature ultrasonic anemometer mounted on a sUAS in a joust configuration to highly accurate wind data taken from a nearby eddy covariance flux tower (aka the Tower). These corrections had a small effect on wind speed error, but reduced wind direction errors from 50° to >120° to 20–30°. A concurrent experiment examining the amount of error due to the sUAS and the Tower not being co-located showed that the impact of this separation was 0.16–0.21 ms−1, a small influence on wind speed errors. Lower wind speed errors were correlated with lower turbulence intensity and higher relative wind speeds. There were also some loose trends in diminished wind direction errors at higher relative wind speeds. Therefore, to improve the quality of sUAS-based wind measurements, our study suggested that flight planning consider optimizing conditions that can lower turbulence intensity and maximize relative wind speeds as well as include post-flight corrections.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/s19092179
