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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. 

Abstract In the marine boundary layer, the exchange of momentum, heat, and moisture occurs between the atmosphere and ocean. Since it is too dangerous for a crewed aircraft to fly close to the ocean surface to directly obtain these measurements, a sUAS (small Uncrewed Aircraft System) is one of the only viable options. On 24 March 2023 a Black Swift Technologies S0 sUAS was deployed from the NOAA P‐3 on a calm clear day off the west coast of Florida. For 23 min at the end of the mission, the sUAS flew 8 straight line legs with an average length of 2.15 km, at roughly 10 m above the ocean surface, with wind speeds between 3.0 and 4.5 m s⁻¹. For the first time over the open ocean using a sUAS, the 4‐Hz wind and thermodynamic data was used to calculate surface momentum flux, sensible heat flux, and latent flux using both direct covariance methods and the bulk aerodynamic formulas. Since all the flux quantities can be found using both direct and indirect methods, we are able to calculate the exchange coefficients of momentum flux (C_D), latent heat flux (C_E), and sensible heat flux (C_H) with results that are generally in good agreement with previous studies over the same wind speed range. This study demonstrates the ability of sUAS to measure air‐sea interactions. Future intention is to use sUAS to obtain similar measurements in high wind events such as hurricanes which could better help understand hurricane intensification and improve model physics. 

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. 

Abstract The global positioning system dropwindsonde has provided thousands of high-resolution kinematic and thermodynamic soundings in and around tropical cyclones (TCs) since 1997. These data have revolutionized the understanding of TC structure, improved forecasts, and validated observations from remote sensing platforms. About 400 peer-reviewed studies on TCs using these data have been published to date. This paper reviews the history of dropwindsonde observations, changes to dropwindsonde technology since it was first used in TCs in 1982, and how the data have improved forecasting and changed our understanding of TCs. 

Abstract The distribution of turbulent kinetic energy (TKE) and its budget terms is estimated in simulated tropical cyclones (TCs) of various intensities. Each simulated TC is subject to storm motion, wind shear, and oceanic coupling. Different storm intensities are achieved through different ocean profiles in the model initialization. For each oceanic profile, the atmospheric simulations are performed with and without TKE advection. In all simulations, the TKE is maximized at low levels (i.e., below 1 km) and ∼0.5 km radially inward of the azimuthal‐mean radius of maximum wind speed at 1‐km height. As in a previous study, the axisymmetric TKE decreases with height in the eyewall, but more abruptly in simulations without TKE advection. The largest TKE budget terms are shear generation and dissipation, though variability in vertical turbulent transport and buoyancy production affect the change in the azimuthal‐mean TKE distribution. The general relationships between the TKE budget terms are consistent across different radii, regardless of storm intensity. In terms of the asymmetric distribution in the eyewall, TKE is maximized in the front‐left quadrant where the sea surface temperature (SST) is highest and is minimized in the rear‐right quadrant where the SST is the lowest. In the category‐5 simulation, the height of the TKE maximum varies significantly in the eyewall between quadrants and is between ∼400 m in the rear‐right quadrant and ∼1,000 m in the front‐left quadrant. When TKE advection is included in the simulations, the maximum eyewall TKE values are downwind compared to the simulations without TKE advection.