Wind Field Research Articles

Reinforcement learning based multi-perspective motion planning of manned electric vertical take-off and landing vehicle in urban environment with wind fields

Reinforcement learning based multi-perspective motion planning of manned electric vertical take-off and landing vehicle in urban environment with wind fields

Low-Level Mesocyclone Evolution of a Cyclic Tornadic Supercell Observed during TORUS on 17 May 2019

Abstract This case study analyzes the 17 May 2019 cyclic, tornadic supercell from southwest Nebraska observed by the Targeted Observation by Radars and UAS of Supercells (TORUS) field experiment. Specifically, 12 multi-Doppler wind syntheses are generated over a 96-min period from 2301 UTC 17 May to 0037 UTC 18 May using two P-3 airborne radars and the ground-based NOXP research radar. Synthesized winds and reflectivity are assimilated into a diabatic Lagrangian analysis for the retrieval of thermodynamic data. The 4D wind fields are found to correlate well with observed tornadic and nontornadic periods, and several storm-scale features related to low-level mesocyclone (LLM) and near-ground rotation processes are documented. This includes vortex line arches that are a defining feature during the first EF2 tornado, followed by an occlusion process and reorganization period. During the most active tornadic period, backward trajectories reveal both inflow parcels and forward-flank parcels participate in the core of the 0–1-km rotation. While tilting of streamwise vorticity into vertical vorticity and subsequent powerful vertical stretching occurs for both inflow and forward-flank parcels, the solenoidal generation of streamwise vorticity is dominant with the latter. This resembles streamwise vorticity currents found within numerical simulations. Last, an intense left-flank convergence boundary develops coincident with the intensification of storm-relative inflow winds, with its formation and dissipation correlated with the final tornado. The 96-min analysis period with 4D kinematic and thermodynamic data makes this study one of the most detailed supercell case studies presented in the literature. Significance Statement A detailed analysis of a supercell that produced nine tornadoes within a 96-min period is presented. The supercell was observed by five radars, which are used to obtain information about the 3D wind, temperature, and moisture fields. Although computer simulations can provide detailed looks into supercell processes, collecting and analyzing observed supercell data of this quality is challenging and rare. We identify features within the supercell that are correlated with periods of strong and weak tornado production. Additionally, we identify the source region of air that is associated with low-level rotation in the supercell and comment on the importance of temperature gradients observed within the supercell, comparing these results to what has been found in simulations.

Identifying the effect of architecture morphology on wind fields and PM2.5 dispersion at the urban block scale via a combined scheme

Identifying the effect of architecture morphology on wind fields and PM2.5 dispersion at the urban block scale via a combined scheme

Canonical polyadic decomposition enhanced stochastic wave-based spectral representation method for the simulation of nonstationary turbulent wind fields

Canonical polyadic decomposition enhanced stochastic wave-based spectral representation method for the simulation of nonstationary turbulent wind fields

Aerodynamic characteristics of the train traversing the thunderstorm downburst wind field

Aerodynamic characteristics of the train traversing the thunderstorm downburst wind field

Climatic features of wind field and their impact on local air quality in Taiyuan Basin.

Climatic features of wind field and their impact on local air quality in Taiyuan Basin.

Observational force analysis and anisotropic characteristics of tropical cyclone sea surface wind fields over Chinese offshore areas

Observational force analysis and anisotropic characteristics of tropical cyclone sea surface wind fields over Chinese offshore areas

Final design of outer poloidal field coils for COMPASS Upgrade

Final design of outer poloidal field coils for COMPASS Upgrade

Transient electrical behavior of DEMO toroidal field coils system in normal operation and fault conditions

Transient electrical behavior of DEMO toroidal field coils system in normal operation and fault conditions

ASSESSING THE SPATIAL-TEMPORAL WAVE ENERGY CHARACTERISTICS ALONG THE SOUTHEAST COAST OF CHINA IN A WAVE SIMULATION STUDY

The objective of this study is to evaluate exploitable wave power in the South China sea, especially along the southeast coast, from a 10-year hindcast simulation of ocean waves. Based on wind speed and wind direction data from meteorological stations in the South China Sea, an evaluation of three reanalysis data products, namely ERA5, CFSv2, and CCMP, was conducted using correlation coefficients, bias, and other performance indexes. Overall, the wind field of the ERA5 dataset performed the best.

Improved nondestructive sensor for field-friendly measurement of total flux leakage to detect corrosion damage to steel wires in concrete structures

ABSTRACT This study introduces the M8 sensor, an improved non-destructive sensor designed to detect cross-sectional losses of steel wires. The ‘M’ in M8 denotes ‘magnet’. Developed as an alternative to the previously used solenoid sensor – which required labour-intensive field winding on tendons or cables – the M8 sensor offers enhanced workability and testing reproducibility. Operating on the same principle as the solenoid sensor, the M8 sensor uses primary coils consisting of eight bar-shaped electromagnets to generate magnetic flux within the steel wires, while a secondary coil measures the total magnetic flux. Variations in the total magnetic flux along the wire length enable the identification of any cross-sectional loss. Numerical simulations were performed to investigate the magnetic flux density distributions in the M8 and solenoid sensors. The results indicated equivalent distributions in both sensors. This implies that the M8 sensor can operate on the same principle. Experimental demonstrations of the M8 and solenoid sensors indicated that the M8 sensor successfully detected a 6.7% cross-sectional loss in the tendon. This confirmed the comparable performance of the M8 and solenoid sensors.

Comparative Analysis of Hydrodynamic Characteristics off Shandong Under the Influence of Two Types of Storm Surges

As China’s largest peninsula, the Shandong Peninsula faces recurrent threats from both tropical and extratropical cyclone-induced storm surges. Understanding the distinct mechanisms governing these surge types is critical for developing targeted coastal hazard mitigation strategies. This investigation employs the FVCOM-SWAVE coupled wave–current model to conduct numerical simulations and comparative analyses of two 2022 surge events, Typhoon Muifa (tropical) and the “221003” extratropical surge. The results demonstrate that hydrodynamic responses exhibit strong dependence on surge-generating meteorological regimes. Tropical surge dynamics correlate closely with typhoon track geometry, intensity gradients, and asymmetric wind field structures, manifesting rightward-biased energy intensification relative to storm motion. Conversely, extratropical surge variations align with evolving wind-pressure configurations during cold air advection, driven by synoptic-scale atmospheric reorganization. The hydrodynamic environmental response in the sea areas surrounding Jiaodong and Laizhou Bay is particularly pronounced, influenced by the intensity of wind stress on the sea surface, as well as the bathymetry and coastal geometry.

Analysis of non-stationary characteristics of measured wind speed in mountains based on TVF-EMD

Abstract The time-varying average wind speed is extracted by using time-varying filtering EMD (TVF-EMD), and the non-stationary characteristics of the measured wind speed in mountainous areas are analyzed. A non-stationary wind speed model is established, and compared with the traditional stationary model. The results show that TVF-EMD is more accurate and reliable in extracting time-varying average wind speed than traditional wavelet transform. The stationary model overestimates the turbulent characteristics of wind, and the turbulence intensity and gust factor are higher than those of the non-stationary model. In the non-stationary model, the turbulent energy of fluctuating wind is reduced because the time-varying trend term is eliminated. In the whole frequency band, the power spectral density is lower than that of the steady-state model. Kaimal PSD with along-wind and Von Karman PSD with cross-wind are suitable for non-stationary wind fields in mountainous areas.

Locked Rotor Fault Analysis in Dual Rotor Wound Field Flux Switching Generator for Counter-Rotating Wind Turbine Application

In this paper, the performance of the Independent Dual Rotor Wound Field Flux Switching Generator (IDRWFFSG) under locked rotor fault scenarios and counter-rotating operational direction for fault withstand capability is investigated. The IDRWFFSG and the locked rotor fault scenarios are defined, and the magnetic path formation is explained. An integrated mathematical and electromagnetic modelling of the generator characteristics performance comprising torque quality, output power, efficiency and power factor are undertaken, based on the finite element method (FEM) under fault conditions. The electromagnetic characteristics are investigated independently for the inner and outer rotors under locked conditions while the counterpart rotor is rotated in both clockwise (CW) and counterclockwise (CCW) directions. The analysis confirms that CCW offers a comparatively better response than CW, with excellent locked rotor fault withstand capability. In the case of CCW operation, the average torque, output power, efficiency, and power factor are improved. Based on the results, it is determined that the rotational direction of the rotor is selected depending on the prerequisite demand of high efficiency, high power factor, and high output power when one of the rotors goes under a locked condition. Finally, a test prototype is developed to validate the predicted electromagnetic characteristics, of which the measured results confirm the effectiveness of the IDRWFFSG fault withstand capability study.

A comparative study on the speed regulation methods of coaxial and axial magnetic gear modulated by magnetic field

Magnetic gear transmission has the characteristics of no direct contact, low speed and high torque, and is widely used in wind, Marine, automotive and aerospace fields. In order to perform a comparative study of the speed regulation methods of coaxial magnetic gears and axial magnetic gears, this paper establishes these two magnetic gears as having approximately the same dimensions and the same transmission ratio. The three-dimensional transient field analysis was performed using COMSOL Multiphysics. The results show that the flux density and transfer torque of the axial magnetic gear are greater, and the coaxial magnetic gear has greater carrying power. The torque fluctuation during operation of the axial magnetic gear is greater. The axial magnetic gear has higher efficiency under the structure and speed established in this paper. The two speed control methods have their own advantages and disadvantages and need to be selected according to the requirements.

Toward understanding the differences between mesoscale and large-eddy simulations of tropical cyclones

Abstract In this work, we investigate the ability of mesoscale and large-eddy simulation (LES) model configurations to predict the mean wind speed profile within the boundary layer of tropical cyclones (TCs). To this end, we perform idealized simulations of five hypothetical intense storms ranging from Category 1 to 5 on the Saffir–Simpson scale, and extract time-averaged quantities near the eyewall region. We compare the model-generated data against mean wind speed profiles compiled from dropsondes launched from reconnaissance aircraft operating in the North Atlantic basin. Our analysis shows that mesoscale- and LES-generated mean wind fields display important differences in the boundary layer, including the magnitude of shear as well as the height where their low-level wind speed maxima are located. In addition, a comparison between the two model configurations with the dropsonde data shows that both modeling approaches are unable to capture the typical structure of mean winds in the lower part of the TC boundary layer (10m to 500 m), calling into question the use of simulations of near-axisymmetric storms for investigating the wind structure of past events. To better understand these differences, we conduct a momentum-budget analysis and show that modeled turbulent fluxes are underestimated in the mesoscale boundary-layer parameterization compared to the LES model. Based on the analysis of the horizontal turbulent fluxes and their potential impact on mean flow quantities, a TC-specific boundary-layer parameterization may be needed.

Ocean Surface Wind Field Retrieval Simultaneously Using SAR Backscatter and Doppler Shift Measurements

Sea surface wind retrieval methods using synthetic aperture radar (SAR) are generally classified into two categories: the direct inversion method and the variational analysis method (VAM). Traditional VAM retrieves wind fields by integrating background wind information with SAR normalized radar cross-section (NRCS). Recent studies have shown that incorporating SAR Doppler centroid anomaly (DCA) as an additional observation for variational analysis can improve the accuracy of wind speed and direction retrieval. However, this method has yet to be systematically evaluated, particularly with respect to its applicability to Sentinel-1 SAR data. This study presents a comprehensive assessment based on 1803 Sentinel-1 vertical–vertical (VV) polarization level-2 Ocean (OCN) product scenes collocated with in situ measurements from the National Data Buoy Center (NDBC), yielding a total of 2826 matched data pairs. We systematically evaluate the performance of three distinct VAM configurations: VAM1 (JNRCS), utilizing only NRCS; VAM2 (JDCA), employing solely DCA; and VAM3 (JNRCS+DCA), which combines both NRCS and DCA. The results demonstrate that VAM3 (JNRCS+DCA) achieves the best performance, with the lowest root mean square error (RMSE) of 1.42 m/s for wind speed and 26.00° for wind direction across wind speeds up to 23.2 m/s, outperforming both VAM1 (JNRCS) and VAM2 (JDCA). Furthermore, the accuracy of background wind speed is identified as a critical factor affecting VAM performance. After correcting the background wind speed, the RMSE and bias of the retrieved wind speed decreased significantly across all VAMs. The most notable bias reduction was observed at wind speeds exceeding 10 m/s. These findings provide essential theoretical support for the operational application of Sentinel-1 OCN products in sea surface wind retrieval.

Compound Dry‐Dusty Air Intrusions During the Genesis of Tropical Storm Kate (2021): Observations From the CPEX‐AW Field Campaign and Coupled Modeling

AbstractThe influence of the Saharan air layer (SAL) on developing tropical cyclones (TCs) involves complex interactions between dynamic, thermodynamic, and cloud microphysical processes and thus remains highly challenging to forecast. This study leverages a unique set of in situ aircraft observations from the NASA Convective Processes – Aerosols and Winds (CPEX‐AW) field campaign and a high‐resolution, fully coupled atmosphere‐wave‐ocean model simulation to examine the complexity of compound dry‐dusty air intrusions during the genesis of Tropical Storm (TS) Kate (2021). The suite of CPEX‐AW observations, featuring a multifrequency lidar, a precipitation radar and GPS dropsondes, provides a unique perspective of the interplay between multiple air masses in the environment surrounding TS Kate. We complement CPEX‐AW observations with atmospheric tracers from the high‐resolution coupled‐model simulation to better understand the origins and transport of these air masses and their impacts on TS Kate. Two distinct intrusions are observed: one within the precursor easterly wave and one during the Tropical Depression (TD) stage. Within the precursor wave, low‐ marine air associated with subsidence within the subtropical high undercuts the SAL as both air masses are entrained along two pathways: (a) lateral entrainment following the wave‐relative inflow and (b) vertical entrainment downward into the boundary layer and subsequently upward within deep convection. Later, mid‐tropospheric dry air from the subtropical high merges with the remnant SAL, resulting in strong radial ventilation of the TD above the boundary layer likely limiting any further intensification.

On the Importance of Learning Non‐Local Dynamics for Stable Data‐Driven Climate Modeling: A 1D Gravity Wave‐QBO Testbed

AbstractModel instability remains a core challenge for data‐driven parameterizations, especially those developed with supervised algorithms, and rigorous methods to address it are lacking. Here, by integrating machine learning (ML) theory with climate physics, we demonstrate the importance of learning spatially non‐local dynamics using a 1D quasi‐biennial oscillation model with parameterized gravity waves (GW) as a testbed. While common offline metrics fail to identify shortcomings in learning non‐local dynamics, we show that the receptive field (RF) can identify instability a‐priori. We find that neural network‐based parameterizations, though predicting GW forcings from wind profiles with 99% accuracy, lead to unstable simulations when RFs are too small to capture non‐local dynamics. Additionally, we demonstrate that learning non‐local dynamics is crucial for the stability of a data‐driven spatiotemporal emulator of the zonal wind field. This work underscores the need to integrate ML theory with physics in designing data‐driven algorithms for climate modeling.

Intensified Tropical Cyclones in Global Climate Simulations Employing a High-Wind Drag Relation over Sea Surface

Abstract Accurate parameterization of momentum fluxes at high winds across the air–sea interface is crucial for realistically simulating the surface wind fields of tropical cyclones (TCs). Climate models often struggle to reproduce observed TC intensities, particularly surface wind speeds. This study evaluates the performance of a revised surface drag scheme with a capping drag coefficient at high wind speeds in global climate models (GCMs). Our results indicate that the revised surface drag scheme significantly improves the representation of TCs in a statistical sense: (i) Not only the mature intensity but also the maximum 10-m wind speeds throughout the TC life cycle are largely enhanced; (ii) biases in the pressure–wind relationship are notably alleviated, exhibiting reasonable agreement with observations; and (iii) other TC statistical features, such as TC number, central sea level pressure, individual lifetime, and intensification rate, show relatively minor sensitivity to the surface drag schemes. The main reason for the superiority of the revised high-wind drag relation is that the lower drag coefficient in high-wind conditions significantly increases the maximum potential intensity (MPI), indicating a higher theoretical limit for TC intensities. These findings are consistent across different model versions and resolutions, highlighting the robustness of the high-wind surface drag parameterization in controlling the simulated surface wind speeds of TCs in GCMs. Significance Statement Tropical cyclones (TCs) stand out as one of the highly destructive weather phenomena, exerting a significant impact on life and property. Accurate simulations and forecasts of TC activity on a global scale are imperative to mitigate potential losses. However, realistically representing TC intensity in global climate models remains a challenge. This study addresses this issue by employing a revised high-wind surface drag scheme to assess the impact of air–sea momentum fluxes on simulated TC activity. Notably, the revised surface drag scheme yields a significant improvement by enhancing the maximum surface wind speed near the TC centers.