Radial Wind Speed Research Articles

Dynamic Response Analysis of Moving Trains Passing Through the Stationary Thunderstorm Downburst Wind

The safety of the high-speed train traveling through the stationary thunderstorm downburst wind was studied. First, a thunderstorm wind test device was used to simulate the stationary thunderstorm downburst wind. Based on the rigid model pressure measurement tests, the aerodynamic forces of the train traveling along different paths through the stationary thunderstorm downburst wind were measured. The influence of the radial distance of the crossing path on the aerodynamic force coefficients of the train was investigated. On this basis, an unsteady aerodynamic model of the high-speed train crossing through the stationary thunderstorm downburst wind was established, and dynamic response analysis was carried out using the SIMPACK multibody dynamics simulation software to explore further the safety of the high-speed train crossing through the stationary thunderstorm downburst wind. The research showed that the stationary thunderstorm downburst wind field has significant spatial variation characteristics compared with the atmospheric boundary layer wind field. When the train passes through the thunderstorm downburst wind, the radial wind speed and wind yaw angle experienced by the train constantly change, and the change curve shows a symmetrical distribution. The aerodynamic force of the train will undergo sudden loading and unloading processes, and the lateral force coefficient of the train on different paths shows a “pulse-type” variation. Moreover, the lateral force coefficient increases with the increase of wind yaw angle. Under the influence of the thunderstorm downburst wind, the variation trend of the aerodynamic force coefficients of the train is consistent with that under crosswind. However, there are significant differences in the numerical values. Therefore, it is impossible to simply use the formula for calculating the aerodynamic force coefficients of the train under crosswinds to predict the aerodynamic force coefficients of the train under the thunderstorm downburst wind. While passing through the thunderstorm downburst wind, the overturning coefficient index plays a decisive role in the safety of train operations. Train rollover is the main form of train safety accidents, while derailment accidents are not easy. The numerical results obtained in this study are significant for evaluating the operational safety while moving trains traversing the stationary thunderstorm downburst wind.

Near-wake measurements and simulations of a floating wind turbine using a four-beam nacelle-based lidar

Recent advances in lidar technology have expanded the possibilities for measuring full-scale wind turbine wakes within the atmospheric boundary layer. This study utilizes a four-beam pulsed lidar installed on the nacelle of a floating turbine to measure the near-wake. The wake measurement campaign was conducted on the Floatgen, with lidar measurements reaching up to 2.5 times the rotor diameter distance. These measurements are presented as 10-minute average radial wind speeds. The focus of this study is on the below rated wind speed of 7 m/s. Free flow conditions were assumed at the farthest measurement points, which are located ±0.9 times the rotor diameter from to the rotor center. The sensitivity of lidar measurements to turbulence intensity, vertical wind shear, and significant wave height was investigated. The environmental conditions were categorized into five cases, considering turbulence, vertical shear, and yaw misalignment as well as waves. Two simulation models with different fidelity levels are used to simulate these cases, and the beam-wise radial wind speed predictions are compared with the measurements. A maximum mean absolute error of 11.3% between the measurements and simulations is observed.

Near-Surface Wind Profiling in a Utility-Scale Onshore Wind Farm Using Scanning Doppler Lidar: Quality Control and Validation

Wind profiling within operating wind farms is important for both wind resource assessment and wind power prediction. With increasing wind turbine size, it is getting difficult to obtain wind profiles covering the turbine-affecting area due to the limited height of wind towers. In this study, a stepwise quality control and optimizing process for deriving high-quality near-surface wind profiles within wind farms is proposed. The method is based on the radial wind speed obtained by the Doppler Wind Lidar velocity-azimuth display (VAD) technique. The method is used to obtain the whole wind profile from ground level to the height affected by wind turbines within a utility-scale onshore wind farm, in northern China. Compared with the traditional carrier-to-noise ratio (CNR) filter-based quality control method, the proposed data processing method can significantly improve the accuracy of the derived wind. For a 10 m wind speed, an increase in coefficient of determination (R2) from 0.826 to 0.932, and a decrease in mean absolute error (MAE) from 1.231% to 0.927% are obtained; while for 70 m wind speed, R2 increased from 0.926 to 0.958, and MAE decreased from 1.023% to 0.771%. For wind direction, R2 increased from 0.978 to 0.992 at 10 m, and increased from 0.983 to 0.995 at 70 m. The optimized method also presents advantages in improving the accuracy of derived wind under complex wind environments, e.g., inside a wind farm, and increasing the data availability during clear nights. The proposed method could be used to derive wind profiles from below the minimum range of a vertically operating scanning Doppler Lidar to a height affected by wind turbines. Combined with Doppler beam-swinging (DBS) scanning data, the method could be used to obtain the complete wind profile in the boundary layer. These wind profiles could be further used to predict wind power and evaluate the climate and environmental effects of wind farms.

Rayleigh Doppler Lidar Technology Based on a Quadruple Dual-pass Fabry–Perot Interferometer

A novel Rayleigh Doppler lidar technology based on a quadruple dual-pass Fabry–Perot interferometer (FPI) that can accurately measure wind field, temperature and aerosol backscatter ratio from the troposphere to lower stratosphere is proposed. This study aims to analyse the detection principle of wind speed, temperature and aerosol backscatter ratio in detail and obtain their measurement error formulas. The structure of this type of lidar is studied and designed. The FPI consists of two edge channels FPI-1 and FPI-2, aerosol channel FPI-M and locking channel FPI-L. FPI-1, FPI-2 and FPI-M use a dual-pass optical path, whereas FPI-L uses a single-pass optical path. The parameters of FPI are optimised as follows: the free spectral spacing (FSR) is 12 GHz, the FWHM of FPI-1 and FPI-2 are both 2.2 GHz, the peak-to-peak interval of FPI-1 and FPI-2 is 5.8 GHz, the FWHM of FPI-M and FPI-L are both 1.2 GHz, the peak-to-peak interval of FPI-M and FPI-1 is 2.9 GHz and the peak-to-peak interval of FPI-L and FPI-1 is 2.3 GHz. Under simulated atmospheric conditions, for a daytime sky background brightness of 0.3 Wsr−1m−2nm−1 at 355 nm, using a laser with a pulse energy of 350 mJ and a repetition frequency of 50 Hz and a telescope with a 0.45-m aperture, with a vertical range resolution of 30 m at 0–10 km, 100 m at 10–20 km and 500 m at 20–35km, temporal resolution of 30 min, zenith angle of 0° for temperature and aerosol backscatter ratio detection and temporal resolution of 3 min and zenith angle of 30° for radial wind speed detection, the detection performance of the designed Rayleigh Doppler lidar is determined. The simulation results show that the measurement errors of aerosol backscatter ratio, temperature and radial wind speed of the lidar system in the daytime and night-time are less than 4.36 × 10−3 and 3.32 × 10−3 (excluding cirrus cloud area), 4.0 K and 3.0 K and 3.8 m/s and 1.9 m/s, respectively, from an altitude of 0.06 to 35km.

Multi-longitudinal-mode Doppler lidar technology based on quadri-channel Mach–Zehnder interferometer

The detection principle of a multi-longitudinal-mode (MLM) Doppler lidar based on a quadri-channel Mach–Zehnder interferometer (QMZI) was analysed. The measurement error formulas for the radial wind speed and backscatter ratio of this type of Doppler lidar system were derived. The advantages of this detection technology were thoroughly analysed based on the principle. The optical path difference (OPD) ‘l’ between the two interference arms of the QMZI was optimised. For a detection height of 0–20 km, ‘l’ was selected as 50 cm to balance the detection of radial wind speed and backscatter ratio. The overall structure of the MLM Doppler lidar based on QMZI was designed, and detailed design parameters of the system were provided. Further simulation was conducted to evaluate the detection performance of the designed QMZI- based MLM Doppler lidar system. The simulation results showed that when using a pulse laser with a power of 17.5 W@355 nm and a telescope with an aperture of 25 cm, a detection zenith angle of 30°, a vertical resolution of 26 m@0–10 km and 52 m@10–20 km and a pulse accumulation time of 1 min, the radial wind speed measurement errors of the system during the day and night were less than 2.1 m/s and 2.5 m/s; the backscatter ratio relative measurement errors were less than 0.81% and 0.97%.

Impact of probe volume and peak detection methods on lidar rotor effective wind speed and turbulence intensity estimations

Lidar simulation techniques are a suitable and increasingly reliable alternative for testing lidar measuring strategies and illustrating their response when combined with modelled wind fields. In this work, two simulation tools are combined to assess the uncertainty in the derivation of the rotor effective wind speed and the wind speed variance from a forward-looking nacelle-mounted continuous wave lidar wind speed estimations. These uncertainties are analysed for a variety of atmospheric turbulence levels and lidar measuring strategies. A synthetic turbulence generator is used to create the reference wind fields. Subsequently, a lidar simulator operated in a continuous-wave mode is used to scan the synthetic wind fields and perform a sensitivity analysis by comparing first- and second-order statistics against reference values. The lidar simulator is enhanced with three Doppler peak detection methods, namely the maximum, the median and the centroid, to extract radial wind speeds from the velocities found within the probe volume. The results show that probe volume and peak detection methods influence the uncertainty of the wind speed variance. The uncertainty in time-averaged and instantaneous rotor effective wind speed estimations is not sensitive to the lidar spatial averaging or peak detection methods investigated. Finally, we saw that the turbulence intensity influences the derived lidar quantities and is the main driver of the variations in rotor effective wind speed uncertainty estimations.

Annual Variations in the Near-Earth Solar Wind

Earth’s orbit and rotation produces systematic variations in geomagnetic activity, most notably via the changing orientation of the dayside magnetospheric magnetic field with respect to the heliospheric magnetic field (HMF). Aside from these geometric effects, it is generally assumed that the solar wind in near-Earth is uniformly sampled. But systematic changes in the intrinsic solar wind conditions in near-Earth space could arise due to the annual variations in Earth heliocentric distance and heliographic latitude. In this study, we use 24 years of Advanced Composition Explorer data to investigate the annual variations in the scalar properties of the solar wind, namely the solar wind proton density, the radial solar wind speed and the HMF intensity. All parameters do show some degree of systematic annual variation, with amplitudes of around 10 to 20%. For HMF intensity, the variation is in phase with the Earth’s heliocentric distance variation, and scaling observations for distance largely explains the observed variation. For proton density and solar wind speed, however, the phase of the annual variation is inconsistent with Earth’s heliocentric distance. Instead, we attribute the variations in speed and density to Earth’s heliographic latitude variation and systematic sampling of higher speed solar wind at higher latitudes. Indeed, these annual variations are most strongly ordered at solar minimum. Conversely, combining scalar solar wind parameters to produce estimates of dynamic pressure and potential power input to the magnetosphere results in solar maximum exhibiting a greater annual variation, with an amplitude of around 40%. This suggests Earth’s position in the heliosphere makes a significant contribution to annual variations in space weather, in addition to the already well-studied geometric effects.

Detection of Atmospheric Wind Speed by Lidar Based on Quadrichannel Mach–Zehnder Interferometer

For a long time, wind speed profile measurement has been the primary task of weather forecasting. Therefore, the detection of atmospheric wind speed is extremely important for studying the changes in atmospheric motion. In order to solve the problems of insufficient data collection, low resolution, and low accuracy in atmospheric wind field detection, this paper introduces the relevant theories of wind speed detection, completes the optical design of the system according to the research objectives, and determines the selection of optical devices. At the same time, a Doppler wind lidar system based on a quadrichannel Mach–Zehnder interferometer is designed and built to carry out ground-based observation experiments, collect echo signal data, and inverse the atmospheric radial wind speed. Furthermore, the wind measurement error is analyzed. Firstly, the paper introduces the basic principle of the wind measurement system, i.e., using the Doppler effect of light, and then analyzes the frequency discrimination device of the system in detail, and obtains the theoretical calculation method of atmospheric wind speed inversion. At the same time, the relevant datasets of wind measurement system are analyzed, including backscattering ratio, aerosol, and molecular extinction coefficient, and the emission mechanism of the large pulse laser is also studied in detail, which provides a theoretical basis for the model construction of Doppler lidar and the research on the enhancement of pulsed laser emission energy. Secondly, according to the research index of wind measurement, a Doppler wind measurement lidar system based on a quadrichannel Mach–Zehnder interferometer is designed, including the design of ab external light path transceiver system, internal light path interferometer, software and hardware, and algorithm. The calibration of the quadrichannel Mach–Zehnder interferometer is completed, with its maximum interference contrast reaching 0.869. Through the self-developed optical transceiver system and data acquisition system, the echo signal of lidar is received and detected. Lastly, the data of echo signals collected by the interferometer are analyzed, the radial atmospheric wind speed profile is inversed, and the signal-to-noise ratio and wind speed measurement error of the system are evaluated. The experimental results show that the maximum signal-to-noise ratio (SNR) of the system can reach 1433 when the emission pulse energy of the large pulse laser is adjusted to 255 mJ, and the farthest wind speed detection distance is about 8 km. The high-precision wind speed detection range can reach 2 km, the actual wind measurement errors in this range are all within 1.593 m/s, and the minimum error is only 0.418 m/s. In addition, the backscattering coefficient and extinction coefficient of atmospheric molecules and aerosols in the range of 8 km and the atmospheric temperature in the range of 10 km are also measured. The measurement accuracy of the aerosol extinction coefficient is ±0.001 m−1, and the measurement error of atmospheric temperature within 10 km is within 2 K, achieving the expected goals.

Comparing scanning lidar configurations for wake measurements based on the reduction of associated measurement uncertainties

Scanning lidars are increasingly being used for new measurement applications, such as wake measurements. This type of measurement requires an uncertainty quantification, and the setup of such instruments should ideally be planned to minimize the overall measurement uncertainty. Based on a previous experimental study, we quantify the overall uncertainty for a scanning lidar wake measurement campaign by analyzing the pointing accuracy for distinct configuration scenarios. The selected scenarios are based on a single ground-based scanning lidar measuring the downstream flow, a scanning lidar mounted on the turbine’s nacelle and, finally, two scanning lidars measuring dual-Doppler points within the wake. The results for each configuration are presented in terms of the overall uncertainty and measurement outputs provided from these setups. In a case study using the experimental dataset to compare ground- and nacelle-based configurations, we find that – under slightly stable conditions at 5D downstream – the overall radial wind speed uncertainty, normalized by reference wind speed without counting the sample size uncertainty, decreases on average from 2.78% for the ground-based lidar to 1.33% for the nacelle-based setup. Another advantage of the nacelle-based setup is the potentially larger sample size, as it can measure multiple downstream distances at once. The dual-lidar configuration has advantages in providing horizontal wind speed and direction instead of radial wind speed components only, hence reducing uncertainties associated with wind direction. However, this comes with the cost of fewer measured points to be compared with an engineering wake model and less flexibility to position the lidars, since their relative spatial position impacts the uncertainty. In summary, the presented methodology can benefit the best selection of scanning lidar configuration for a particular application, here demonstrated for wake measurements, proving the user with an estimation of the overall measurement uncertainty and, most importantly, the sensitivity of each parameter.

Evidence of Ocean Waves Signature in the Space–Time Turbulent Spectra of the Lower Marine Atmosphere Measured by a Scanning LiDAR

To achieve more accurate weather and climate forecasting, and propose efficient engineering solutions for exploiting offshore renewable energies, it is imperative to accurately describe the atmospheric turbulent flow in the offshore environment. The ocean’s dynamics raise specific challenges for the aforementioned applications, as they significantly alter the atmospheric flow through complex wind–wave interactions. These interactions are important in fairly common situations and notably in old-sea conditions, where ocean waves travel fast, under comparatively slow wind velocities. In the present study, a scanning LiDAR (sLiDAR) was deployed on the shore to study micro-scale wind–wave interactions by performing horizontal scans 18 m above the ocean, and as far as 2 km from the coast. In the proposed configuration, and in the test cases presented in old seas, the sLiDAR captures wave-induced disturbances propagating into the lower part of the marine atmospheric boundary layer. Based on measurements of high-resolution space–time maps of the Radial Wind Speed, an original two-dimensional spectral analysis of the space–time auto-correlation functions was performed. Unlike more conventional data-processing techniques, and as long as the waves travel sufficiently (∼twofold) faster than the mean wind at the measurement height, the upward transfer of motions from the waves to the wind can be clearly distinguished from the atmospheric turbulence in the wave-number–angular-frequency (k–w) turbulent spectra. These are the first space–time auto-correlation functions of the wind velocity fluctuations obtained at micro-scales above the ocean. The analyses demonstrate sLiDAR systems’ applicability in measuring k–w-dependent turbulent spectra in the coastal environment. The findings present new perspectives for the study of micro-scale wind–wave interactions.

Increase a real wind farm productivity through optimizing wind turbines layout

In this paper, a 3D wake model considering both axial and radial wind speed variations along the incoming wind direction, and the non-flat topography effect on the wind flow, is developed for the layout optimization of a real onshore wind farm. The effectiveness of two methods (i.e., the discretization method that divides the wind scenario into small intervals and the Monte Carlo method which randomly generates the discrete wind speed samples), for evaluating the overall wind farm power production under the wind speed variation of Weibull distribution is investigated for the comparative study. It is found that the Monte Carlo power evaluation method achieves a better outcome than the traditional discretization method, with more total power output and less computational cost. Through the layout optimization with a total of 15 wind turbines installed, the individual wind turbine yields more than 533 kW power out of 536 kW theoretical wake-free power. As the installed wind turbine number increases, the maximum discrepancy of the actual wind turbine power output with respect to the theoretical power increases from 3 kW (with 15 wind turbines) to 6 kW (with 20 wind turbines). Through the comparative study of different wind rotation scenarios, it is found that the maximum discrepancy of individual actual wind turbine power outputs is 8 kW and 13 kW for a rotational angle of [Formula: see text] and [Formula: see text], respectively. Under the scenario of [Formula: see text] wind rotation scenario, the maximum individual power output deficit with 20 installed wind turbines is around 20 kW and the discrepancy of the total power output by comparing to the baseline wind model is maximally 1% proving the robustness of the optimization results with respect to the wind scenario variation.

Experimental Investigation of the Near-Surface Flow Dynamics in Downburst-like Impinging Jets Immersed in ABL-like Winds

Downburst winds are strong downdrafts of cold air that embed into the atmospheric boundary layer (ABL) and produce intense horizontal outflow upon impingement on the ground. They are highly transient and three-dimensional extreme wind phenomena with a limited spatiotemporal structure that often makes the anemometric measurements in nature inadequate for reconstructing their complex flow fields. In the framework of the project THUNDERR, an experimental campaign on downburst outflows has been carried out at the WindEEE Dome at Western University, Canada. The present study analyzes the three-dimensional interaction between downburst (DB) outflows produced as large-scale impinging jets and ABL winds. Most experimental, numerical and analytical models in the literature neglect this flow interplay or treat it in an oversimplistic manner through a vector superposition. We found that the generated near-surface outflow is asymmetric, and a high-intensity wind zone develops at the interface between DB and ABL winds. The time variability of the leading edge of the outflow was investigated by synchronizing all wind measurements across the testing chamber. The three-dimensional flow structure was studied using a refined grid of Cobra probes that sampled the flow at high frequencies. The passage of the primary vortex produced a significant decrease in the height of maximum radial wind speed, predominantly in the ABL-streamwise direction. The turbulence intensity was the highest in the region where DB propagates into oppositely directed ABL winds.

Flux Rope Merging and the Structure of Switchbacks in the Solar Wind

Abstract A major discovery of Parker Solar Probe (PSP) was the presence of large numbers of localized increases in the radial solar wind speed and associated sharp deflections of the magnetic field—switchbacks (SBs). A possible generation mechanism of SBs is through magnetic reconnection between open and closed magnetic flux near the solar surface, termed interchange reconnection, that leads to the ejection of flux ropes (FRs) into the solar wind. Observations also suggest that SBs undergo merging, consistent with an FR picture of these structures. The role of FR merging in controlling the structure of SBs in the solar wind is explored through direct observations, analytic analysis, and numerical simulations. Analytic analysis reveals key features of the structure of FRs and their scaling with heliocentric distance R, which are consistent with observations and demonstrate the critical role of merging in controlling the structure of SBs. FR merging is shown to energetically favor reductions in the strength of the wrapping magnetic field and the elongation of SBs. A further consequence is the resulting dominance of the axial magnetic field within SBs that leads to the observed characteristic sharp rotation of the magnetic field into the axial direction at the SB boundary. Finally, the radial scaling of the SB area in the FR model suggests that the observational probability of SB identification should be insensitive to R, which is consistent with the most recent statistical analysis of SB observations from PSP.

Direct Comparison of Sea Surface Velocity Estimated From Sentinel-1 and TanDEM-X SAR Data

This article presents the first direct comparison of the sea surface radial velocity (RVL) derived from the two satellite SAR systems Sentinel-1 and TanDEM-X, operating at different frequencies and imaging modes. The RVL is derived from the Doppler centroid (Dc) provided in the Sentinel-1 OCN product and from the along-track interferometric phase of the TanDEM-X. The comparison is carried out using unique opportunistic acquisitions, collocated in space and time, over three different sites located in the Iceland Sea, the Pentland Firth, and the Kattegat Sea. First, it is observed that the RVL derived from both satellites is biased, thus calibration is applied using the land as a reference. The comparison shows that the correlation and the mean bias between the two datasets depend on the differences in acquisition time, incidence angle, and azimuth angle, and on wind and surface velocities. It is found that, given a time difference of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\lesssim$</tex-math></inline-formula> 20 min, the spatial correlation coefficient is relatively high (between 0.70 and 0.93), which indicates that the two SAR systems observe similar sea surface current fields. The spatial correlation degrades primarily due to increasing time difference and decreasing velocity magnitudes. It is also found that the mean RVL bias increases primarily with the radial wind speed, which suggests that the bias is mainly due to the wave-induced Doppler shift. This article shows that under certain conditions, i.e., similar acquisition geometry and short time delay, a good agreement between the two independently derived RVL is achieved, both in the spatial variation and absolute mean value. This encourages a synergistic use of the sea surface velocity estimated from different C- and X-band SAR systems.

A SAR-Based Parametric Model for Tropical Cyclone Tangential Wind Speed Estimation

The tangential wind speed increases from the center to the eyewall of tropical cyclones (TC) along the radial direction and begins to decay when it extends outward. The tangential wind profile model is one of the most effective and widely used methods to reconstruct the TC radial wind speed. This paper proposes a parametric tangential wind profile (TWP) model based on high-spatial-resolution SAR imagery. The new model functions are piecewise with maximum tangential wind speed as a threshold, and all of them are designed as nonlinear. Notably, the derivative at the segmentation threshold is zero to ensure a smooth transition of the estimated wind speed profile. With the SAR-derived azimuth-averaged wind speed, we can determine the model parameters and get the tangential wind speed. The TWP model outperforms the commonly used SMRV model, as it better resolves the tangential wind profile shape as depicted by both SAR-derived winds and hurricane hunter Stepped-Frequency Microwave Radiometer (SFMR) derived winds. A comprehensive analysis of the TWP model parameters is carried out by fitting tangential winds for 620 hurricane hunter flights. Interestingly, the tangential wind profiles for major hurricanes show a similar shape. The proposed TWP model can be used for improved TC characterization and forecasting purposes.

Dropsonde observations and numerical simulations of intensifying/weakening tropical cyclones over the northern South China Sea

Vertical profiles of tangential and radial wind speeds in Cyclone Mangkhut at 0900–1200 utc 15 September 2018 are shown. Red triangles represent dropsonde locations. Orange solid dots and dashed lines respectively represent observed and simulated tangential wind speed U tan (in ms−1), anti-clockwise positive. Blue solid dots and dashed lines respectively represent observed and simulated radial wind speed U rad (in ms−1), outflow positive. z represents height above mean sea level (in km). d represents distance from storm centre (in km).

Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System

Floating LIDAR systems (FLS) are a cost-effective way of surveying the wind energy potential of an offshore area. However, as turbulence intensity estimates are strongly affected by wave-induced buoy motion, it is essential to correct them. In this study, we quantify the turbulence intensity measurement error of a WindCube v2® mounted on a 12-ton anchored buoy as a function of met-ocean conditions, and we construct a subsequently applied correction method suitable for 10-min wind LIDAR data storage. To this end, we build a model to simulate the effect of buoyancy movements on the LIDAR’s wind measurements. We first apply the model to understand the mechanisms responsible for the wind LIDAR measurement error. The effect of the buoy’s rotational and translational motions on the radial wind speed measurements of the individual beams is first studied. Second, the temporality induced by the LIDAR operation is taken into account; the effect of motion subsampling and the interaction between the different measurement beam positions. From this model, a correction method is developed and successfully applied to a 13-week experimental campaign conducted off the shores of Fécamp (Normandie, France) involving the buoy-mounted WindCube v2® compared with cup anemometers from a met mast and a fixed WindCube v2® on a platform. The correction improves the linear regression against the fixed LIDAR turbulence intensity measurements, shifting the offset from ~0.03 to ~0.005 without post-processing the remaining peaks.

Empirical Relationship Between the Doppler Centroid Derived From X-Band Spaceborne InSAR Data and Wind Vectors

One of the challenges in ocean surface current retrieval from synthetic aperture radar (SAR) data is the estimation and removal of the wave-induced Doppler centroid (DC). This article demonstrates empirically the relationship between the dc derived from spaceborne X-band InSAR data and the ocean surface wind and waves. In this study, we analyzed over 300 TanDEM-X image pairs. It is found that the general characteristics of the estimated dc follow the theoretically expected variation with incidence angle, wind speed, and wind direction. An empirical geophysical model function (GMF) is fit to the estimated dc and compared to existing models and previous experiments. Our GMF is in good agreement (within 0.2 m/s) with other models and data sets. It is found that the wind-induced Doppler velocity contributes to the total Doppler velocity with about 15% of the radial wind speed. This is much larger than the sum of the contributions from the Bragg waves (~0.2 m/s) and the wind-induced drift current (~3% of wind speed). This indicates a significant (dominant) contribution of the long wind waves to the SAR dc. Moreover, analysis of dual-polarized data shows that the backscatter polarization ratio ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$PR=\sigma ^{0}_{VV}/\sigma ^{0}_{HH}$ </tex-math></inline-formula> ) and the dc polarization difference ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$PD={|dc_{VV}|-|dc_{HH}|}$ </tex-math></inline-formula> ) are systematically larger than 1 and smaller than 0 Hz, respectively, and both increase in magnitude with incidence angle. The estimated PR and PD are compared to other theoretical and empirical models. The Bragg scattering theory-based (pure Bragg and composite surface) models overestimate both PR and PD, suggesting that other scattering mechanisms, e.g., wave breaking, are involved. In general, it is found that empirical models are more consistent with both backscatter and Doppler data than theory-based models. This motivates a further improvement of SAR dc GMFs.

Analysis on the Evolution and Microphysical Characteristics of Two Consecutive Hailstorms in Spring in Yunnan, China

By using products of the cloud model, National Centers for Environmental Prediction (NCEP) Final Operational Global Analysis (FNL) reanalysis data, and Doppler weather radar data, the mesoscale characteristics, microphysical structure, and mechanism of two hail cloud systems which occurred successively within 24 h in southeastern Yunnan have been analyzed. The results show that under the influence of two southwest jets in front of the south branch trough (SBT) and the periphery of the western Pacific subtropical high (WPSH), the northeast-southwest banded echoes affect the southeastern Yunnan of China twice. Meanwhile, the local mesoscale radial wind convergence and uneven wind speed lead to the intense development of convective echoes and the occurrence of hail. The simulated convective cloud bands are similar to the observation. The high-level mesoscale convergence line leads to the development of convective cloud bands. The low-level wind direction or wind speed convergence and the high-level wind speed divergence form a deep tilted updraft, with the maximum velocity of 15 m·s−1 at the −40~−10 °C layer, resulting in the intense development of local convective clouds. The hail embryos form through the conversion or collision growth of cloud water and snowflakes and have little to do with rain and ice crystals. Abundant cloud water, especially the accumulation region of high supercooled water (cloud water) near the 0 °C layer, is the key to the formation of hail embryos, in which qc is up to 1.92 g·kg−1 at the −4~−2 °C layer. The hail embryos mainly grow by collision-coalescence (collision-freezing) with cloud water (supercooled cloud drops) and snow crystal riming.

No Stagnation Region before the Heliopause at Voyager 1? Inferences from New Voyager 2 Results

Abstract We present anisotropy results for anomalous cosmic-ray protons in the energy range ∼0.5–35 MeV from Cosmic Ray Subsystem (CRS) data collected during calibration roll maneuvers for the magnetometer instrument when Voyager 2 (V2) was in the inner heliosheath. We use a new technique to derive for the first time the radial component of the anisotropy vector from CRS data. We find that the CRS-derived radial solar wind speeds, when converted from the radial components of the anisotropy vectors via the Compton–Getting (C–G) effect, generally agree with those similarly derived speeds from the Low Energy Charged Particle experiment using 28–43 keV data. However, they often differ significantly from the radial solar wind speeds measured directly by the Plasma Science (PLS) instrument. There are both periods when the C–G-derived radial solar wind speeds are significantly higher than those measured by PLS and times when they are significantly lower. The differences are not expected nor explained, but it appears that after a few years in the heliosheath the V2 radial solar wind speeds derived from the C–G method underestimate the true speeds as the spacecraft approaches the heliopause. We discuss the implications of this observation for the stagnation region reported along the Voyager 1 trajectory as it approached the heliopause inferred using the C–G method.