Application of SAR Data for Tropical Cyclone Intensity Parameters Retrieval and Symmetric Wind Field Model Development

The spaceborne synthetic aperture radar (SAR) is an effective tool to observe tropical cyclone (TC) wind fields at very high spatial resolutions. TC wind speeds can be retrieved from cross-polarization signals without wind direction inputs. This paper proposed methodologies to retrieve TC intensity parameters; for example, surface maximum wind speed, TC fullness (TCF) and central surface pressure from the European Space Agency Sentinel-1 Extra Wide swath mode cross-polarization data. First, the MS1A geophysical model function was modified from 6 to 69 m/s, based on three TC samples’ SAR images and the collocated National Oceanic and Atmospheric Administration stepped frequency microwave radiometer wind speed measurements. Second, we retrieved the wind fields and maximum wind speeds of 42 TC samples up to category 5 acquired in the last five years, using the modified MS1A model. Third, the TCF values and central surface pressures were calculated from the 1-km wind retrievals, according to the radial curve fitting of wind speeds and two hurricane wind-pressure models. Three intensity parameters were found to be dependent upon each other. Compared with the best-track data, the averaged bias, correlation coefficient (Cor) and root mean-square error (RMSE) of the SAR-retrieved maximum wind speeds were –3.91 m/s, 0.88 and 7.99 m/s respectively, showing a better result than the retrievals before modification. For central pressure, the averaged bias, Cor and RMSE were 1.17 mb, 0.77 and 21.29 mb and respectively, indicating the accuracy of the proposed methodology for pressure retrieval. Finally, a new symmetric TC wind field model was developed with the fitting function of the TCF values and maximum wind speeds, radial wind curve and the Rankine Vortex model. By this model, TC wind field can be simulated just using the maximum wind speed and the radius of maximum wind speed. Compared with wind retrievals, averaged absolute bias and averaged RMSE of all samples’ wind fields simulated by the new model were smaller than those of the Rankine Vortex model.

Estimating the Key Parameter of a Tropical Cyclone Wind Field Model over the Northwest Pacific Ocean: A Comparison between Neural Networks and Statistical Models

Estimation of maximum wind speed associated with tropical cyclones (TCs) is crucial to evaluate potential wind destruction. The Holland B parameter is the key parameter of TC parametric wind field models. It plays an essential role in describing the radial distribution characteristics of a TC wind field and has been widely used in TC disaster risk evaluation. In this study, a backpropagation neural network (BPNN) is developed to estimate the Holland B parameter (Bs) in TC surface wind field model. The inputs of the BPNN include different combinations of TC minimum center pressure difference (Δp), latitude, radius of maximum wind speed, translation speed and intensity change rate from the best-track data of the Joint Typhoon Warning Center (JTWC). We find that the BPNN exhibits the best performance when only inputting TC central pressure difference. The Bs estimated from BPNN are compared with those calculated from previous statistical models. Results indicate that the proposed BPNN can describe well the nonlinear relation between Bs and Δp. It is also found that the combination of BPNN and Holland’s wind pressure model can significantly improve the maximum wind speed underestimation and overestimation of the two existing wind pressure models (AH77 and KZ07) for super typhoons.

Theoretical Analysis and Experimental Validation on Galloping of Iced Transmission Lines in a Moderating Airflow

Galloping of an iced transmission line subjected to a moderating airflow has been analysed in this study, and a new form of galloping is discovered both theoretically and experimentally. The partial differential equations of the iced transmission line are established based on the Hamilton theory. The Galerkin method is then applied on the continuous model, and a discrete model is derived along with its first two in-plane and torsional modes. A trapezoidal wind field model is built through the superposition of simple harmonic waves. The vibrational amplitude is generally observed to be more violent when the wind velocity decreases, except in the 2nd in-plane mode. Furthermore, the influence of the declining wind velocity rates on galloping is analysed using different postdecline wind velocities and the duration of the decline in wind velocities. Subsequently, an experiment has been carried out on a continuous model of an iced conductor in the wind tunnel dedicated for galloping. The first two in-plane modal profiles are observed, along with their response to the moderating airflow. Different declining rates of the wind velocity are also verified in the wind tunnel, which show good agreement with the results simulated by the mathematical model. The sudden increase in the galloping amplitude poses a significant threat to the transmission system, which also improves the damage mechanism associated with the galloping of a slender, a long structure with a noncircular cross-section.

Capacity Configuration and Selection of Emergency Power Supply for Wind Farms under Typhoon Conditions

China’s coastal areas are rich in wind energy resources, and there is a huge market demand for wind power generators. However, due to the impact of typhoons every summer, the wind farms are cut off, causing serious damage to the wind turbines and causing significant economic losses. Based on optimizing the yaw system under typhoon conditions, this paper configures and selects the capacity of diesel generators. First, this article introduces the structure and main functions of the yaw control system. Secondly, through the study of the under-stage wind field model, the algorithm of wind speed extreme value and the calculation method of yaw angle and yaw direction are proposed, and hill climbing algorithm is introduced to optimize the work of the yaw control system. Then, a method for calculating the actual power of a single yaw control system is introduced. On this basis, the capacity configuration plan of the standby diesel generator set was determined, so that it can meet the normal yaw work of the whole field yaw system in the event of a power outage in the field to ensure the safety of the wind turbine.

Forecasts of Hurricanes Using Large-Ensemble Outputs

This paper describes the development of a model framework for Forecasts of Hurricanes Using Large-Ensemble Outputs (FHLO). FHLO quantifies the forecast uncertainty of a tropical cyclone (TC) by generating probabilistic forecasts of track, intensity, and wind speed that incorporate the state-dependent uncertainty in the large-scale field. The main goal is to provide useful probabilistic forecasts of wind at fixed points in space, but these require large ensembles [O(1000)] to flesh out the tails of the distributions. FHLO accomplishes this by using a computationally inexpensive framework, which consists of three components: 1) a track model that generates synthetic tracks from the TC tracks of an ensemble numerical weather prediction (NWP) model, 2) an intensity model that predicts the intensity along each synthetic track, and 3) a TC wind field model that estimates the time-varying two-dimensional surface wind field. The intensity and wind field of a TC evolve as though the TC were embedded in a time-evolving environmental field, which is derived from the forecast fields of ensemble NWP models. Each component of the framework is evaluated using 1000-member ensembles and four years (2015–18) of TC forecasts in the Atlantic and eastern Pacific basins. We show that the synthetic track algorithm generates tracks that are statistically similar to those of the underlying global ensemble models. We show that FHLO produces competitive intensity forecasts, especially when considering probabilistic verification statistics. We also demonstrate the reliability and accuracy of the probabilistic wind forecasts. Limitations of the model framework are also discussed.

An Improved Meshless Divergence-Free PBF Framework for Ocean Wave Modeling in Marine Simulator

It is a challenging work to simulate wind and waves in virtual scenes of marine simulators. In this paper, a divergence-free position based fluid (DFPBF) framework is introduced for ocean wave modeling in marine simulators. We introduce a set of constant density constraints and divergence-free velocity constraints to enforce incompressibility. By adjusting the position distribution of fluid particles, the particle density is forced to be constant. Constraining the divergence-free velocity field can keep the density change rate at zero. When correcting the position and velocity of particles, we introduced a relaxation correction scheme to accelerate the convergence of the framework. The simulation results show that as the scene scale expands and the number of fluid particles increases, this acceleration effect will be more significant. Secondly, we propose a novel particle-based three-dimensional stochastic fluctuating wind field. The Perlin noise is introduced to disturb the constant horizontal wind field to form a stochastic wind field. On this basis, a stochastic fluctuating wind field simulation framework is proposed. By adjusting the pulse period and pulse width, users can flexibly control the fluid turnover under the action of the wind field. This wind field framework can be easily integrated into the DFPBF model. Based on this wind field model, we simulated some typical wind wave scenarios, including interaction scenarios with lighthouse and lifebuoy, and verified the effectiveness of the wind field model.

Damage Analysis of Three Long-Track Tornadoes Using High-Resolution Satellite Imagery

Remote sensing of tornado damage can provide valuable observations for post-event surveys and reconstructions. The tornadoes of 3 March 2019 in the southeastern United States are an ideal opportunity to relate high-resolution satellite imagery of damage with estimated wind speeds from post-event surveys, as well as with the Rankine vortex tornado wind field model. Of the spectral metrics tested, the strongest correlations with survey-estimated wind speeds are found using a Normalized Difference Vegetation Index (NDVI, used as a proxy for vegetation health) difference image and a principal components analysis emphasizing differences in red and blue band reflectance. NDVI-differenced values across the width of the EF-4 Beauregard-Smiths Station, Alabama, tornado path resemble the pattern of maximum ground-relative wind speeds across the width of the Rankine vortex model. Maximum damage sampled using these techniques occurred within 130 m of the tornado vortex center. The findings presented herein establish the utility of widely accessible Sentinel imagery, which is shown to have sufficient spatial resolution to make inferences about the intensity and dynamics of violent tornadoes occurring in vegetated areas.

Modeling and Parameter Estimation of Hurricane Wind Fields with Asymmetry

This article presents an azimuthally asymmetric gradient hurricane wind field model that can be coupled with hurricane-track models for engineering wind risk assessments. The model incorporates low-wavenumber asymmetries into the maximum wind intensity parameter of the Holland et al. wind field model. The amplitudes and phases of the asymmetries are parametric functions of the storm-translation speed and wind shear. Model parameters are estimated by solving a constrained, nonlinear least squares (CNLS) problem that minimizes the sum of squared residuals between wind field intensities of historical storms and model-estimated winds. There are statistically significant wavenumber-1 asymmetries in the wind field resulting from both storm translation and wind shear. Adding the translation vector to the wind field model with wavenumber-1 asymmetries further improves the model’s estimation performance. In addition, inclusion of the wavenumber-1 asymmetry resulting from translation results in a greater decrease in modeling error than does inclusion of the wavenumber-1 shear-induced asymmetry. Overall, the CNLS estimation method can handle the inherently nonlinear wind field model in a flexible manner; thus, it is well suited to capture the radial variability in the hurricane wind field’s asymmetry. The article concludes with brief remarks on how the CNLS-estimated model can be applied for simulating wind fields in a statistically generated ensemble.