scholarly journals Modeling and Parameter Estimation of Hurricane Wind Fields with Asymmetry

2020 ◽  
Vol 59 (4) ◽  
pp. 687-705
Author(s):  
Derek Chang ◽  
Saurabh Amin ◽  
Kerry Emanuel

AbstractThis 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.

2000 ◽  
Vol 126 (10) ◽  
pp. 1203-1221 ◽  
Author(s):  
P. J. Vickery ◽  
P. F. Skerlj ◽  
A. C. Steckley ◽  
L. A. Twisdale

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Xiaoyang Liu ◽  
Chao Liu ◽  
Wanping Liu

Wind shear is a dangerous atmospheric phenomenon in aviation. Wind shear is defined as a sudden change of speed or direction of the wind. In order to analyze the influence of wind shear on the efficiency of the airplane, this paper proposes a mathematical model of point target rain echo and weather target signal echo based on Doppler effect. The wind field model is developed in this paper, and the antenna model is also studied by using Bessel function. The spectrum distribution of symmetric and asymmetric wind fields is researched by using the mathematical model proposed in this paper. The simulation results are in accordance with radial velocity component, and the simulation results also confirm the correctness of the established model of antenna.


2013 ◽  
Vol 79 ◽  
pp. 29-35 ◽  
Author(s):  
Ivan V. Kovalets ◽  
Vladimir Y. Korolevych ◽  
Alexander V. Khalchenkov ◽  
Ievgen A. Ievdin ◽  
Mark J. Zheleznyak ◽  
...  

Author(s):  
Eduardo Rodríguez ◽  
Gustavo Montero ◽  
Rafael Montenegro ◽  
José María Escobar ◽  
José María González-Yuste

2004 ◽  
Vol 3 (1) ◽  
pp. 33-39 ◽  
Author(s):  
Xiuqin Wang ◽  
Chengchun Qian ◽  
Wei Wang ◽  
Tong Yan

2015 ◽  
Vol 8 (4) ◽  
pp. 1259-1273 ◽  
Author(s):  
J. Ray ◽  
J. Lee ◽  
V. Yadav ◽  
S. Lefantzi ◽  
A. M. Michalak ◽  
...  

Abstract. Atmospheric inversions are frequently used to estimate fluxes of atmospheric greenhouse gases (e.g., biospheric CO2 flux fields) at Earth's surface. These inversions typically assume that flux departures from a prior model are spatially smoothly varying, which are then modeled using a multi-variate Gaussian. When the field being estimated is spatially rough, multi-variate Gaussian models are difficult to construct and a wavelet-based field model may be more suitable. Unfortunately, such models are very high dimensional and are most conveniently used when the estimation method can simultaneously perform data-driven model simplification (removal of model parameters that cannot be reliably estimated) and fitting. Such sparse reconstruction methods are typically not used in atmospheric inversions. In this work, we devise a sparse reconstruction method, and illustrate it in an idealized atmospheric inversion problem for the estimation of fossil fuel CO2 (ffCO2) emissions in the lower 48 states of the USA. Our new method is based on stagewise orthogonal matching pursuit (StOMP), a method used to reconstruct compressively sensed images. Our adaptations bestow three properties to the sparse reconstruction procedure which are useful in atmospheric inversions. We have modified StOMP to incorporate prior information on the emission field being estimated and to enforce non-negativity on the estimated field. Finally, though based on wavelets, our method allows for the estimation of fields in non-rectangular geometries, e.g., emission fields inside geographical and political boundaries. Our idealized inversions use a recently developed multi-resolution (i.e., wavelet-based) random field model developed for ffCO2 emissions and synthetic observations of ffCO2 concentrations from a limited set of measurement sites. We find that our method for limiting the estimated field within an irregularly shaped region is about a factor of 10 faster than conventional approaches. It also reduces the overall computational cost by a factor of 2. Further, the sparse reconstruction scheme imposes non-negativity without introducing strong nonlinearities, such as those introduced by employing log-transformed fields, and thus reaps the benefits of simplicity and computational speed that are characteristic of linear inverse problems.


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