Wind shear signal simulation of the airborne weather radar

2011 ◽  
Author(s):  
Yi Fan ◽  
Renbiao Wu ◽  
Zhichao Meng ◽  
Zhigang Su ◽  
Xiaoguang Lu ◽  
...  
Keyword(s):  
Wind Shear ◽  
Weather Radar ◽  
Signal Simulation

Wind Shear Detection from Weather Radar Data

2019 ◽  
Vol 44 (11) ◽  
pp. 782-789 ◽  
Author(s):  
D. A. Denisenkov ◽  
V. Yu. Zhukov ◽  
G. G. Shchukin
Keyword(s):  
Wind Shear ◽  
Weather Radar ◽  
Radar Data

scholarly journals Turbulence and Wind Shear in Layers of Large Doppler Spectrum Width in Stratiform Precipitation

2009 ◽  
Vol 26 (3) ◽  
pp. 430-443 ◽  
Author(s):  
Valery M. Melnikov ◽  
Richard J. Doviak
Keyword(s):  
Wind Shear ◽  
Weather Radar ◽  
Velocity Fields ◽  
The Other ◽  
Doppler Spectrum ◽  
Weak Turbulence ◽  
Radar Observations ◽  
Spectrum Width ◽  
Stratiform Precipitation ◽  
Radar Resolution

Abstract Weather radar observations of stratiform precipitation often reveal regions having very large measured Doppler spectrum widths, exceeding 7, and sometimes 10, m s−1. These widths are larger than those typically found in thunderstorms; widths larger than 4 m s−1 are associated with moderate or severe turbulence in thunderstorms. In this work, stratiform precipitation has been found to have layers of widths larger than 4 m s−1 in more than 80% of cases studied, wherein the shear of the wind on scales that are large compared to the dimensions of the radar resolution volume is the dominant contributor to spectrum width. Analyzed data show that if width ≤7 m s−1, and if the layers are not wavy or patchy, these layers have weak turbulence. On the other hand, regions having widths >4 m s−1 in patches or in wavelike structures are likely to have moderate to severe turbulence with the potential to be a hazard to safe flight. To separate the contributions to spectrum width from wind shear and turbulence and to evaluate the errors in turbulence estimates, data have been collected with elevation increments much less than a beamwidth. Despite beamwidth limitations, the small elevation increments reveal impressive structures in the fields. For example, the “cat’s eye” structure associated with Kelvin–Helmholtz waves is clearly exhibited in the fields of spectrum width observed at low-elevation angles, but not in the reflectivity or velocity fields. Reflectivity fields in stratiform precipitation are featureless compared to spectrum width fields.

scholarly journals Spaced-Antenna Interferometry to Measure Crossbeam Wind, Shear, and Turbulence: Theory and Formulation

2007 ◽  
Vol 24 (5) ◽  
pp. 791-805 ◽  
Author(s):  
Guifu Zhang ◽  
Richard J. Doviak
Keyword(s):  
Cross Sections ◽  
Wind Shear ◽  
Cross Correlation ◽  
Weather Radar ◽  
Turbulence Theory ◽  
Wind Component ◽  
Elliptical Cross ◽  
Wind Measurements ◽  
Doppler Techniques ◽  
The Mean

Abstract The theory of measuring crossbeam wind, shear, and turbulence within the radar’s resolution volume V6 is described. Spaced-antenna weather radar interferometry is formulated for such measurements using phased-array weather radar. The formulation for a spaced-antenna interferometer (SAI) includes shear of the mean wind, allows turbulence to be anisotropic, and allows receiving beams to have elliptical cross sections. Auto- and cross-correlation functions are derived based on wave scattering by randomly distributed particles. Antenna separation, mean wind, shear, and turbulence all contribute to signal decorrelation. Crossbeam wind cannot be separated from shear, and thus crossbeam wind measurements are biased by shear. It is shown that SAI measures an apparent crossbeam wind (i.e., the angular shear of the radial wind component). Whereas the apparent crossbeam wind and turbulence within V6 cannot be separated using monostatic Doppler techniques, angular shear and turbulence can be separated using the SAI.

scholarly journals Processing algorithms for finding the boundaries of areas of dangerous wind shear for on-board weather radar

2021 ◽  
Vol 2094 (3) ◽  
pp. 032050
Author(s):  
Yu A Novikova ◽  
M B Ryzhikov
Keyword(s):  
Data Processing ◽  
Wind Shear ◽  
Weather Radar ◽  
Radar Data ◽  
International Standards ◽  
Joint Processing ◽  
Input Parameters ◽  
Processing Algorithms

Abstract This report considers the results of the development of algorithms for processing radar data when working in the mode of detecting dangerous areas of wind shear, which use binary values of hazard signs in each direction of sensing as input parameters, are presented. The first of them implements data processing for each individual direction, and the second-joint processing in all directions. As a result of their work, it is possible to identify dangerous areas of wind shear that meet the spatial requirements of the international standards ARING-708A and DO-220.

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