Windshear Identification Algorithms by Doppler Pulse Lidar

Ekaterina Lemishchenko,Nikolay Baranov

doi:10.1051/itmconf/20192401011

Abstract

Doppler pulse lidars are increasingly common as a tool for monitoring hazardous wind phenomena. Possible applications include measurements of wake vortices behind aircraft, detection of vertical and horizontal wind shear, detection of gust fronts, and identification of areas of intense turbulence. This paper reviews several computational procedures used to measure wind shear parameters and determine the gust front position. Algorithms for wind shear calculation are based on the construction of regression dependencies of changes in the wind speed components at a given distance. In accordance with the ICAO recommendations, horizontal wind shear is determined at a distance of 600m. The application of the algorithms is illustrated by the results of data processing for scanning in PPI mode performed by WINDEX-5000 Doppler pulse lidar.

Highlights

Wind shear is one of the most challenging meteorological phenomena complicating aviation operations
The results of measurements obtained using WINDEX-5000 Doppler pulse lidar jointly developed by International Aero Navigation Systems Concern, JSC and Laser Systems LLC were used as initial data
Lidar scanning data in PPI mode generally takes into account horizontal wind shear, and vertical wind shear

Summary

Introduction

Wind shear is one of the most challenging meteorological phenomena complicating aviation operations. A linear approximation is constructed using the weighted least squares method for each wind speed component w(rj+0.5 LWS e) ≈aw+ bw (rj-r0) With such an approximation, the parameter bw in this case is the gradient of the wind speed component w at the distance [r0-0.5 LWS e, r0+0.5 LWS e], while the value bw⋅LWS determines the magnitude of the wind shear, calculated based on the change in the wind speed component w. To determine the position of the gust front, the measured values of the radial component of the wind speed are approximated by a logistic type function: f(r) = 1 / ( 1 + exp(a + b⋅r) ), where a, b are the approximation coefficients, and r is the range parameter.

Result and discussion

Conclusion