Strong convergence field recognition and speed correction method based on Doppler weather radar data

Abstract

The invention discloses a strong convergence field recognition and speed correction method based on Doppler weather radar data, and the method comprises the following steps: designing a new coordinatesystem, converting radially distributed radar data into grid point data, and completing the extraction of a high-reflectivity area; designing a detection template, and obtaining a parameter vector for describing the convergence intensity and position of a convergence point on the basis that the convergence point is located quickly; extracting a slave convergence point to generate a convergence zone, and correcting the idea and algorithm of the convergence intensity through the direction of the convergence zone, thereby effectively solving a problem of the underestimating of the strong convergence field at a single pitch angle and even the detection leakage; determining a profile line according to the strongest convergence point at the single pitch angle, obtaining the better section of the strong convergence field, and obtaining the depth information of the strong convergence field. The method can achieve the automatic detection of the strong convergence field, solves the problems ofunderestimation and detection leakage to a certain degree through a speed correction method, achieves the automatic drawing of the section map of the strong convergence field, achieves the calculationof the feature parameter of the strong convergence field, and promotes the recognition and forecast of the convective weather disasters.

Description

technical field [0001] The invention relates to the field of meteorology, in particular to a strong convergence field identification and speed correction method based on Doppler weather radar data. Background technique [0002] Convergence intensity in convective storms often has a strong predictive effect on disastrous gale [1] . In 1992, Lemon et al. found that there is a deep convergence zone (DCZ) with a vertical extension of 10 km at the junction of the updraft and downdraft of the supercell. [2] , and disastrous winds often occur along or behind the DCZ with mesocyclone or gust front [3,4] ; Subsequently, Eilts et al. found that the strong and deep radial convergence in the middle layer is one of the factors to effectively predict the downburst [5] ; Przybylinski et al., through the study of convective systems such as squall lines and bow echoes, found that before the convective line began to "bow", the front of the convective line had already had the feature of mid...

AI Technical Summary

Problems solved by technology

This method is time-consuming and laborious, and it is difficult to accurately obtain quantitative indicators, which weakens the role of the characteristics of the strong convergence field in early warning of thunderstorms and strong winds, a

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