Identification and velocity correction method of strong convergence field based on Doppler weather radar data

Abstract

The invention discloses a strong convergence field identification and velocity correction method based on Doppler weather radar data, comprising the following steps: designing a new coordinate system to convert radially distributed radar data into grid point data, and simultaneously completing high reflectivity Region extraction; design a detection template, so as to obtain the parameter vector describing the convergence strength and position of the convergence point on the basis of quickly locating the convergence point; propose the idea of ​​generating a convergence zone from the convergence point, and then using the direction of the convergence zone to correct the convergence intensity and algorithm to effectively overcome the problem of underestimation or even missed detection of the strong convergence field at a single elevation angle; determine the profile line according to the strongest convergence point at a single elevation angle to obtain a better profile showing the strong convergence field, and obtain the depth information of the strong convergence field . This method can automatically detect the strong convergence field, and overcome certain underestimation and missed detection problems through the speed correction method, and at the same time automatically draw the profile of the strong convergence field and calculate the characteristic parameters of the strong convergence field in the profile to promote convection Recognition and forecasting of weather hazards.

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, and the calculation of the parameters of the strong convergence field is relatively rough.

In addition, there has been no effective solution to the underestimation and missed detection of MARC values ​​caused by radar observation angles of view.

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