Method and device for extracting vertical beam turbulence spectrum of wind profile line radar during precipitation

Abstract

The invention provides a method and a device for extracting a vertical beam turbulence spectrum of a wind profile line radar during precipitation. The method comprises the following steps: obtaining first power spectral data collected by the wind profile radar and second power spectral data collected by a vertically directed millimeter wave cloud radar adjacent to the wind profile radar under a condition of uniform precipitation and layered cloud precipitation; correcting fourth power spectrum data according to attenuation rule information to generate corrected eighth power spectrum data; andextracting turbulence spectrum information generated by a tropospheric wind profile radar under the precipitation condition according to the eighth power spectral data and the third power spectral data. According to the method and the device for extracting the vertical beam turbulence spectrum of the wind profile line radar during precipitation, the inaccuracy caused by a large difference betweenthe power spectrum and the Gaussian distribution is avoided by using two radars to analyze detection data at similar places and nearly the same time; and the problem of obtaining air vertical motion information under a condition of stratified cloud precipitation with less and uniformity precipitation intensity and long duration is solved.

Description

technical field [0001] The invention relates to the field of meteorological radars, in particular to a method and a device for extracting a vertical beam turbulence spectrum of a wind profile radar during precipitation. Background technique [0002] At present, in the method of obtaining vertical wind field information under precipitation conditions, mathematical methods are mostly used at home and abroad to process the wind profile radar power spectrum. The specific method is to use mathematical methods such as double-Gaussian fitting or least square fitting to fit the bimodal characteristics of the wind profile radar power spectrum under precipitation conditions, and the fact that the bimodal theoretically conforms to the Gaussian normal distribution. The closest model to the original spectral type. When the correlation between the obtained model and the original spectrum reaches a certain threshold, it can be considered that the effect is good, and the power spectrum and...

AI Technical Summary

Problems solved by technology

However, due to the complexity of atmospheric motion, the power spectrum does not necessarily show obvious Gaussian normal distribution characteristics in some cases, resulting in poor fitting results and it is difficult to separate the accurate turbulence spectrum

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