Quality testing method for intensity data of weather radar

Abstract

The invention relates to a quality testing method for the intensity data of a weather radar, and the method comprises the steps: enabling a beam broadening factor to be corresponding to a radar beam broadening quality index Frange; enabling a beam blocking factor to be corresponding to a radar beam blocking quality index Fshield; enabling an electromagnetic attenuation factor to be corresponding to a radar electromagnetic attenuation quality index Fatt; enabling a vertical profile non-uniform factor to be corresponding to a radar vertical profile non-uniform quality index Fvpr; and carrying out the weighted summation of the radar beam broadening quality index Frange, the radar beam blocking quality index Fshield, the radar electromagnetic attenuation quality index Fatt and the radar vertical profile non-uniform quality index Fvpr to be weighted according to the corresponding weight coefficients, and obtaining a radar mean quality index FZ. The method gives full consideration to main factors affecting the quality of radar intensity data, is reasonable, is visual in obtained testing results, and is high in applicability.

Description

technical field [0001] The invention relates to the technical field of weather radar data processing, in particular to a method for testing the quality of weather radar intensity data. Background technique [0002] As a means of active remote sensing, radar can obtain real-time precipitation information with certain accuracy, large-scale and high spatial-temporal resolution. Using radar for rainfall monitoring and surface rainfall calculation can improve the accuracy and timeliness of flood forecasting. In flood monitoring and forecasting It has a good application prospect, so the application research of radar in hydrology and water resources has attracted more and more attention. [0003] Over the years, many meteorological and hydrological scholars have done a lot of research work on the application of radar rainfall information in the study of hydrology and water resources. These studies have provided many constructive ideas for improving the accuracy of hydrological fore...

AI Technical Summary

Problems solved by technology

These factors can bias the radar measurements from their true values ​​and directly affect the final precipitation estimate product

Although corresponding identification and correction algorithms have been developed for various problems in the quality of radar data, these algorithms still have certain limitations: that is, the focus is on data correction rather than data testing

If the quality of the data is too poor, even if the correction method is advanced, it will be difficult to get the correct result. If the rainfall is calculated based on this result, the final result will have a large error, or even a serious error.

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