NRIET X-band radar cooperative networking analysis method

Abstract

The invention discloses a NRIET X-band radar cooperative networking analysis method. The method comprises the steps that data are collected; the data quality is controlled; a distance weight interpolation technology is used, and a three-dimensional cressman interpolation method is used to perform lattice interpolation on radar echo, radial wind and each polarization; three-dimensional data networking is carried out; for a three-dimensional wind field inversed by a dual Doppler radar, the inversed wind field is constrained by a mass continuous equation, and the three-dimensional wind field is acquired by repeatedly iteratively solving the equation; the vertical velocity w is acquired by the mass continuous equation, and a trace boundary condition is used to adjust a vertical motion field, wherein the upper boundary of the mass continuous equation is set to integrate down; based on a radar product reflectivity algorithm, a combined reflectivity puzzle product and an echo top puzzle product are generated; through Z-R relationship, quantitative precipitation is estimated to acquire a rain intensity product; a texture classification method is used to identify a precipitation stratus convection region; and a fuzzy logic algorithm is used to recognize the phase state of precipitation particles in each region at different stages of a precipitation process.

Description

technical field [0001] The invention relates to a radar interpolation networking, wind field inversion and weather identification method, in particular to a NRIETX band radar collaborative networking analysis method. Background technique [0002] Monitoring, forecasting, and studying mesoscale weather systems have always been an important task of weather forecasting, and have always been a major problem in atmospheric science. The main difficulty lies in our understanding of the three-dimensional structure, The mechanisms of development and even the microphysical processes in strong convection are poorly understood. Among the various means of detecting the atmosphere, weather radar has become an extremely effective tool for disastrous weather, especially for mesoscale disastrous weather monitoring and short-term weather forecasting, due to its high temporal and spatial resolution and timely and accurate remote sensing detection capabilities. The use of weather radar has gre...

AI Technical Summary

Problems solved by technology

[0010] Aiming at the problem that the two-dimensional network mosaic product can only conduct qualitative analysis on the weather process, the three-dimensional cressman interpolation is used to interpolate the radar volume scan data into the three-dimensional grid points to obtain the three-dimensional field information of the weather process, and to combine multiple radars Network to obtain large-scale three-dimensional data to display precipitation information at various altitudes during the entire weather process

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