Radar echo extrapolation prediction method and system based on velocity field sensing network

Abstract

The invention provides a radar echo extrapolation prediction method and system based on a velocity field sensing network. The prediction method includes: inputting radar echo data and velocity field data into a trained velocity field sensing radar extrapolation network model to obtain a prediction radar echo sequence, wherein the trained velocity field sensing radar extrapolation network model isobtained by the following steps of building a memory at any time, building an output gate at any time, obtaining a hidden state at any time, constructing a long short-term memory network structure atany time, building and integrating a radar extrapolation network model with a velocity field to obtain the velocity field sensing radar extrapolation network model, and inputting tensor sequence datainto the velocity field sensing radar extrapolation network model for training to obtain a trained velocity field sensing radar extrapolation network model. According to the invention, information hidden in historical data is mined. The velocity field is combined in the velocity field sensing radar extrapolation network model, which makes the model have more accurate prediction capability.

Description

technical field [0001] The present invention relates to the field of computer data analysis, more specifically, to a radar echo extrapolation prediction method and system based on a velocity field perception network. Background technique [0002] Radar weather data is crucial to national meteorological services, and radar echo extrapolation is a major means of quantitative precipitation forecasting and catastrophic short-term forecasting. Therefore, whether the radar echo sequence in the future can be accurately predicted based on the radar echo sequence in the past will affect the accuracy of the subsequent quantitative precipitation forecast and disaster short-term forecast. The accurate prediction of radar echo extrapolation is extremely important for generating emergency rainfall warnings at the social level, generating airport weather guidance, and seamlessly connecting to long-term numerical weather prediction models. [0003] In the process of radar echo extrapolatio...

AI Technical Summary

Problems solved by technology

However, these methods are purely data-driven, the network structure design is not reasonable enough, and the prediction results are inaccurate

Images