Storm body position and form prediction method based on Doppler radar reflectivity image

Abstract

The invention discloses a storm body position and form prediction method based on a Doppler radar reflectivity image, and relates to the field of meteorology. The method comprises the following steps: calculating the form prediction result of a storm body at a moment Fti+1 through prediction layers of the same reflectivity intensity thresholds at two successive moments by adopting a bidirectional expansion prediction algorithm; overlaying the form prediction results of the storm body at the moment Fti+1 in other six layers in sequence by taking the form prediction results of the storm body at the moment Fti+1 in a 25dBZ prediction layer, and finally overlaying a reserved layer at a moment ti to obtain a form prediction image of the storm body at the moment Fti+1; predicting the orientation of the storm body according position change and direction change to obtain the direction angel gamma and the position coordinate C of the storm body at the moment Fti+1, and combining the form prediction image of the storm body at the moment Fti+1 to obtain a final prediction picture. According to the method, prediction of the orientation and structural form of the storm body is realized, and the type of severe convection weather can be judged more accurately.

Description

technical field [0001] The invention relates to the field of meteorology, in particular to a method for predicting the position and shape of a storm body based on Doppler radar reflectivity images. Background technique [0002] The new generation of weather radar can give the real-time echo intensity (reflectivity factor Z), radial velocity (V) and velocity spectral width (W) of precipitation particles or hail particles, and provide weather information in the form of multi-elevation images. A main method of using radar data to monitor and nowcast severe convective weather is based on accurate tracking and reasonable prediction of radar echoes. At present, the most commonly used tracking methods in the world are centroid tracking method and cross-correlation tracking method. The representative algorithms developed based on the centroid tracking method include Thunderstorm Identification, Tracking, Analysis and Nowcasting (TITAN), Storm Body Identification and Tracking Algori...

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Problems solved by technology

[0004] In the process of realizing the present invention, the inventor found that there are at least the following deficiencies in the prior art: all algorithms tend to extrapolate the storm position on the basis of storm body identification and tracking, without emphasizing the shape and structure prediction inside the storm body , and the shape and structure information are very useful for judging the type of severe convective weather

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