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Method and system for automatic identification and tracking of low vortex and shear line based on deep learning

A deep learning and automatic identification technology, applied in the field of meteorology, can solve the problems of unable to replace the manual identification of meteorological workers, low accuracy, etc.

Active Publication Date: 2022-06-21
河南省气象台 +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, the existing calculation results of low vortex and shear line positions based on synoptic principles and simple mathematical formulas have low accuracy and cannot replace the manual judgment of meteorologists based on the rich experience accumulated by synoptic principles.

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  • Method and system for automatic identification and tracking of low vortex and shear line based on deep learning
  • Method and system for automatic identification and tracking of low vortex and shear line based on deep learning
  • Method and system for automatic identification and tracking of low vortex and shear line based on deep learning

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Embodiment Construction

[0126] The present invention will be described below with reference to specific examples. Those skilled in the art can understand that these examples are only for illustrating the present invention, and they do not limit the scope of the present invention in any way.

[0127] The automatic identification and tracking method of low eddy and shear lines based on deep learning includes the following steps:

[0128] S1. Collect, store and preprocess the reanalysis data and numerical model prediction results to obtain a normalized data set;

[0129] In this example, the reanalysis data and meteorological station data for the 30 years from 1990 to 2019 are prepared; such as figure 1 As shown, the implementation of step S1 includes the following steps:

[0130] S101. Automatically download historical, real-time reanalysis data and numerical model forecast results, and automatically store the meteorological element field by date,

[0131] S102. Perform data format conversion on the...

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Abstract

The invention discloses a method and system for automatic identification and tracking of low vortex and shear line based on deep learning. The present invention uses deep learning technology and label sampling of massive historical data, and combines the comprehensive physical rules of meteorologists and the judgment rules of experience and intuition to establish a deep learning model to achieve the effect of imitating manual judgment; greatly improve the low vortex and shear line The accuracy of automatic computer judgment can basically replace the manual judgment of meteorologists based on experience.

Description

technical field [0001] The invention belongs to the technical field of meteorology, and in particular relates to a method and system for automatic identification and tracking of low vortex and shear lines based on deep learning. Background technique [0002] A vortex, a meteorological term, refers to a cyclonic vortex on a weather map where the central pressure tends to be lower than the surrounding area, that is, a low-pressure vortex with a smaller horizontal and vertical extent in the middle and lower troposphere of the atmosphere. It is mainly a weather system relative to the pressure field, and is most significant on the isobaric surfaces of 500hPa, 700hPa and 850hPa. [0003] Shear line, a meteorological term, refers to a discontinuous line with cyclonic sudden changes in the wind field, and the components of the wind vector on both sides parallel to the line have sudden changes, that is, the shear line is a sharp change in wind direction or wind speed. The narrow and...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/26G06F16/26G06F16/25G06F16/29G06N3/04G06N3/08
Inventor 王新敏张勇牛涛张霞高宏斌栗晗邓博文钟宇峰
Owner 河南省气象台