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Low-eddy and shear line automatic identification and tracking method and system based on deep learning

A deep learning and automatic identification technology, applied in the field of meteorology, can solve the problems of low accuracy and cannot replace the manual identification of meteorological workers.

Active Publication Date: 2021-04-16
河南省气象台 +1
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  • Abstract
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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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  • Low-eddy and shear line automatic identification and tracking method and system based on deep learning
  • Low-eddy and shear line automatic identification and tracking method and system based on deep learning
  • Low-eddy and shear line automatic identification and tracking method and system 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 used to illustrate the present invention and do not limit the scope of the present invention in any way.

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

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

[0129] In this embodiment, the reanalysis data and meteorological station data of these thirty years from 1990 to 2019 are prepared; as figure 1 As shown, the realization of the step S1 includes the following steps:

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

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

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Abstract

The invention discloses a low-eddy and shear line automatic identification and tracking method and system based on deep learning. According to the method, a deep learning technology and label sampling of massive historical data are applied, and a meteorological worker comprehensive physical rule and an empirical intuition identification rule are combined to establish a deep learning model, so that the effect of simulating manual identification is achieved; and the computer automatic identification accuracy of the low vortex and shear line is greatly improved, and the manual identification of meteorological workers according to experience can be basically replaced.

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 eddies and shear lines based on deep learning. Background technique [0002] Low vortex, a meteorological term, refers to the cyclonic vortex on the weather map where the central pressure is often lower than that of the surrounding area, that is, the low-pressure vortex that appears in the middle and lower layers of the troposphere in the atmosphere and has a small horizontal and vertical range. It is mainly a synoptic system relative to the pressure field, and it 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 mutation in the wind field, and the wind vector on both sides of it is parallel to the line. The long and narrow area is a synoptic system relative to the flow field, which ...

Claims

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Application Information

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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