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Doppler radar data-based downburst forecasting method

A technology of Doppler radar and prediction method, applied in the field of downburst disaster prediction, can solve the problems of low downburst recognition rate, etc., and achieve the effect of reducing economic losses and casualties

Active Publication Date: 2019-01-08
TIANJIN UNIV
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Problems solved by technology

In addition, the identification rate of downbursts is low, and there is room for improvement in the automatic identification and prediction method of downbursts based on Doppler weather radar

Method used

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  • Doppler radar data-based downburst forecasting method
  • Doppler radar data-based downburst forecasting method
  • Doppler radar data-based downburst forecasting method

Examples

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experiment example

[0066] Experimental example: used in meteorology to identify and forecast downbursts, the steps are as follows:

[0067] 1) Collect historical radar data of downbursts and other types of disaster weather;

[0068] The information collected about historical sample data of downbursts and other severe weather types is: the start time and end time of all sample data are 2008-2017, respectively. By analyzing the storm disaster reports, a total of 594 disaster event reports containing downbursts and 6289 disaster records not related to downbursts were found. Through downsampling, 594 records were selected from the samples of non-downburst disasters.

[0069] According to the disaster report records of downbursts and non-downbursts, a total of 1254 radar scan data were found from the radar database, and the interval between radar data was 3 minutes. A disaster record corresponds to a group of radar data sequences, called a case, and the average length of a case is 63 individual sca...

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Abstract

The invention discloses a Doppler radar data-based downburst forecasting method, which comprises the following steps: acquiring 10 years of storm event reports and Doppler weather radar data matched with the reports, identifying convection monomers at all moments, and extracting static features to acquire a convection monomer order; matching the convection monomer order with the storm events; by taking a disaster occurrence moment as a time reference point, splitting the convection monomer order into a plurality of sample order segment sets; extracting feature sets of the sample order segmentsets, and performing a statistical significance test to find out significance feature sets of positive and negative sample feature sets; performing dimensionality reduction and decoupling on the significance feature sets through main component analysis to acquire effective features, then training a classifier model, and acquiring a group of classifier models; and combining and applying a classifier model set to detect and forecast a downburst. The Doppler radar data-based downburst forecasting method can be used for automatically detecting the convection monomers causing the downburst and forecasting occurrence time and an occurrence location of the downburst.

Description

technical field [0001] The invention relates to downburst disaster prediction in the field of meteorology, in particular to a method for automatically identifying convective cells that generate downbursts by using Doppler weather radar data. Background technique [0002] Convective gale includes linear gale, tornado, etc.; linear gale includes bow echo and downburst. Among them, the harm of downbursts in airports and ports is very obvious. In the field of meteorological forecasting, Doppler weather radar is an effective tool for monitoring convective storms. Using Doppler weather radar, the three-dimensional structure of convective storms can be obtained, and at the same time, the radial velocity of particles inside the convective storm can be detected. With the help of Doppler weather radar, it is possible to detect some salient features of the convective cells that produce downbursts, such as the height of the overhanging cell nucleus and the radial convergence of the mid...

Claims

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Application Information

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IPC IPC(8): G01S13/95
CPCG01S13/95Y02A90/10
Inventor 王萍赵宗玉侯谨毅
Owner TIANJIN UNIV
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