Hail and short-time heavy rainfall forecasting method based on GBDT+LR model

A LR model, a technology for heavy precipitation, applied in weather forecasting, measuring devices, meteorology, etc., can solve the problem of small detection space scale, achieve excellent performance and reduce impact.

Inactive Publication Date: 2020-03-17
TIANJIN UNIV
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Problems solved by technology

[0003] Weather radar can be used to forecast hail and short-term heavy precipitation, but the information reflected by weather radar is only the real situation, and the detection space scale is small. Therefore, weather radar cannot make forecasts for a long time in advance

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  • Hail and short-time heavy rainfall forecasting method based on GBDT+LR model
  • Hail and short-time heavy rainfall forecasting method based on GBDT+LR model
  • Hail and short-time heavy rainfall forecasting method based on GBDT+LR model

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Embodiment 1

[0056] This embodiment takes the Tianjin area as an example. The hail and short-term heavy precipitation forecast method based on the GBDT+LR model in Tianjin includes the following steps:

[0057] Step S1, acquisition of raw data:

[0058]Collect the ground meteorological observation station data of Tianjin Meteorological Bureau from March to September every year from 2006 to 2018, hours before the occurrence of hail and short-term heavy precipitation, including: ground pressure, sea level pressure, temperature, dew point temperature, relative Humidity, vapor pressure, 2-minute average wind direction, 2-minute average wind speed, 10-minute average wind direction, and 10-minute average wind speed. In this embodiment, the data of 3 hours before the occurrence of hail and short-term heavy precipitation are collected.

[0059] see figure 1 , select the data of five sounding stations (at 8:00 am and 8:00 pm) in the upper reaches of Tianjin, Beijing air-sounding meteorological s...

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Abstract

The invention discloses a hail and short-time heavy rainfall forecasting method. The method comprises the following steps: acquiring ground meteorological observation station data of a certain regionfrom March to September each year before hail and short-time heavy rainfall occur and data of a plurality of sounding stations at the upstream of the region; expanding the hail process data with relatively small data volume in the data through an SMOTE oversampling algorithm to obtain an oversampled data set; carrying out dimension reduction on the oversampled data set by adopting a PCA method; dividing samples in the data set after dimension reduction into a training set and a test set; constructing a GBDT + LR model, taking features extracted from leaf nodes of the GBDT model as input features of the LR model, and training and testing the GBDT + LR model through the samples of the training set and the test set; and acquiring ground meteorological observation station data three hours before a to-be-predicted time point of the region, acquiring data of a plurality of sounding stations at the upstream of the region, substituting the data into the trained GBDT + LR model and judging whether hail or short-time heavy rainfall occurs at the predicted time point.

Description

technical field [0001] The invention relates to the field of weather forecasting, in particular to a method for forecasting hail and short-term heavy precipitation. Background technique [0002] In meteorological forecasting, hail and short-term heavy precipitation have the characteristics of short generation and extinction cycles, small affected areas, and extremely severe weather changes. They will have a great impact on industry, agriculture and people's daily life. [0003] Weather radars can be used to forecast hail and short-term heavy precipitation, but the information reflected by weather radars is only the real situation, and the detection space scale is small. Therefore, weather radars cannot forecast for a long time in advance. Contents of the invention [0004] In order to overcome the deficiencies of the prior art, the present invention aims to provide a method for forecasting hail and short-term heavy precipitation based on the GBDT+LR model, using the relat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01W1/10
CPCG01W1/10
Inventor 路志英汪永清
Owner TIANJIN UNIV
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