Quantitative rainfall prediction method based on radar reflectivity extrapolation

A technology of radar reflection and prediction method, applied in the field of atmospheric science, can solve the problems of large actual deviation and low accuracy of precipitation forecast, and achieve the effect of avoiding low accuracy and improving prediction accuracy.

Pending Publication Date: 2020-02-21
兰州大方电子有限责任公司
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AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is: in order to solve the current precipitation forecast based on the linear motion relationship, when predicting the echo image for a long time, the deviation from the actual is large, and the accuracy of the precipitation forecast is low. The present invention provides a radar-based Quantitative Precipitation Prediction Method Based on Albedo Extrapolation

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  • Quantitative rainfall prediction method based on radar reflectivity extrapolation

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Embodiment 1

[0033] like figure 1 As shown, this embodiment provides a quantitative precipitation prediction method based on radar reflectivity extrapolation, including:

[0034] S1: Collect radar base data for prediction, and use the reflectivity factor in the radar base data to generate radar echo reflectance images;

[0035] S2: Solve the pre-built optical flow equation based on the radar echo reflectivity image to obtain the motion field of the radar echo. Flow smooth changes;

[0036] S3: Use the pre-built recognition model to identify the strong convective area in the sports field of the radar echo, and use the SCIT algorithm to track and locate the strong convective area. The identification model identifies the strong convective area in the sports field of the radar echo, specifically including:

[0037] Traversing all the pixels of the sports field of the radar echo, if the reflectivity intensity of the current pixel is greater than the set threshold, the intensity flag of the pi...

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Abstract

The invention discloses a quantitative rainfall prediction method based on radar reflectivity extrapolation and relates to the technical field of atmospheric science. The method comprises the steps: S1, collecting radar base data for prediction and generating a radar echo reflectivity image through a reflectivity factor in the radar base data; S2, solving a pre-constructed optical flow equation based on the radar echo reflectivity image to obtain a motion field of radar echo; S3, identifying a strong convection region in the motion field of the radar echo by using a pre-constructed identification model and tracking and positioning a strong convection region; S4, constructing a radar echo extrapolation model, training the radar echo extrapolation model by using the strong convection region,and predicting radar echo data; and S5, converting the radar echo data by using a trained quantitative precipitation neural network prediction model to obtain predicted precipitation. The method hasthe advantages of simplicity and high prediction accuracy.

Description

technical field [0001] The invention relates to the technical field of atmospheric science, and more specifically relates to a quantitative precipitation prediction method based on radar reflectivity extrapolation. Background technique [0002] Currently, there are two methods for short-imminent precipitation forecasting: [0003] One is the numerical weather model forecasting method. Although the resolution and accuracy of the numerical weather prediction model are already very high, especially the accuracy of the medium and short-term flow field and situation field predicted by the numerical weather prediction model is already very high, but due to the There is a spin-up problem in all the models, and the short-imminent precipitation forecasted by the numerical weather model has a large error. [0004] The other is weather radar echo map extrapolation method. The nowcasting technology based on weather radar detection data plays a very active and effective role in short-te...

Claims

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Application Information

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IPC IPC(8): G01S13/95G01S7/40G01S7/35
CPCG01S7/4052G01S7/354G01S13/95Y02A90/10
Inventor 李晓纯李扬于娟刘明海宋如萍王怀荣
Owner 兰州大方电子有限责任公司
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