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A self-categorization radar method for estimating precipitation based on big data

A big data and self-categorization technology, which is applied in the field of precipitation estimation, can solve problems such as difficult to analyze the implicit relationship of data attributes, and does not take into account the massive data of radar data, so as to improve accuracy and reduce subjective factors.

Active Publication Date: 2018-03-27
BUREAU OF HYDROLOGY CHANGJIANG WATER RESOURCES COMMISSION
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Problems solved by technology

This method belongs to the traditional mathematical method, which does not take into account the fact that radar data is actually massive data, which makes it difficult for traditional estimation techniques to analyze the implicit relationship between data attributes

Method used

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  • A self-categorization radar method for estimating precipitation based on big data
  • A self-categorization radar method for estimating precipitation based on big data
  • A self-categorization radar method for estimating precipitation based on big data

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Embodiment

[0058] Such as figure 1 As shown, the following three examples are the albedo, estimated precipitation and actual values ​​of automatic rainfall stations in Yueyang City on August 2, 2011, May 11, 2014, and May 25, 2014, respectively. Comparing the radar quantitatively estimated precipitation value (the second row in the figure) with the actual situation of the automatic rainfall station (the third row), the precipitation range and intensity have good results.

[0059] To verify the function and effect of the method of self-segmentation radar estimation of precipitation based on big data. The reason for choosing Yueyang City, Hunan Province mainly considers the following factors:

[0060] (1) Mountains, hills, and hills are widely distributed in Hunan Province, accounting for 80.49% of the province's land area. Affected by complex topographical conditions and weather and climate, rainfall is abundant, and mountain torrent disasters are extremely prone to occur.

[0061] (2) ...

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Abstract

The invention discloses a method for estimating precipitation with self-categorical radar based on big data, including radar basic data preprocessing, optimal method for estimating precipitation, abnormal point detection and filtering, feature value extraction, and dynamic correction for estimating precipitation. Using the research method of big data, an algorithm for estimating radar precipitation data is proposed. In this algorithm, outliers or values ​​with inconspicuous characteristics are first filtered out by outlier detection, and then the DBSCAN algorithm is used for cluster analysis to calculate the representative stations. The deviation value is used to dynamically revise the radar estimated precipitation data, so that the precipitation can be estimated more accurately.

Description

technical field [0001] The invention relates to a method for estimating precipitation by radar, in particular to a method for estimating precipitation by self-segmenting radar based on big data, and belongs to the technical field of estimating precipitation. Background technique [0002] my country is a country with a vast territory, complex terrain and deeply affected by climate disasters. Statistics show that about 600 million people are affected by major disastrous weather and climate such as drought, heavy rain and tropical storm in my country every year, and the average annual loss caused by meteorological disasters accounts for about 3%-5% of the gross national product. Therefore, accurate acquisition of regional rainfall information is crucial for flood control and disaster reduction. [0003] Conventional radar in the prior art intelligently obtains precipitation intensity information, and due to the influence of rain area attenuation and the inability to reflect ch...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01W1/10
CPCG01W1/10
Inventor 周北平程海云杨文发訾丽邱辉程卫帅李春龙屈家安
Owner BUREAU OF HYDROLOGY CHANGJIANG WATER RESOURCES COMMISSION
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