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Self-analysis radar rainfall estimating method based on big data

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

Active Publication Date: 2016-06-29
长江水利委员会水文局
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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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  • Self-analysis radar rainfall estimating method based on big data
  • Self-analysis radar rainfall estimating method based on big data
  • Self-analysis radar rainfall estimating method 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 self-analysis radar rainfall estimating method based on big data. The method comprises the steps of: radar base data preprocessing; rainfall estimation by an optimal method; abnormal point detecting and filtering; characteristic value extracting; and dynamic estimated rainfall correction. An algorithm estimating radar rainfall data is provided by a research method of the big data. In the algorithm, firstly, abnormal point detection is adopted to filter out abnormal values or values of unconspicuous characteristics; then a DBSCAN algorithm is adopted to perform clustering analysis, and a deviation value of a representative station is calculated. The algorithm is used for dynamically correcting the data of the radar estimated rainfall, so that the rainfall estimation can be more accurate.

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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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 长江水利委员会水文局
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