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Method for carrying out fusion processing on meteorological data and generating numerical weather forecast

A technology of numerical weather forecasting and fusion processing, which is applied in electrical digital data processing, special data processing applications, instruments, etc. It can solve the problems of large amount of calculation, difficulty in obtaining the precise initial value of the model state error covariance matrix, and large storage capacity.

Active Publication Date: 2019-07-16
江苏无线电厂有限公司
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AI Technical Summary

Problems solved by technology

The four-dimensional variational method and the Kalman filter method are considered to be the development direction of data assimilation, but due to the large amount of calculation, the large amount of storage, and the difficulty in obtaining the precise initial value of the model state error covariance matrix, only a few countries use it in business operations
[0009] The current research is mainly based on the assimilation of conventional observation and detection data, high-altitude sounding wind data, automatic observation station data, Doppler weather radar data, wind profile radar data, and even lightning data and other meteorological data. There is also a method of combining ground conventional observation data with other data, but there is no further research on effectively analyzing the advantages and disadvantages of various meteorological data and combining them

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  • Method for carrying out fusion processing on meteorological data and generating numerical weather forecast
  • Method for carrying out fusion processing on meteorological data and generating numerical weather forecast
  • Method for carrying out fusion processing on meteorological data and generating numerical weather forecast

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Embodiment

[0139] The invention discloses a method for merging meteorological data and generating a numerical weather forecast, comprising the following steps:

[0140] Step 1, collect and receive various meteorological element data, and obtain the meteorological element set X 1 ;

[0141] Step 2, performing standardized preprocessing on the collected meteorological element data to obtain a standardized meteorological element set X;

[0142] Step 3: Perform three-dimensional data variation assimilation on the meteorological element set X, and perform characteristic error analysis and cross-covariance analysis on the data in the meteorological element set X to obtain the covariance error mean square of each data in the meteorological element set X According to the root mean square of the covariance error, the optimal type of meteorological element data is obtained;

[0143] Step 4, compile the WRF numerical weather forecast model according to the optimal meteorological element data type...

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Abstract

The invention discloses a method for carrying out fusion processing on meteorological data and generating a numerical weather forecast, which comprises the following steps: step 1, collecting and receiving various meteorological element data from meteorological observation detection equipment or CCTV to obtain a meteorological element set X1; step 2, performing standardized preprocessing on the acquired meteorological element data to obtain a standardized meteorological element set X; step 3, performing three-dimensional data variation assimilation on the meteorological element set X, performing characteristic error analysis and cross covariance analysis on the data in the meteorological element set X to obtain a covariance error root mean square of each data in the meteorological elementset X, and obtaining an optimal meteorological element data type according to the covariance error root mean square; step 4, performing WRF numerical weather forecast mode compiling according to the optimal meteorological element type; and step 5, performing forecast post-processing on the WRF mode result to generate meteorological element numerical forecast.

Description

technical field [0001] The invention relates to the field of weather forecasting, in particular to a method for merging weather data and generating numerical weather forecasting. Background technique [0002] The numerical model itself has been able to simulate the actual atmospheric movement quite accurately, and the resolution is becoming more and more refined; Three-dimensional variation method, four-dimensional variation method and Kalman filter method. The four-dimensional variational method and the Kalman filter method are considered to be the development direction of data assimilation, but due to the large amount of calculation, the large amount of storage, and the difficulty in obtaining the precise initial value of the model state error covariance matrix, only a few countries use it in business operations. WRF's assimilation system WRFda is a relatively complete three-dimensional variational assimilation system, which has achieved remarkable results in business app...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06K9/62
CPCG06F30/20G06F18/2411G06F18/251Y02A90/10
Inventor 孙婕杜一凡于群宁张群陈国鑫周康陈晨吴宇飞赵娟
Owner 江苏无线电厂有限公司
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