Meteorological data extraction and visualization method based on big data processing and four-dimensional analysis algorithm
A technology for big data processing and meteorological data, which is applied in electrical digital data processing, special data processing applications, database design/maintenance, etc. Accurate understanding and efficient delivery of effects
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specific Embodiment approach 1
[0035] Embodiment 1: The present invention discloses a method for accurately extracting and displaying meteorological data through a four-dimensional analysis algorithm and a weather recognition algorithm based on big data processing. The method includes the following steps.
[0036] S1. Establish a dynamic meteorological database.
[0037] S2. Establish an operating database (the timeliness of operating data needs to be ensured).
[0038] S3. Data processing, extracting meteorological data that accurately matches the operating data (four-dimensional analysis algorithm, weather recognition algorithm, big data processing).
[0039] S4. Data visualization.
specific Embodiment approach 2
[0040] Embodiment 2: This embodiment is a further description of Embodiment 1, and the S1 includes the following steps.
[0041] S101. Access and store meteorological data from different data sources and types in an array.
[0042] Specifically, it contains 3 different data sources;
[0043] Meteorological data types involve: temperature, wind speed, wind direction, humidity, icing, turbulence, tropopause height, and CB data; meteorological data are all four-dimensional data (x, y, z, t), and static terrain data (one-dimensional).
[0044] S102. Meteorological data preprocessing:
[0045] The turbulence data involves the merging of data from different sources. Taking into account the turbulence spatio-temporal resolution and turbulence value of different sources, four-dimensional processing is performed on its time, space, and turbulence value. Based on the processing results, the average value of turbulence from different sources is taken.
[0046] S103. Construct various t...
specific Embodiment approach 3
[0050] Specific implementation mode three: this implementation mode is a further description of specific implementation mode one, and the S2 includes the following steps:
[0051] S201. Obtain data through the operation data interface, and use the MQ polling method to ensure the timeliness of data acquisition.
[0052] S202. The flight ID in the monitoring data involves the same flight ID. If it involves a flight plan change, the latest data shall prevail, that is, the update of the flight plan data will trigger data reprocessing and rendering.
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