A Fast Verification Method for Upper-Air Meteorological Second-Level Data by Random Error Transmission
To ensure the accuracy of meteorological forecasts,this article puts forward a fast verification method for upper-air meteorological second-level data considering random error transmission.It can preprocess upper-air meteorological second-level data,including data centralization processing and feature point extraction.The processing method of data centralization is to implement weighted average processing of each group of data,and obtain new data groups as benchmark data,while the processing method used for feature point extraction is the traversal method,which requires traversing all data points.Then,the fast verification method is to consider the random error transmission during the data acquisition process,and implement spatial consistency check and internal consistency check on the preprocessed upper-air meteorological second-level data.A fast verification model of upper-air meteorological second-level data based on CSI-EEMD is constructed using the Ensemble Empirical Mode Decomposition(EEMD)algorithm and the Contrast Source Inversion(CSI)algorithm,and the experiment data can get quickly verified.The test results show that this new method can realize the rapid verification of the data of four weather stations,and the root mean square error and the mean absolute error of the verification results are both lower than 0.1,achieving the quality control of observation data.Applying this method to the verification of meteorological station data can achieve accurate data verification and has a certain practical value.
random error transmissionfeature point extractionupper-air meteorological second-level dataconsistency checkdata verification
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