A Quality Control Method for Surface Air Temperature Data Based on Improved Inverse Distance Weighting

Abstract

The invention provides a method for controlling the quality of surface air temperature data based on improved inverse distance weighting. The steps are as follows: S1 collects the actual daily average temperature observation data of the target station and n reference stations within a certain range; S2 establishes the original inverse distance weighting S3 establishes an improved inverse distance weighted method model for experimental prediction: calculate the first root mean square of the estimated daily average temperature of the target station and the actual value of the daily average temperature Error RMSE; Repeat S1 and S2 to calculate the second root mean square error RMSE between the estimated value of the daily average temperature of the target station and the actual value of the daily average temperature; repeat m times to obtain m groups of estimated values ​​and corresponding RMSE, m and n is obtained through PSO optimization; S4 assigns the weight value of the predicted value according to the value of RMSE, and multiplies the predicted value of each experiment by the corresponding weight to obtain the final predicted result. The accuracy, stability and adaptability of the algorithm of the invention are better, and the deviation value is smaller.

Description

technical field [0001] The invention belongs to the technical field of quality control of surface air temperature data, and in particular relates to a method for quality control of surface air temperature data based on improved inverse distance weighting. Background technique [0002] Meteorological data is the basis for meteorological research. In order to ensure that the meteorological research process truly reflects the weather and its changing laws, the quality control of the meteorological data used must be carried out before the research to ensure the authenticity and usability of the data. In recent years, with the in-depth research on climate change in various countries, many quality control methods for meteorological data have emerged. Traditional quality control methods are mainly based on meteorology, meteorological principles, climatological principles, and the temporal and spatial variation laws of various meteorological elements and the interrelationships betwe...

AI Technical Summary

Problems solved by technology

The original IDW mainly uses the distance between the target station and the reference station to carry out the weighting value. The closer the distance is, the greater the weight of the station is, and the processing effect on complex terrain and abnormal weather is not good.

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