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Ground air temperature quality control method based on cosine similarity and moving surface fitting

A quality control method, cosine similarity technology, applied in character and pattern recognition, complex mathematical operations, instruments, etc., can solve problems such as poor results, and achieve the effect of improving accuracy

Active Publication Date: 2020-07-28
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

However, the effect is poor for mountainous areas with complex terrain and areas with sparse stations

Method used

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  • Ground air temperature quality control method based on cosine similarity and moving surface fitting
  • Ground air temperature quality control method based on cosine similarity and moving surface fitting
  • Ground air temperature quality control method based on cosine similarity and moving surface fitting

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specific Embodiment

[0059] The present invention selects Nanjing station (station number: 58238) and Xinxiang station (station number: 53986) as representatives to carry out example analysis, and the observation station within 200km of the two stations is taken as the adjacent station, figure 1 It is the station distribution within 200km around the two target stations of Nanjing and Xinxiang.

[0060] Figure 2(a) and Figure 2(b) are the RMSE-COS schematic diagrams of the target station and the surrounding stations. From Figure 2(a) and Figure 2(b), it can be seen that RMSE and COS basically show linear changes, and RMSE The bigger the COS is, the smaller the RMSE is, the smaller the COS is. The points farther from the rectangular area in the figure are called outliers, the points closer to the periphery of the rectangle are called adjacent points, and the points inside the rectangle are called similar points. The abscissa RMSE calculates the error between the temperature observation data of each...

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Abstract

The invention discloses a ground air temperature quality control method based on cosine similarity and moving surface fitting, and relates to the technical field of ground air temperature quality control algorithms. The method specifically comprises the following steps: selecting the daily average temperature time series data of a target station and the daily average temperature time series data of an adjacent station at the same time slot; calculating a cosine similarity COS value and a root mean square error RMSE value of each piece of adjacent station data and the target station data, and selecting a station with a high COS value and a small RMSE value as an experiment reference station; fitting a spatial correlation curved surface by using a moving curved surface fitting algorithm, andpredicting daily average temperature data of the target station to obtain a predicted value; analyzing results in combination with evaluation indexes, wherein the evaluation indexes include a root-mean-square error, an average absolute error and a Nash coefficient; and comparing the predicted value with the observed value, if the difference value meets the condition, considering that the data passes the inspection, and if the difference value does not meet the condition, considering that the data is suspicious, and marking the suspicious data. And the accuracy, stability and adaptability of the algorithm are effectively improved.

Description

technical field [0001] The invention relates to the technical field of surface air temperature quality control algorithms, in particular to a surface air temperature quality control method based on cosine similarity and moving surface fitting. Background technique [0002] In the context of global informatization. Numerical weather prediction has become a necessary means of weather forecasting that affects economic development and social progress. Scholars at home and abroad have conducted in-depth research on numerical weather prediction through a large number of observation experiments and numerical simulations. Research shows that data assimilation technology is the premise to ensure the accuracy of numerical weather prediction. The quality control of meteorological data is a necessary part of assimilation. In recent years. Scholars at home and abroad have conducted extensive research on algorithms for quality control of meteorological observation data. From the stud...

Claims

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Application Information

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IPC IPC(8): G06F30/20G06F17/18G06Q50/26G06K9/62G06F119/08
CPCG06F17/18G06Q50/26G06F18/22
Inventor 叶小岭姚锦松吕于荣巩灿灿金瞳宇
Owner NANJING UNIV OF INFORMATION SCI & TECH
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