| Since the first batch of national automatic weather stations officially put into run in January 1,2000 in China,there are more than 30000 automatic weather stations that greatly increase the time density of the surface meteorological observation data and improve the precision and quality of the data. However, the existing ground meteorological observation business still exists deficiencies. In this paper,missing measure rate,error rate,compared difference rate,the root mean square,standard error and consistence rate of the double automatic weather stations of data are compared,and the data processing algorithm is based on sliding variance of space consistency,this paper is divided in four chapters to introduce:The first chapter gives a brief overview of the purpose and significance of the topicthen we introduce the research situation of the problem about Date Evaluation and Data Fusion of the Double Automatic Weather Stations at home and abroad. Finally,we elaborate the research content about thesis and the main research results.In chapter 2,the temperature observation date by Xiuning station from Oct.2010 to Fed.2011 is used to calculate missing measure rate,error rate, compared difference rate,the root mean square,standard error and consistence rate of temperature. On temperature,compared difference rate,the root mean square,standard error and consistence rate of mean day temperature and mean monthly temperature are counted and made correlation analysis.In chapter 3,a data processing algorithm based on space consistency and sliding variance is proposed,and the temperature data by hours of Anhui's Xiuning station,Anhui Province from Oct.2010 to Feb.2011 are used to validate the algorithm. The results show that the validity discrimination of the data base;and that the result of data fusion based on sliding variance is close to the "truth-value",thus reflecting the basic situation of the atmosphere.Chapter 4 gives the summary for the full thesis and has a corresponding discussion. |
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