Joint Center of data assimilation research and applications, school of atmospheric science,Nanjing University of Information Science & technology
With the construction of about 70,000 automatic weather stations across China, comprehensively automatic meteorological observation has been realized. However, the real application of this kind of observations always surfers from their low quality. Large number of error data seriously affect the practical application of observation. Therefore, it is a particularly important work to repair those abnormal observations. Using a total of 168 times of hourly surface temperature observations of automatic weather station during December 1-7, 2019 provided by Jiangsu meteorological bureau, a restoration method based on the Empirical Orthogonal Function method is proposed. The accuracy analysis of the ideal restoration experiments shows that the new restoration method can well repair the wrong observations, and the error of the restoration method is about 0.48 ℃. The methods based on Cressman interpolation, which rely on single point observation information, are more vulnerable to small-scale signal interference and introduce unnatural observation information, and the surface temperature repair error can reach 1.55 ℃. The analysis of the actual repair results also proves that the new repair method makes full use of the time-space separation and modal orthogonality of EOF analysis method, and gradually eliminates the influence of wrong data through iterative method, so as to obtain better space-time continuity repair results with the surrounding observation data.