Quality Control and Uncertainty Analysis of Return Radiosonde Data
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Abstract
Aiming at promoting the application of new types of sounding data in NWP (numerical weather prediction) models, this paper presents a basic research work of return radiosonde data. Based on archived return radiosonde observation datasets in China, a quality control scheme for future operational implementation purposes is established. By comparing and analyzing the statistical characteristics of observation samples before and after the quality control, the rationality of the quality control method is demonstrated. After the quality control procedure, the sampling distribution of the detection variables is more reasonable, and the inner-consistency of variables is also improved. An uncertainty analysis of return radiosonde data is then carried out by referring to the high-resolution NWP model forecast field and the conventional sounding observation data of the same site. The results show that the precision of return radiosonde reaches the breakthrough target defined by the WMO (world meteorological organization). Some detection variables even achieve the ideal target. Finally, the assimilability of the return radiosonde data is discussed based on the background field of the NWP model. The results show that wind field observations at all times and night temperature observations satisfy the Gaussian and unbiased assumptions of the variational assimilation system and can be assimilated directly. To play a more effective role in the data assimilation system, air pressure, humidity observations, and daily temperature need to be corrected before data assimilation. This work lays a foundation for the future assimilation application of return radiosonde.
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