Year: 2025
Type: article
Abstract: In order to further enhance the numerical application of weather radar radial velocity, this paper proposes a quality control scheme for weather radar radial velocity from the perspective of data assimilation. The proposed scheme is based on the WRFDA (Weather Research and Forecasting Data Assimilation) system and utilizes the biweight algorithm to perform quality control on weather radar radial velocity data. A series of quality control tests conducted over the course of one month demonstrate that the scheme can be seamlessly integrated into the data assimilation process. The scheme is characterized by its simplicity, fast implementation, and ease of maintenance. By determining an appropriate threshold for quality control, the percentage of outliers identified by the scheme remains highly stable over time. Moreover, the mean errors and standard deviations of the O-B (observation-minus-background) values are significantly reduced, improving the overall data quality. The main information and spatial distribution features of the data are preserved effectively. After quality control, the distribution of the O-B Probability Density Function is adjusted in a manner that brings it closer to a Gaussian distribution. This adjustment is beneficial for the subsequent data assimilation process, contributing to more accurate numerical weather predictions. Thus, the proposed quality control scheme provides a valuable tool for improving weather radar data quality and enhancing numerical forecasting performance.
Authors: Yin Liu, Mingyue Su, Hong Zhao, Minjie Xia
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: diamond
Award: G7577136607
OpenAlex ID: W4411570270