A data assimilation-oriented radial velocity quality control method for weather radar

Abstract

The invention discloses a data assimilation-oriented radial velocity quality control method for weather radar. The method is based on a double weight algorithm, and the options of scientific research and business are set in the parameter list, and the requirements of intuitive operation and efficient execution in scientific research work are met by setting the quality control threshold independently, and the business work is realized through recursive quality control. The effect is stable and there is no need for human interference. This method reasonably eliminates the data with large observation errors, removes the small-scale change data that cannot be resolved by the model resolution and the data that is difficult to simulate, and ensures that the probability density function of the actual observation value minus the background field simulation value is close to the Gaussian distribution, which improves the analysis efficiency. The accuracy of the field is beneficial to the subsequent radar data assimilation. This method fully considers the actual needs of data assimilation in numerical weather prediction, and combines the conventional process of numerical weather prediction, and is directly integrated into the numerical weather prediction model, which has the advantages of simplicity, quick execution, and convenient maintenance.

Description

technical field [0001] The invention relates to weather radar data quality control, in particular to a data assimilation-oriented weather radar radial velocity quality control method. Background technique [0002] Doppler weather radar has high sensitivity, stable and reliable software and hardware, and has the ability of unattended automatic observation around the clock. It is an important equipment for monitoring small and medium-scale disastrous weather systems. Doppler weather radar can provide three basic data of radial velocity, reflectivity factor and spectral width with high temporal and spatial resolution. Among them, the radial velocity can accurately provide the detailed information of the wind field of the weather system, and has played an important role in the early warning of disastrous weather for a long time, and is an indispensable data for short-term nowcasting. At the same time, with the continuous improvement of my country's new generation of weather rad...

AI Technical Summary

Problems solved by technology

However, the dual-weight algorithm is only initially applied in the quality control and assimilation of GPS data, ground observation data, and satellite ozone data. There is no precedent for applying it to the quality control and assimilation of radar radial velocity data. The difficulty lies in How to solve the problem of space-time matching between radar data and model background field data, how to reasonably coordinate scientific research needs and business needs, and how to organically integrate with conventional processes to adapt to high-frequency radar data assimilation

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