Weather radar radial velocity quality control method for data assimilation

Abstract

The invention discloses a weather radar radial velocity quality control method for data assimilation. The method is based on a double weight algorithm, scientific research and business options are setin a parameter list, the requirements of direct operation and efficient execution in scientific research work are met in an autonomous quality control threshold setting mode, and the requirements ofstable effects and no human interference in business are met in a recursion quality control mode. The method reasonably rejects data with larger observation errors, removes small-scale variable data which cannot be resolved by the mode resolution and data difficult to simulate, guarantees that a probability density function for subtracting a background field simulation value from an actual observed value approaches Gaussian distribution, improves the accuracy of an analysis field and facilitates following radar data assimilation. The method takes actual requirement of data assimilation in numerical weather prediction into full consideration, is directly integrated into a numerical weather prediction mode in combination with a conventional process of the numerical weather prediction and hasthe advantages of being convenient, easy to implement, rapid in execution, convenient to maintain and the like.

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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