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Journal of Meteorological Research

, Volume 32, Issue 4, pp 598–611 | Cite as

Statistics of the ZR Relationship for Strong Convective Weather over the Yangtze–Huaihe River Basin and Its Application to Radar Reflectivity Data Assimilation for a Heavy Rain Event

  • Xue Fang
  • Aimei Shao
  • Xinjian Yue
  • Weicheng Liu
Article
  • 32 Downloads

Abstract

The relationship between the radar reflectivity factor (Z) and the rainfall rate (R) is recalculated based on radar observations from 10 Doppler radars and hourly rainfall measurements at 6529 automatic weather stations over the Yangtze–Huaihe River basin. The data were collected by the National 973 Project from June to July 2013 for severe convective weather events. The ZR relationship is combined with an empirical qrR relationship to obtain a new Zqr relationship, which is then used to correct the observational operator for radar reflectivity in the three-dimensional variational (3DVar) data assimilation system of the Weather Research and Forecasting (WRF) model to improve the analysis and prediction of severe convective weather over the Yangtze–Huaihe River basin. The performance of the corrected reflectivity operator used in the WRF 3DVar data assimilation system is tested with a heavy rain event that occurred over Jiangsu and Anhui provinces and the surrounding regions on 23 June 2013. It is noted that the observations for this event are not included in the calculation of the Z–R relationship. Three experiments are conducted with the WRF model and its 3DVar system, including a control run without the assimilation of reflectivity data and two assimilation experiments with the original and corrected reflectivity operators. The experimental results show that the assimilation of radar reflectivity data has a positive impact on the rainfall forecast within a few hours with either the original or corrected reflectivity operators, but the corrected reflectivity operator achieves a better performance on the rainfall forecast than the original operator. The corrected reflectivity operator extends the effective time of radar data assimilation for the prediction of strong reflectivity. The physical variables analyzed with the corrected reflectivity operator present more reasonable mesoscale structures than those obtained with the original reflectivity operator. This suggests that the new statistical ZR relationship is more suitable for predicting severe convective weather over the Yangtze–Huaihe River basin than the ZR relationships currently in use.

Key words

ZR relationship Weather Research and Forecasting (WRF) model three-dimensional variational (3DVar) system data assimilation observation operator 

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Notes

Acknowledgments

All the observational data used in this work were provided by the National (Key) Basic Research and Development (973) Program of China (2013CB430102). The NCEP-FNL datasets are available from https://rda.ucar.edu/datasets/ds083.2/

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Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Xue Fang
    • 1
  • Aimei Shao
    • 1
  • Xinjian Yue
    • 1
  • Weicheng Liu
    • 2
  1. 1.Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric SciencesLanzhou UniversityLanzhouChina
  2. 2.Lanzhou Central Meteorological ObservatoryLanzhouChina

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