Statistics Of Z-R Relationship For Strong Convective Weather Over Yangtze-Huaihe River Basin And Its Application In Radar Data Assimilation

The relationship between radar reflectivity factor Z and rainfall rate R is recounted based on radar observations from multiple Doppler radars and hourly rainfall measurements at multiple automatic weather stations over the Yangtze-Huaihe river basin collected by the National“973”project for severe convective weather.Subsequently,the Z-R relationship is combined with the empirical q_r-R relationship to correct the observation operator for radar reflectivity in the three-dimensional variational data assimilation system of the Weather Research and Forecasting model to improve the analysis and prediction for severe convective weather occurred over the Yangtze-Huaihe river basin.The performance of the corrected reflectivity operator used in WRF3DVar is tested with a heavy rain case and a squall line case occurred on 22-23 June 2013 and 14June 2009 over Jiangsu,Anhui provinces and their surrounding region,respectively,and it is noted that the observations on these cases are left out during the calculation process of Z-R relationship.The main conclusions are listed as follows:?1?Compared with the existing Z-R relationships(Z=300R^1.4 and Z=200R^1.6),the Z-R relationship(Z=109R^1.74)recalculated in this paper should be more suitable for strong convective weather occurred over the Yangtze-Huaihe river basin,as shown by the CTF values and test with two convective cases.?2?The screening of statistical samples has an important impact on the statistics of Z-R relationship.Even for the convective precipitation,the interference of weaker phases during severe weather processes reduces the reliability of Z-R statistics.Therefore,we rechoose samples to perform statistics of Z-R relationship,in which the proportion of reflectivity no less than 30dBZ?hereafter referred to as dBZ30?of single sample is simply used as a screening standard.?3?The observational operator for radar reflectivity is obtained by the Z-R relationship.Compared with two Z-qr relationships derived from the recounted Z-R relationship and used in WRF 3DVar,we can see that the new Z-qr relationship produces a larger qr than that used in WRF3DVar for a given Z less than 43.87 dBZ.However,it is opposite when Z is greater than 43.87dBZ.?4?The reflectivity data assimilation with the corrected observational operator can improve the quality of initial analyzed field,which indicates that the reasonable Z-R relationship play an important role in radar data assimilation.The corrected observation operator based on the recalculated Z-R relationship performed obviously better than the original used in WRF 3DVar.The patterns of dynamics,thermodynamics and water vapor are reasonable with the use of corrected observational operator,which is more conducive to the occurrence and development of convection.?5?The reflectivity data assimilation with the corrected observational operator can improve the prediction of radar composite reflectivity within the first 6 hours,especially for strong echoes?above 30 dBZ?.With the used of the corrected operator,the spatial structure and the location of forecasted composite reflectivity are more consistent with the observations.For this heavy rain case,the use of corrected reflectivity operator can extend the effective time of radar data assimilation for the prediction of strong reflectivity.The effective time is extended from 3.5 hours to 5.5 hours for the prediction of radar composite reflectivity for the 30-dBZ threshold.For the squall line case,the use of corrected reflectivity operator can obviously improve the prediction of strong reflectivity within 3-6 hours.