Zhang A-si, Uang Chao-ying, Chen Shengo, Zhang Peng-fei, HU Dong-ming, Xiao Liu-si
{"title":"Utilization of Specific Attenuation for Rainfall Estimation in Southern China","authors":"Zhang A-si, Uang Chao-ying, Chen Shengo, Zhang Peng-fei, HU Dong-ming, Xiao Liu-si","doi":"10.46267/J.1006-8775.2021.005","DOIUrl":null,"url":null,"abstract":"This study uses rain gauge observations to assess the performance of different radar estimators R(ZH), R(KDP) and R(A) in estimating precipitation based on the observations of an S-band polarimetric radar over southern China during a typical convective storm and an extremely severe typhoon, i. e., Typhoon Manghkut. These radar estimators were derived from observations of a local autonomous particle size and velocity (Parsivel) unit (APU) disdrometer. A key parameter, alpha (α), which is the ratio of specific attenuation A to specific differential phase KDP with three fixed values (α=0.015 dB deg-1, α=0.0185 dB deg-1 and α=0.03 dB deg-1) was examined to test the sensitivity of the R(A) rain retrievals. The results show that: (1) All radar estimators can capture the spatio-temporal patterns of two precipitation events, R(A) with α=0.0185 dB deg-1 is well correlated with gauge measurement via higher Pearson's correlation coefficient (CC) of 0.87, lower relative bias (RB) of 16%, and lower root mean square error (RMSE) of 17.09 mm in the convective storm while it underestimates the typhoon event with RB of 35%; (2) R(A) with α=0.03 dB deg-1 shows the best statistical scores with the highest CC (0.92), lowest RB (7%) and RMSE (25.74mm) corresponding to Typhoon Manghkut; (3) R(A) estimates are more efficient in mitigating the impact of partial beam blockage. The results indicate that α is remarkably influenced by the variation of drop size distribution. Thus, more work is needed to establish an automated and optimized α for the R(A) relation during different rainfall events over different regions.","PeriodicalId":17432,"journal":{"name":"热带气象学报","volume":"3 1","pages":"48-61"},"PeriodicalIF":1.5000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"热带气象学报","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.46267/J.1006-8775.2021.005","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
This study uses rain gauge observations to assess the performance of different radar estimators R(ZH), R(KDP) and R(A) in estimating precipitation based on the observations of an S-band polarimetric radar over southern China during a typical convective storm and an extremely severe typhoon, i. e., Typhoon Manghkut. These radar estimators were derived from observations of a local autonomous particle size and velocity (Parsivel) unit (APU) disdrometer. A key parameter, alpha (α), which is the ratio of specific attenuation A to specific differential phase KDP with three fixed values (α=0.015 dB deg-1, α=0.0185 dB deg-1 and α=0.03 dB deg-1) was examined to test the sensitivity of the R(A) rain retrievals. The results show that: (1) All radar estimators can capture the spatio-temporal patterns of two precipitation events, R(A) with α=0.0185 dB deg-1 is well correlated with gauge measurement via higher Pearson's correlation coefficient (CC) of 0.87, lower relative bias (RB) of 16%, and lower root mean square error (RMSE) of 17.09 mm in the convective storm while it underestimates the typhoon event with RB of 35%; (2) R(A) with α=0.03 dB deg-1 shows the best statistical scores with the highest CC (0.92), lowest RB (7%) and RMSE (25.74mm) corresponding to Typhoon Manghkut; (3) R(A) estimates are more efficient in mitigating the impact of partial beam blockage. The results indicate that α is remarkably influenced by the variation of drop size distribution. Thus, more work is needed to establish an automated and optimized α for the R(A) relation during different rainfall events over different regions.
本研究利用雨量计观测资料,评估了不同雷达估计器R(ZH)、R(KDP)和R(A)在一次典型对流风暴和台风“山竹”期间对中国南方s波段极化雷达降水的估计性能。这些雷达估计来自于局部自主粒径和速度(Parsivel)单位(APU) disdrometer)的观测。为了检验R(A)雨反演的灵敏度,我们考察了一个关键参数alpha (α),即特定衰减A与特定差分相位KDP的比值,该比值具有三个固定值(α=0.015 dB deg-1、α=0.0185 dB deg-1和α=0.03 dB deg-1)。结果表明:(1)所有雷达估测器均能捕捉到两个降水事件的时空格局,其中α=0.0185 dB deg-1的R(A)与实测数据具有较好的相关性,对流风暴的Pearson相关系数(CC)为0.87,相对偏差(RB)为16%,均方根误差(RMSE)为17.09 mm,而低估了台风事件的RB为35%;(2) α=0.03 dB deg-1的R(A)表现出最高的CC(0.92)、最低的RB(7%)和RMSE (25.74mm);(3) R(A)估计在减轻部分波束阻塞的影响方面更有效。结果表明,α受液滴粒径分布的影响显著。因此,需要更多的工作来建立一个自动化和优化的α在不同地区不同降雨事件的R(A)关系。