Derivation of Z-R relationship parameter for Alor Setar radar using Traditional Matching Method (TMM)

• Published in: IOP conference series. Earth and environmental science Vol. 646; no. 1; p. 12043
• Main Authors: Mahyun, A W, Chua, Kar-Kei, Salwa, M.Z.M, Seman, Noramirah Abu, Hassan, Zulkarnain, Kamarudzaman, Ain Nihla
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.01.2021
• Subjects: Bias; Correlation coefficient; Correlation coefficients; Empirical analysis; Matching; Meteorological radar; Parameters; Radar; Rain; Rain gauges; Rainfall; Rainfall measurement; Rainfall rate; Reflectance; Root-mean-square errors; Weather; Malaysia
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/646/1/012043

Abstract The rainfall measurement can be done by using rain gauge and weather radar instruments. However, weather radar does not measure the rainfall depth directly as contrary to rain gauge. Therefore, an empirical relationship between reflectivity (Z) and rainfall rate (R) which is commonly known as reflectivity-rainfall (Z-R) relationship consisting of parameter A and exponential b ( Z= A·R b ), usually used to convert reflectivity data into rainfall rate for a radar. Presently, the Z-R relationship parameters proposed by Marshall and Palmer (1947) used in Malaysia is seem no longer suitable for Malaysia condition. Hence, a new relationship should be developed. The reflectivity data from year 2006 to year 2007 at Alor Setar radar and gauge rainfall data from 14 rain gauge in the Northern of Peninsular Malaysia were calibrated. By using the Traditional Matching Method (TMM), a new parameter was developed for Alor Setar radar which located in Northern Peninsular Malaysia. By minimizing the errors, a Mean Field Bias Correction (MFB) technique was apply to all selected parameter in this study with adjusting the value A and fixed the value b. As a results, new climatological Z-R relationship ( Z =14.30 R 1.9 ) was obtained. To justify the new relationship, validation analysis has been performed by using the five statistical measure. It was found that the validation analysis has given the best results of Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Bias and Pearson Correlation Coefficient (r) with value of 0.00, 0.00, 7.54, 1.00 and 0.85 respectively. Concluded that, it is suitable for radar rainfall estimation in the Northern Region of Peninsular Malaysia.