Open AccessDerivation of Z-R relationship parameter for Alor Setar radar using Traditional Matching Method (TMM)
Author(s) -
A. W. Mahyun,
Kar-Kei Chua,
Mohd Zaini Makhtar Salwa,
Noramirah Abu Seman,
Zulkarnain Hassan,
Ain Nihla Kamarudzaman
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/646/1/012043
Subject(s) - radar , rain gauge , setar , mean squared error , statistics , reflectivity , rain rate , mathematics , correlation coefficient , gauge (firearms) , measure (data warehouse) , meteorology , remote sensing , environmental science , geography , computer science , physics , data mining , time series , optics , telecommunications , star model , archaeology , autoregressive integrated moving average
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.