Rainfall Reflectivity Relationship For Rainfall Nowcasting In Northern Region Of Peninsular Malaysia - Wahab, Mahyun Ab (2017)
Short term rainfall forecasting is one of the most crucial forecasting tasks in meteorology. The success of rainfall forecasting depend upon many factors such as, experience of forecaster, the capability of radar hardware and the parameter conversion between reflectivity (Z) and rainfall rate (R), called the Z-R relationship (Z=ARb). Using the optimization technique, new Z-R relationship parameter for Alor Star Radar was derived. Sensitivity analysis was conducted to ease the calibration process. Calibration and validation process were performed between rainfall radar and gauge data to get the best parameter of A and exponential b. Short term rainfall forecasting was conducted using cross correlation technique to find the speed and direction of rainfall. Then, persistence forecast using linear extrapolation applied to forecast the next storm with the assumption there are no growth and decay of rainfall. The new Z-R relationship parameter for Alor Star Radar was determined to be Z = 40R1.6. Four statistical analyses were performed and it was found that the Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R²) value within the acceptable statistical indicators with the values of 1.77, 2.19, 3.11, and 0.90 respectively. Short term rainfall forecasting shows an acceptable result for 10 and 30 minutes lead time according to Nash and Sutcliffe Coefficient of Efficiency with the value is 0.86 and 0.48 respectively. As a conclusion, persistence forecast is suitable to forecast short term rainfall while Z-R relationship parameter value is an important input to the successfulness of rainfall forecasting by radar.