| dc.description.abstract | To reduce the impact of hydrometerological disasters, a research is needed in estimating rainfall. Weather radar is a type of remote sensing used in the field of meteorology to determine atmospheric conditions, measure rainfall, and others. However, the accuracy of weather radar products related to rainfall estimation needs to be evaluated. The type of rain is also a factor that greatly affects the accuracy of rainfall estimation. This study aims to determine the accuracy of weather radar products in estimating rainfall in North Sumatra, namely standard products (CAPPI 0.5 km, PPI 0.5o and CMAX) and the best Z-R relations (Marshall-Palmer and Rosenfeld Tropical) on convective and stratiform rain. This research begins by classifying the observed rainfall data based on the type of rain. Then, rainfall observation data every 10 minutes is processed and accumulated into hourly data. The radar-estimated rainfall raw data is processed and generated using the Rainbow application. The raw data that has been processed is then converted using ASCII to obtain data in the form of numbers. Furthermore, the radar estimated rainfall data is compared with rainfall observation data. Comparisons are made from each weather radar product and Z-R relation. In analyzing and making decisions, verification tests are carried out using correlation, mean absolute error (MAE), and mean error (ME). The results showed that the CMAX product is quite good at estimating stratiform rainfall in the North Sumatra region with a correlation value of 0.499. As for convective rainfall, the CAPPI product is a good enough product in estimating rainfall with a correlation value of 0.369. In addition, the error value of the CMAX product is 1.867 and CAPPI is 10.360 which is the smallest error value in all AWS/ARG locations in the North Sumatra region. As for the Z-R relation, the Marshall-Palmer equation is best used for stratiform rain with a correlation value of 0.419 and 0.295 in convective rain. | en_US |
