Abstract
Predictions of accurate heavy rain are needed in building a flood early warning system. One of the most commonly used weather parameter modeling models is the Weather Research Forecasting, but the results of the WRF model prediction have deficiencies inaccuracy so that data assimilation needs to be done to improve accuracy. This research aims to determine the effect of radar data assimilation by applying RUC using WRF 3DVAR to improve the predictions of heavy rain events in the Jabodetabek area with cases representing each of the four seasons, on February 20, 2017, April 3, 2017, June 13, 2017, and November 09, 2017. The data used for this research are synoptic observation data, GSMaP, GFS, Radar data, in the form of Z CAPPI products. In general, WRF radar data assimilation with RUC shows better spatial and point values. This can be seen in the spatial rainfall distribution on February 20th, 2017, June 13th, 2017, and November 09th, 2017 analysis on Climatology Station of PondokBetung, as well as the analysis of rain dichotomy, shows WRF assimilation using RUC with a TS value increased by 9%, PC value increased by 10%, and FAR value fixed by 18%.
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More From: IOP Conference Series: Earth and Environmental Science
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