IMPACT OF RADAR DATA ASSIMILATION ON THE ACCURACY OF HEAVY RAIN EVENTS PREDICTION IN BANGKA ISLAND

• Main Author: Setiawan, Nur
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/47203
• Institution: Institut Teknologi Bandung

Improvement of model initial condition by radar data assimilation is considered reliable to improve prediction accuracy. This study aims to determine the impact of radar data assimilation on WRF models in predicting heavy rainfall on Bangka Island. Case study were carried out on 5 (five) cases of heavy rain on flood events during 2015-2018. The Weather Research Forecasting (WRF) numerical model is run without assimilation and with assimilation of radar data. Radar data assimilation model is run in two ways: a single radar assimilation method with a radar point in Pangkalpinang and multiple radar assimilations with two radar points in Pangkalpinang and Palembang. The reflectivity value and rainfall distribution of model output are then verified qualitatively and quantitatively correspond to observation. The result shows that using assimilation on both single and multiple radar reflectivity data increase rainfall prediction skills in three cases (60%) with wide cloud coverage.. It also shows lack of improvement in rainfall events with little cloud coverage. Both model skills improvement is shown in Kelapa with hourly data on February 7th, 2016 with increasing value of ACC, TS, PoD and FAR. Nevertheless, general interpretation based on five case studies conducted by the model prediction result with radar data assimilation shows the method is reliable to improve the model output result.