Open AccessA preliminary results of assessment of BMKG-WRF numerical model daily rainfall forecasts performance using categorical verification
Author(s) -
Fatkhuroyan,
Alfan Sukmana Praja,
Trinah Wati
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/284/1/012013
Subject(s) - weather research and forecasting model , categorical variable , meteorology , environmental science , climatology , quantitative precipitation forecast , numerical weather prediction , downscaling , forecast skill , statistics , mathematics , geography , precipitation , geology
Indonesia Agency for Meteorology, Climatology and Geophysics (BMKG) has been using WRF (Weather and Research Forecasting) numerical weather model in forecasting daily rainfall accumulation. The method used to compare the daily rainfall accumulation of WRF forecast results (one to three days forecast) to rain-gauge observation data from 153 meteorological stations from March 2016 to December 2017 by using categorical verification techniques. The results show that the values of Frequency Bias Index (FBI), Proportion Correct (PC), Probability of Detection (POD), False Alarm ratio (FAR), and Threat Score (TS) for one-day forecast and three-day forecast in 2016 are mostly lower than 2017. Meanwhile, for 2-days forecast in 2016 generally lower than 2017 except PC and FAR. Molucca-Papua have the highest value of PC (0.63) for one-day forecast while Kalimantan have the highest values of PC (0.67, 0.68) for 2 and 3 days ahead forecast. In contrary, Sumatera have the lowest PC value (0.55) for one-day forecast while Bali-Nusa Tenggara have the lowest PC value (0.58, 0.59) for 2 and 3 days ahead forecast, respectively. It can be concluded that the performance of BMKG WRF quite accurate in forecasting daily rainfall up to three days ahead.