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All Journal JFA (Jurnal Fisika dan Aplikasinya)
Al Habib, Abdul Hamid
Indonesia Agency for Meteorology Climatology and Geophysics
Physics

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WRF-ARW Numerical Model Sensitivity Test on Simulation of Loud Rain in The South Kalimantan Area Al Habib, Abdul Hamid; Firdiyanto, Resa Agna
Jurnal Fisika dan Aplikasinya Vol 19, No 3 (2023)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat, LPPM-ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24604682.v19i3.17421

Abstract

On January 13-14, 2021, there was heavy rain in the South Kalimantan region, causing more than 10,000 houses and the main provincial road to be flooded, and also 2 main bridges collapsed. Based on observations at the Syamsudin Noor Meteorological Station Banjarmasin, the rainfall values on January 13 and 14 2021 were 51 mm and 249 mm, respectively. Meanwhile, at the Banjarbaru Climatology Station, it was recorded on January 13-14, 2021, at 45.9 mm and 255.3 mm, respectively. The amount of rainfall recorded at the Banjarmasin Meteorological Station and Banjarbaru Climatology Station makes this condition interesting to study. This simulation uses FNL data with temporal and spatial resolution of 3 hours and 1°×1°, respectively. In this study, the downscaling stage was carried out 2 times with domain 1 of 16 km and domain 2 of 6 km. Furthermore, the input data is running by testing as many as 9 parameterization schemes. Based on the results of the WRF rainfall output with the microphysics scheme (Kessler), the PBL scheme (Yonsei University Scheme) and the cumulus scheme (Kain-Fritcsh) showed the best value and the smallest error value compared to the other 8 schemes. Based on the CAPE value and air humidity, it proves that the atmospheric conditions are unstable and there is significant growth of convective clouds in the South Kalimantan region. The results of the stremaline analysis also show the presence of strong wind bends that result in the accumulation of air masses and indications of orographic rain in the west of the Meratus Mountains.
Ensemble Physics of the Weather Research and Forecasting (WRF) Model for Predicting Heavy Rainfall in the Bandung area, West Java Al Habib, Abdul Hamid; Ramadhani, Fathan Ilham; Trilaksono, Nurjanna J.
Jurnal Fisika dan Aplikasinya Vol 21, No 1 (2025)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat, LPPM-ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24604682.v21i1.20986

Abstract

The complex topography of the Bandung region, with the presence of mountains and valleys, can affect air flow patterns and rainfall distribution. Accurate weather predictions and spatial precision are crucial for anticipating the impacts of heavy rainfall. This study aims to evaluate the capability of the WRF physics ensemble prediction system in forecasting heavy rainfall events in the Bandung region. The use of an ensemble prediction system is a viable approach to quantifying uncertainty in numerical weather prediction and provide more reliable information. The case study used is the heavy rainfall event that caused flooding on October 4, 2022, in the Pagarsih area. Global Forecasting System (GFS) data with a spatial resolution of 0.25 x 0.25 and a temporal resolution of three hours were used as input for downscaling in the WRF-ARW model. This study used 9 configuration schemes of the WRF-ARW model parameterization as ensemble members. The results of the study indicate that the WRF model (a combination of the Purdue Lin, Yonsei University Scheme, and Betts-Miller-Janjic Scheme) provided the most accurate heavy rainfall prediction, with an RMSE value of 2.13. The probability maps of rainfall products can effectively identify peak heavy rainfall between 1:00 PM- 4:00 PM. This is indicated by the large area with a greater than 90% probability of rainfall exceeding 10 mm. The ensemble mean product of rainfall predictions tends to underestimate heavy rainfall in the Pagarsih area. The ensemble mean product of surface air temperature can effectively identify the pattern of observational f luctuations with a low RMSE value (0.77), and the ensemble mean product of surface layer air humidity can identify the pattern of observational fluctuations with a relatively high RMSE value (13.28).
Co-Authors Firdiyanto, Resa Agna Ramadhani, Fathan Ilham Trilaksono, Nurjanna J.