VISIBILITY PREDICTION EVALUATION FOR AIR TRANSPORTATION SAFETY IN INDONESIA (CASE STUDY : KERTAJATI AIRPORT)

• Main Author: Salsabila Sahda, Faiza
• Format: Final Project
• Language: Indonesia
• Subjects: Geologi, hidrologi & meteorologi
• Online Access: https://digilib.itb.ac.id/gdl/view/75655
• Institution: Institut Teknologi Bandung

Low visibility condition often occurs on Indonesia, including on Kertajati region. Kertajati Airport is an international airport located in Majalengka, West Java. The location is close to the Ciremai Mountains, one of the highest mountains in West Java. This topographic condition makes Kertajati prone to fog, especially during the rainy season. Based on January 2022 METAR data, the Kertajati area has significant visibility changes due to fog. So there is a need for further visibility predictions. In this study, visibility prediction was performed using Weather Research and Forcasting (WRF). The output of WRF will be estimated visibility with diagnostic equations. Then, this study will evaluate visibility predictions on two low visibility condition events, January 2, 2022 and January 21, 2022 with a minimum visibility value of 200 meters. There are 7 methods used to predict visibility in January 2022 in the Kertajati region. The data used in this study are prediction data from the NCEP-GFS and observation data from METAR. The 7 methods used in estimating visibility in Kertajati are categorized in 3 groups, those are the Vis RH-based parameterization with 4 diagnostic equations, Vis LWC-based parameterization with 2 diagnostic equations, and other parameterizations with one diagnostic equation. The results of this study indicate that during the low visibility event of the two events, the Relative Humidity (RH) based method tends to have a large visibility difference with observations. This happens because the RH variable used in the estimation equation is not well simulated by WRF. This can be seen from the temperature depression value in the model is higher so that RH tends to be lower and have good visibility. For the method used, at times the model with low visibility tends to overestimate the result (parameterisation Vis RH-based) and inclined underestimate (parameterization Vis LWC-based and other parameterization). The best method in diurnal low visibility events 1 and 2 is the Vis based RH_2 method, which has a smaller RMSE of 2824.87 meters and 3537.76 meters.