Convective Clouds Classification Based on Weather Forecast for Air Traffic Flow Management in Kualanamu Airport
1.Sunardi, 2.Syahrul Humaidi, 3. Marhaposan Situmorang, 4.Marzuki Sinambela.

Department of Physics - Faculty of Mathematics and Natural Sciences, Universitas Sumatera Utara, Medan, Indonesia
Politeknik Penerbangan Palembang, Sumatera Selatan, Indonesia

Abstract

Weather conditions are important information in flight. Extreme weather such as heavy rain, strong winds, and fog can disrupt flight activities, ranging from delays to plane crashes. This study aims to classify and predict extreme weather events at Kualanamu Airport as information for determining Air Traffic Flow Management (ATFM). ATFM is an air traffic management system that is oriented towards optimizing resources, which aims to improve safety, ensure smooth operation, deal with limitations, and harmonize flight operations and traffic. This research was conducted using the Weather Research and Forecasting (WRF) numerical model, Himawari 8 satellite imagery, and observation data from the Kualanamu Meteorological Station on a case study of heavy rain events on 17 January 2021. The results showed that the WRF model was able to predict extreme weather events so that they could be anticipated earlier by the airline traffic operator (Air Traffic Controller). The cloud growth observed in the Himawari 8 satellite image adds information to the location of extreme weather events in the short term.

Keywords: ATFM, weather forecasting, aviation safety

Topic: Artificial Intelligence and Data Science