Accuracy of cumulonimbus cloud prediction using Rapidly Developing Cumulus Area (RDCA) products at Pattimura Ambon airport

Abstract

Extreme weather conditions caused by cumulonimbus (Cb) clouds are closely related to the world of aviation, which is the main mode of transportation in Indonesia. Thus, the delivery of information regarding Cb predictions needs to be optimized to support flight safety and minimize the impact that can be caused. The RDCA product from the Himawari satellite can be a solution for predicting cumulus clouds that have the potential to become Cb within the next 1 hour. How accurate is the prediction of the RDCA, is considered important to be carried out in its application in the Ambon Pattimura airport area. This study focuses on the spatial and statistical analysis of categorical scores from dichotomous verification using weather radar data and surface observations, which were also verified using several parameters. Based on analysis in July and December 2021, RDCA verification results using weather radar aligned with surface observation data show that RDCA has a high accuracy value in predicting Cb in the next 10-60 minutes. Meanwhile, the results of research with several parameters have a proficient level of accuracy, although in certain cases, there are still quite a lot of false alarms and misses, indicating that the RDCA point cannot predict perfectly. The results of this research have led to progress in the development of techniques or ways to obtain the accuracy of RDCA products. The results of the accuracy of the application of RDCA can be used as a basis for nowcasting considerations as well as practical use from an operational perspective in aviation. In addition to using surface data or observations as one of the verification considerations, this paper is a initial step in assessing the accuracy of RDCA products in the tropics, especially in Ambon.