Space-time permutation statistics application to detect cloud-to-ground lightning prone area (Case study: Pasuruan, Indonesia)

Karisma, Ria Dhea Layla Nur ORCID: https://orcid.org/0000-0002-5941-9565 and Hamidah, Rohmatul (2023) Space-time permutation statistics application to detect cloud-to-ground lightning prone area (Case study: Pasuruan, Indonesia). ITM Web of Conferences, 61. ISSN 2271-2097

Preview

Text 18038.pdf - Published Version Available under License Creative Commons Attribution. Download (836kB) | Preview

Abstract

Lightning is a natural phenomenon caused by the release of positive and negative charges occur in cumulonimbus (CB) clouds. CG lightning is a lightning that strikes from the clouds to the ground. This lightning is dangerous for human activities which can cause burns, blindness, and even temporary deafness. This research will determine the areas prone to CG lightning strikes and lightning characteristics in the city of Pasuruan. Space-time permutation scan statistics is a method used to detect prone areas by considering spatial and temporal aspects. This method merely requires case data, such as location and time without using population data. The detected prone areas will be tested for significance using Monte Carlo. It is used to determine the distribution of the sample. In this study, the Monte Carlo test for scanning window is 0,048 (p-value < 0,05), Sekargadung. Thus, making Sekargadung a hotspot for lightning-prone areas. Furthermore, the value is taken based on the highest ratio test (LRT), 11,46, which is the most likely cluster. Based on space-time permutation statistics Sekargadung is the main hotspot prone area in this case study. It has 226 strikes with the intensity of their occurrence with characteristics area dominant paddy field.

Item Type:	Journal Article
Keywords:	Space-time permutatio scan; likelihood ratio test; hazardous areas; cloud-to-fround; lightning prone area
Subjects:	01 MATHEMATICAL SCIENCES > 0104 Statistics > 010401 Applied Statistics
Divisions:	Faculty of Mathematics and Sciences > Department of Mathematics
Depositing User:	Miss Ria Dhea Layla Nur Karisma
Date Deposited:	23 Jan 2024 11:06

Downloads

Origin of downloads

Actions (login required)

View Item