Litcius/Paper detail

Extreme Wind Variability and Wind Map Development in Western Java, Indonesia

Muhammad Rais Abdillah, Prasanti Widyasih Sarli, Hafidz Rizky Firmansyah, Anjar Dimara Sakti, Faiz Rohman Fajary, Robi Muharsyah, Gian Gardian Sudarman

2022International Journal of Disaster Risk Science21 citationsDOIOpen Access PDF

Abstract

Abstract Wind-related disasters are one of the most frequent disasters in Indonesia. It can cause severe damages of residential construction, especially in the world’s most populated island of Java. Understanding the characteristics of extreme winds is crucial for mitigating the disasters and for defining structural design standards. This study investigated the spatiotemporal variations of extreme winds and pioneered a design wind map in Indonesia by focusing on western Java. Based on gust data observed in recent years from 24 stations, the extreme winds exhibit a clear annual cycle where northwestern and southeastern sides of western Java show out-of-phase relationship due to reversal monsoons. Meanwhile, extreme wind occurrences are mostly affected by small-scale weather systems, regardless of seasons and locations. To build the wind map, we used bias-corrected gust from ERA5 and applied the Gumbel method to predict extreme winds with different return periods. The wind map highlights some drawbacks of the current national design standards, which use single wind speed values regardless of location and return period. Beside a fundamental improvement for wind design, this study will benefit disaster risk mapping and other applications that require extreme wind speed distribution.

Topics & Concepts

Gumbel distributionReturn periodWind speedMeteorologyJavaEnvironmental scienceClimatologyExtreme weatherExtreme value theoryPrevailing windsWind powerGeographyClimate changeGeologyComputer scienceEngineeringOceanographyStatisticsProgramming languageFlood mythArchaeologyMathematicsElectrical engineeringMeteorological Phenomena and SimulationsTropical and Extratropical Cyclones ResearchClimate variability and models