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Analysis of Extreme Rainfall of Tropical Cyclone Using Solar Radiation Management and Era5 Data in Eastern Part of Indonesia

Modelling
Indonesia | Gernowo
Extreme weather, Precipitation

Summary

The study assesses extreme rainfall from Tropical Cyclones Seroja, Surigae and Rai in eastern Indonesia using ERA5 data and GeoMIP solar radiation management (SRM) simulations. SRM consistently reduces cyclone‑related rainfall, with GeoMIP producing much lower rainfall than ERA5, e.g., Seroja drops from 50 mm/day (ERA5) to 10–20 mm/day. Future projections show large rainfall increases under high‑emission scenarios (SSP5‑8.5), while SRM scenarios limit changes to 5–20%. Results suggest SRM may reduce flooding risk but could worsen water scarcity.

Abstract

The East Nusa Tenggara (NTT) and Papua provinces, located in eastern Indonesia, have recently experienced an increase in the frequency and intensity of tropical cyclones and extreme weather events. The impact of tropical cyclones in this region, particularly in terms of extreme rainfall, has raised concerns about the potential for severe flooding, landslides, and damage to infrastructure. This study aims to investigate the extreme rainfall due to tropical cyclones. We focus on three tropical cyclones (TC) that struck in eastern Indonesia, i.e., Seroja TC (April 2021), Surigae TC (April 2021), and Rai TC (December 2021). The extreme rainfall during TC was analyzed using the ERA5 model, with Bias correction from GeoMIP applied to enhance accuracy. The Solar Radiation Management (SRM) is used for comparative analysis and impact evaluation, assessing how each scenarios influence extreme rainfall during tropical cyclones by comparing GeoMIP model with ERA5 data. Our analysis using Solar Radiation Management (SRM) shows that the data from both sources correlate well and indicate a decrease in rainfall over eastern Indonesia during the tropical cyclone. Potential biases in the GeoMIP approach, such as the simplification of cloud-aerosol interactions and the assumptions underlying the SRM mechanism, may contribute to underestimating precipitation.

Publication data

Journal: Geographica Technica
Date: 04 March 2025
DOI: 10.21163/GT_2025.201.20

Authors

Sorja Koesuma

Sebelas Maret University, Indonesia

Akhmad Faqih

IPB University

Hendri Hendri

University of Papua

Rahmat Gernowo

Diponegoro University

Jassica Listyarini

Department of Geophysics and Meteorology, IPB University, Bogor

Delfina Azzahra Kusuma

Department of Oceanography, Diponegoro University, Semarang

Angger Zufan Hanggara

Department of Physics, Sebelas Maret University, Surakarta

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