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Research & review articles are invited for publication in September 2026 (Vol. 28, Issue 3) || Submission: up to 28th September || Editorial decision: within 48 hrs.

Tropical convective cloud growth models for hydrometeorological disaster mitigation in Indonesia

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  • Tropical convective cloud growth models for hydrometeorological disaster mitigation in Indonesia

Rahmat Gernowo 1, * and Dwi Purwantoro Sasongko 2

1 Department of Physic Faculty of Mathematics and Natural Sciences, Diponegoro University, Semarang, Indonesia.
2 Environmental Expert, Center for Environmental Research, Diponegoro University, Semarang, Indonesia.
 
Research Article
Global Journal of Engineering and Technology Advances, 2021, 06(02), 114-120.
Article DOI: 10.30574/gjeta.2021.6.2.0022
DOI url: https://doi.org/10.30574/gjeta.2021.6.2.0022
Received on 11 January 2021; revised on 10 February 2021; accepted on 12 February 2021
Heavy rain in Semarang on 1 January 2020 caused flooding. The existence of heavy rain cannot be separated from the dynamics of weather parameters which are closely related to the convection process and cloud formation. In this paper research has been conducted using Weather Research and Forecasting (WRF), to analyze the growth patterns of convective clouds as an effort to mitigate the initial events of extreme rainfall disasters. Several weather parameters that support cloud growth are very significant, namely the parameter values ​​that support the convection process to form convective clouds (Cumulonimbus). The results of the model show that there has been extreme rainfall which can be used as initial mitigation of hydrometeorological disasters.
Heavy Rainfall; Flood Hazard; Cloud Growth; Global Model; Hydrometeorological disasters.
https://gjeta.com/sites/default/files/fulltext_pdf/GJETA-2021-0022.pdf

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Rahmat Gernowo and Dwi Purwantoro Sasongko. Tropical convective cloud growth models for hydrometeorological disaster mitigation in Indonesia. Global Journal of Engineering and Technology Advances, 2021, 6(2), 114-120. Article DOI: https://doi.org/10.30574/gjeta.2021.6.2.0022

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