Advances in weather and climate extreme studies: a systematic comparative review
There is a growing evidence-based concerns pointing to global increase of weather and climate extreme events (WCEE). What decides whether these hazards become a disaster is how the society and humanity prepare and responds to it. Although various researchers have step up efforts through scholarly co...
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2024
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my.upm.eprints.1159782025-03-17T05:23:58Z http://psasir.upm.edu.my/id/eprint/115978/ Advances in weather and climate extreme studies: a systematic comparative review Muhammad Kafi, Kamil Ponrahono, Zakiah There is a growing evidence-based concerns pointing to global increase of weather and climate extreme events (WCEE). What decides whether these hazards become a disaster is how the society and humanity prepare and responds to it. Although various researchers have step up efforts through scholarly contributions in response to WCEE. However, the task of utilizing the needed tools, selecting the most suitable approach, and choosing appropriate techniques for WCEE studies can be daunting for researchers. Moreover, the technicality and complexity associated with the wide array of models and methods present additional challenges when it comes to their practical implementation in disaster applications. This review comprehensively explores four approaches in WCEE studies: statistical analysis, geospatial modeling, MCDA, and AI-based techniques. It evaluates their effectiveness in assessing impacts within WCEE and highlights AI’s (ML and DL’s) superior performance compared to other conventional methods in disaster-related studies. Springer 2024-10-02 Article PeerReviewed text en cc_by_nc_nd_4 http://psasir.upm.edu.my/id/eprint/115978/1/115978.pdf Muhammad Kafi, Kamil and Ponrahono, Zakiah (2024) Advances in weather and climate extreme studies: a systematic comparative review. Discover Geoscience, 2 (1). art. no. 66. pp. 1-26. ISSN 2948-1589 https://link.springer.com/article/10.1007/s44288-024-00079-1?error=cookies_not_supported&code=32b43794-5982-4f4b-a538-fa53e3130c72 10.1007/s44288-024-00079-1 |
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There is a growing evidence-based concerns pointing to global increase of weather and climate extreme events (WCEE). What decides whether these hazards become a disaster is how the society and humanity prepare and responds to it. Although various researchers have step up efforts through scholarly contributions in response to WCEE. However, the task of utilizing the needed tools, selecting the most suitable approach, and choosing appropriate techniques for WCEE studies can be daunting for researchers. Moreover, the technicality and complexity associated with the wide array of models and methods present additional challenges when it comes to their practical implementation in disaster applications. This review comprehensively explores four approaches in WCEE studies: statistical analysis, geospatial modeling, MCDA, and AI-based techniques. It evaluates their effectiveness in assessing impacts within WCEE and highlights AI’s (ML and DL’s) superior performance compared to other conventional methods in disaster-related studies. |
format |
Article |
author |
Muhammad Kafi, Kamil Ponrahono, Zakiah |
spellingShingle |
Muhammad Kafi, Kamil Ponrahono, Zakiah Advances in weather and climate extreme studies: a systematic comparative review |
author_facet |
Muhammad Kafi, Kamil Ponrahono, Zakiah |
author_sort |
Muhammad Kafi, Kamil |
title |
Advances in weather and climate extreme studies: a systematic comparative review |
title_short |
Advances in weather and climate extreme studies: a systematic comparative review |
title_full |
Advances in weather and climate extreme studies: a systematic comparative review |
title_fullStr |
Advances in weather and climate extreme studies: a systematic comparative review |
title_full_unstemmed |
Advances in weather and climate extreme studies: a systematic comparative review |
title_sort |
advances in weather and climate extreme studies: a systematic comparative review |
publisher |
Springer |
publishDate |
2024 |
url |
http://psasir.upm.edu.my/id/eprint/115978/1/115978.pdf http://psasir.upm.edu.my/id/eprint/115978/ https://link.springer.com/article/10.1007/s44288-024-00079-1?error=cookies_not_supported&code=32b43794-5982-4f4b-a538-fa53e3130c72 |
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13.251813 |