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International Journal of Climatology
Article . 2023 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Future projections of extreme rainfall events in Indonesia

Authors: Ari Kurniadi; Evan Weller; Jennifer Salmond; Edvin Aldrian;

Future projections of extreme rainfall events in Indonesia

Abstract

AbstractPrevious evaluations of coupled climate models have indicated that under the influence of global warming precipitation extremes, including those over Indonesia, are expected to intensify. Here, we examine the most recent future projections of extreme rainfall in Indonesia using 24 global climate models from the Coupled Model Intercomparison Project Phase 6, consisting of 11 low resolution (LR) and 13 medium resolution (MR) models. The performance of these models is evaluated against Climate Hazards Group InfraRed Precipitation with Station data observations and realistically reproduce Indonesia's mean climatology over the period assessed (1987–2014). Overall, both LR and MR multi‐model ensemble means (MMEM) outperform individual models. Interestingly, extreme rainfall projections vary across different seasons, time periods, spatial resolutions and climate change scenarios. The LR and MR MMEMs project a continuous increase in wet extremes (R95p and Rx5d) during the wet season across most of Indonesia over the 21st century. Conversely, dry extremes (consecutive dry days [CDD]) are projected to increase (decrease) over the south (north) during the wet season but increase countrywide during the dry season. We show that future extreme wet and dry events are projected to be more frequent and intense, with upper extreme values surpassing historical records. The MR models project smaller changes in extreme wet indices than the LR models but simulate a more prolonged extreme dry index. Key findings here indicate that forthcoming instances of extreme rainfall present substantial hazards, necessitating the implementation of adequate preventative measures by policymakers, particularly within densely inhabited regions, such as Java.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Top 10%
Top 10%
hybrid