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Title: Risk-based versus storyline approaches for global warming impact assessment on basin-averaged extreme rainfall: a case study for Typhoon Hagibis in eastern Japan
Authors: Tanaka, Tomohiro  kyouindb  KAKEN_id  orcid (unconfirmed)
Kawase, Hiroaki
Imada, Yukiko
Kawai, Yuki
Watanabe, Satoshi
Author's alias: 田中, 智大
Keywords: pseudo global warming
Typhoon Hagibis
storyline approach
risk-based approach
Issue Date: 25-Apr-2023
Publisher: IOP Publishing
Journal title: Environmental Research Letters
Volume: 18
Issue: 5
Thesis number: 054010
Abstract: Two methods exist to address the degree to which past extreme events and associated disasters will be intensified due to climate change: storyline approaches and risk-based approaches. However, the risk-based approach applied to weather similar to the target event (typhoons, a stationary weather front, ...etc) becomes theoretically similar to the storyline approach. We examine this theory for the climate change impact of a real event, Typhoon Hagibis, which caused devastating flood damage to eastern Japan in 2019, while focusing on basin-averaged accumulated rainfall (BAAR) in major eastern river basins. A risk-based approach was conducted to determine the future change of BAAR by calculating the quantile change corresponding to Hagibis from the probability distribution of typhoon-induced events in a large ensemble climate simulation dataset database for Policy Decision-making for Future climate change (past, +2K and +4K future climates). A storyline approach for Typhoon Hagibis was realized using a pseudo global warming (PGW) experiment with a 5 km non-hydrostatic model. The projected BAAR in the two approaches were consistent for all target basins, supporting the robustness of the calculated changes in extreme catchment precipitation. This presents an important practical benefit: one can assess future climate change impact on a past symbolic event using either PGW experiments or large ensemble climate projections for the target weather.
Rights: © 2023 The Author(s). Published by IOP Publishing Ltd
Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
DOI(Published Version): 10.1088/1748-9326/accc24
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