Future changes in extreme storm surge based on a maximum potential storm surge model for East Asia

We analyzed tropical cyclones (TC) based on the theory of Maximum Potential Intensity (MPI) and Maximum Potential Surge (MPS) for a long-term assessment of extreme TC intensity and storm surge heights. We investigated future changes in the MPI fields and MPS for different global warming levels based on 150-year continuous scenario projections (HighResMIP) and large ensemble climate projections (d4PDF/d2PDF). Focusing on the Western North Pacific Ocean (WNP), we analyzed future changes in the MPI and found that it reached a maximum in the latitudinal range of 30–40°N in September. We also analyzed future changes in the MPS in major bays of East Asia and along the Pacific coast of Japan. Future changes in the MPS were projected, and it was confirmed that changes in the MPS are larger in bays where large storm surge events have occurred in the past

Spatio-temporal wave climate using nested numerical wave modeling in the northern Indian Ocean

In order to simulate the wave climate in a specific region for different purposes such as climate change impact assessment, wave energy assessment, etc., it is important to consider the long-term variations (Shimura et al., 2015). Due to the scarcity of the wave measurements, numerically modeled wave data are an appropriate alternative to provide the wave characteristics in desired spatial and temporal coverage. There are limited studies which investigated the wave climate in the northern Indian Ocean. Amrutha et al. (2016) studied the wave climate in the eastern Arabian Sea at the west of India by comparison of the results of a nested numerical modeling with buoy data. Kamranzad et al. (2016) also assessed the temporal-spatial variation of wave energy and nearshore hotspots in northern Gulf of Oman based on the locally generated wind waves. In this study, wave modeling performance is investigated in the northern Indian Ocean (NIO) considering long distance swells. A nested wave modeling was utilized in the NIO to discuss the accuracy of wave simulation both temporally (by comparing to buoy dataset) and spatially (by comparing to the satellite altimeter records in the domain). High temporal resolution is important to consider the peak events for extreme value analysis, while the accurate estimation of spatial distribution is important for long-term variation of average wave climate in a domain

Impact Assessment of Storm Surge and Climate Change-Enhanced Sea Level Rise on Atoll Nations: A Case Study of the Tarawa Atoll, Kiribati

The Pacific region consists of numerous Small Island Developing States (SIDS), one of the most vulnerable to flooding caused by compound effects of sea level rise (SLR) and storms. Nevertheless, individual studies regarding the impact assessment for SIDS, such as the low-lying Kiribati, remain scarce. This study assessed the impact of climate change-induced storm surge and SLR compounding effects on Tarawa, the most populous atoll of Kiribati, the largest coral atoll nation. It projected the impact using a combined dynamic surge and SLR model based on the IPCC AR5 RCP scenarios and 1/100 and 1/50 years return period storm events. This approach allows estimating the inundation scope and the consecutive exposed population by the end of the 21st century. The results of this study show that the pace of SLR is pivotal for Tarawa, as the sea level rise alone can claim more than 50% of the territory and pose a threat to over 60% of the population under the most intense greenhouse gas emissions scenario. Furthermore, most coasts on the lagoon side are particularly vulnerable. In contrast, the contribution of extreme events is generally minimal due to low wind speeds and the absence of tropical cyclones (TC). Despite this, it is clear the compound effects are critical and may inescapably bring drastic changes to the atoll nations by the end of this century. The impact assessment in this study draws attention to the social impact of climate change on SIDS, most notably atoll islands, and evaluates their adaptation potential

Multi-scale Simulation of Subsequent Tsunami Waves in Japan Excited by Air Pressure Waves Due to the 2022 Tonga Volcanic Eruption

The 2022 Hunga Tonga-Hunga Ha’apai eruption generated tsunamis that propagated across the Pacific Ocean. Along the coast of Japan, nearshore amplification led to amplitudes of nearly 1 m at some locations, with varying peak tsunami occurrence times. The leading tsunami wave can generally be reproduced by Lamb waves, which are a type of air-pressure wave generated by an eruption. However, subsequent tsunamis that occurred several hours after the leading wave tended to be larger for unknown reasons. This study performs multi-scale numerical simulations to investigate subsequent tsunami waves in the vicinity of Japan induced by air pressure waves caused by the eruption. The atmospheric pressure field was created using a dispersion relation of atmospheric gravity wave and tuned by physical parameters based on observational records. The tsunami simulations used the adaptive mesh refinement method, incorporating detailed bathymetry and topography to solve the tsunami at various spatial scales. The simulations effectively reproduced the tsunami waveforms observed at numerous coastal locations, and results indicate that the factors contributing to the maximum tsunami amplitude differ by region. In particular, bay resonance plays a major role in determining the maximum amplitude at many sites along the east coast of Japan. However, large tsunami amplification at some west coast locations was not replicated, probably because it was caused by amplification during oceanic wave propagation rather than meteorological factors. These findings enhance our understanding of meteotsunami complexity and help distinguish tsunami amplification factors

Impacts of ocean wave‐dependent momentum flux on global ocean climate

Accurate knowledge of air‐sea fluxes of momentum, heat, and carbon are central to fully understanding the evolution of the climate system. The role of ocean surface waves has been largely overlooked in global climate models despite the growing body of work elucidating the influence of ocean wave state on air‐sea fluxes. Here we account for the impact of ocean surface waves on global ocean climate using a global ocean model through implementation of wave‐dependent momentum fluxes. Wave‐dependent momentum fluxes improve the simulation of observed ocean heat content (OHC) through increasing the trend in OHC over the last three decades. Specifically, the larger increase in OHC is attributable to increased net heat flux in the Southern Hemisphere (SH). These results highlight the important role of accounting for wave‐dependent momentum transfer in terms of both simulating future climate and understanding changes over the recent historical period

Robustness and uncertainties in global multivariate wind-wave climate projections

Understanding climate-driven impacts on the multivariate global wind-wave climate is paramount to effective offshore/coastal climate adaptation planning. However, the use of single-method ensembles and variations arising from different methodologies has resulted in unquantified uncertainty amongst existing global wave climate projections. Here, assessing the first coherent, community-driven, multi-method ensemble of global wave climate projections, we demonstrate widespread ocean regions with robust changes in annual mean significant wave height and mean wave period of 5–15% and shifts in mean wave direction of 5–15°, under a high-emission scenario. Approximately 50% of the world’s coastline is at risk from wave climate change, with ~40% revealing robust changes in at least two variables. Furthermore, we find that uncertainty in current projections is dominated by climate model-driven uncertainty, and that single-method modelling studies are unable to capture up to ~50% of the total associated uncertainty

Storm surges and extreme sea levels: Review, establishment of model intercomparison and coordination of surge climate projection efforts (SurgeMIP).

Coastal flood damage is primarily the result of extreme sea levels. Climate change is expected to drive an increase in these extremes. While proper estimation of changes in storm surges is essential to estimate changes in extreme sea levels, there remains low confidence in future trends of surge contribution to extreme sea levels. Alerting local populations of imminent extreme sea levels is also critical to protecting coastal populations. Both predicting and projecting extreme sea levels require reliable numerical prediction systems. The SurgeMIP (surge model intercomparison) community has been established to tackle such challenges. Efforts to intercompare storm surge prediction systems and coordinate the community's prediction and projection efforts are introduced. An overview of past and recent advances in storm surge science such as physical processes to consider and the recent development of global forecasting systems are briefly introduced. Selected historical events and drivers behind fast increasing service and knowledge requirements for emergency response to adaptation considerations are also discussed. The community's initial plans and recent progress are introduced. These include the establishment of an intercomparison project, the identification of research and development gaps, and the introduction of efforts to coordinate projections that span multiple climate scenarios

気候変動に伴う波浪変化の長期予測と気候因子解析

京都大学0048新制・課程博士博士(工学)甲第18931号工博第3973号新制||工||1612(附属図書館)31882京都大学大学院工学研究科社会基盤工学専攻(主査)教授 間瀬 肇, 教授 平石 哲也, 准教授 森 信人学位規則第4条第1項該当Doctor of Philosophy (Engineering)Kyoto UniversityDFA