Swells of the East China Sea

Over the past few decades, an increasing number of marine activities have been conducted in the East China Sea, including the construction of various marine structures and the passage of large ships. Marine safety issues are paramount and are becoming more important with respect to the likely increase in size of ocean waves in relation to global climate change and associated typhoons. In addition, swells also can be very dangerous because they induce the resonance of floating structures, including ships. This study focuses on an investigation of swells in the East China Sea and uses hindcast data for waves over the past 5 years in a numerical model, WAVEWATCH III (WW3), together with historical climate data. The numerical calculation domain covers the entire North West Pacific. Next, swells are separated and analyzed using simulated wave fields, and both the characteristics and generation mechanisms of swells are investigated.     

The basement geology of Japan from A to Z

The Precambrian and lower Paleozoic units of the Japanese basement such as the Hida Oki and South Kitakami terranes have geological affinities with the eastern Asia continent and particularly strong correlation with units of the South China block. There are also indications from units such as the Hitachi metamorphics of the Abukuma terrane and blocks in the Maizuru terrane that some material may have been derived from the North China block. In addition to magmatism, the Japanese region has seen substantial growth due to tectonic accretion. The accreted units dominantly consist of mudstone and sandstone derived from the continental margin with lesser amounts of basaltic rocks associated with siliceous deep ocean sediments and local limestone. Two main phases of accretionary activity and related metamorphism are recorded in the Jurassic Mino–Tanba–Ashio, Chichibu, and North Kitakami terranes and in the Cretaceous to Neogene Shimanto and Sanbagawa terranes. Other accreted material includes ophiolitic sequences, e.g. the Yakuno ophiolite of the Maizuru terrane, the Oeyama ophiolite of the Sangun terrane, and the Hayachine–Miyamori ophiolite of the South Kitakami terrane, and limestone‐capped ocean plateaus such as the Akiyoshi terrane. The ophiolitic units are likely derived from arc and back‐arc basin settings. There has been no continental collision in Japan, meaning the oceanic subduction record is more complete than in convergent orogens seen in intracontinental settings making this a good place to study the geological record of accretion. Hokkaido lacks most of the Paleozoic history recognized in Honshu, Shikoku, Kyushu, and the Ryukyu Islands to the south and its geology reflects the Cenozoic development of two convergent domains with volcanic arcs, their approach, and eventual collision. The Hidaka terrane reveals a cross section through a volcanic arc and the main accretionary complex of the convergent system is represented by the Sorachi–Yezo terrane.     

Bayesian tsunami fragility modeling considering input data uncertainty

Empirical tsunami fragility curves are developed based on a Bayesian framework by accounting for uncertainty of input tsunami hazard data in a systematic and comprehensive manner. Three fragility modeling approaches, i.e. lognormal method, binomial logistic method, and multinomial logistic method, are considered, and are applied to extensive tsunami damage data for the 2011 Tohoku earthquake. A unique aspect of this study is that uncertainty of tsunami inundation data (i.e. input hazard data in fragility modeling) is quantified by comparing two tsunami inundation/run-up datasets (one by the Ministry of Land, Infrastructure, and Transportation of the Japanese Government and the other by the Tohoku Tsunami Joint Survey group) and is then propagated through Bayesian statistical methods to assess the effects on the tsunami fragility models. The systematic implementation of the data and methods facilitates the quantitative comparison of tsunami fragility models under different assumptions. Such comparison shows that the binomial logistic method with un-binned data is preferred among the considered models; nevertheless, further investigations related to multinomial logistic regression with un-binned data are required. Finally, the developed tsunami fragility functions are integrated with building damage-loss models to investigate the influences of different tsunami fragility curves on tsunami loss estimation. Numerical results indicate that the uncertainty of input tsunami data is not negligible (coefficient of variation of 0.25) and that neglecting the input data uncertainty leads to overestimation of the model uncertainty.