Sea surface waves alter sea surface roughness and surface winds and influence the exchange of mass, momentum, and heat at the air-sea interface (Hwang, 2011). Huge waves under extreme wind conditions usually cause severe coastal and ship disasters, which have led to thousands of deaths and extensive property losses in the past two decades (Chang & Mori, 2021;Möller et al., 2008). Therefore, providing accurate wave height forecasts is necessary and urgent (Alves et al., 2013). However, significant bias still exist in numerical wave models (Campos et al., 2018(Campos et al., , 2019 due mainly to simplified physical processes, inaccurate initial conditions, and limited grid resolution (Cannon, 2018;Giorgi & Bi, 2000;Hack et al., 2006). Bias correction was proposed to mitigate the bias in numerical models to fit the observations better (Soriano et al., 2019). Bias correction techniques for results from numerical models include linear regression, quantile mapping, cumulative distribution functions, Kalman filter, and so on (
Tokyo Electric Power Company announced to discharge the contaminated radioactive water resulting from the Fukushima nuclear accident into the ocean after purification from 2023. Concerns remain about safety and removal efficiency of radionuclides. This study calculated the total radioactivity and simulated the marine transport of 137Cs, 90Sr, and tritium. It assessed activity concentration in ocean and marine products, lifetime doses from marine product consumption, and associated cancer risks. We found the radionuclides would be globally distributed and penetrate into deep ocean, with the highest concentrations along Japan's eastern coast. If 137Cs and 90Sr were not removed, related cancer risks would range between 8.64 - 33.35 cases per 100,000 people, depending on age and discharge scenario. Risks would be below one case per 100,000 if only tritium is present. Efficient removal of radionuclides is crucial to mitigating health risks. This study provides evidence of potential health risks and recommendations for prevention.
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