Assessment of impact of data assimilation of the regional ocean wave model

Globally, 39% of the world's population lives within 100 km of the coast. Eight of the top ten largest cities in the world are located along the coast. In South Korea, 27% of the population also resides in coastal areas. Ocean waves, induced by sea winds, potentially endanger offshore infrastructure and threaten low-lying ecosystems and communities due to coastal erosion and flooding. More accurate prediction of ocean wave patterns, or sea states, is crucial for informed decision-making in mitigating these risks. Recently, many National Meteorological and Hydrological Services (NMHs) have been endeavoring to enhance the accuracy of ocean wave predictions by assimilating in-situ and remote sensing observations. The Korea Meteorological Administration (KMA) also initiated an ocean wave data assimilation system in 2021. However, this system has thus far only been adapted to a global-scale model. This study aims to install and evaluate the impact of ocean wave data assimilation on a regional scale. The regional ocean wave data assimilation system employs optimal interpolation based on WAVEWATCH-Ⅲ version 6.07 with a spatial resolution of 1/30° targeted for the East Asian region. Significant wave height data from five satellites in polar orbit, ocean data buoys, and coastal wave buoys were utilized. Numerical experiments for summer (2023JJA) and winter (2023/24DJF) reveal that the use of data assimilation reduced the root mean square error by 49.2% and 38.6%, respectively, for the initial fields of regional wave models. The assimilated initial fields improved ocean wave predictions by 12 hours in the KMA regional ocean wave model, which is consistent with previous research in the field. Particularly during Typhoon KHANUN in August 2023, there was a tendency to overestimate sea winds, which are input variables of the ocean wave model. Despite the use of overestimated sea winds, the regional ocean wave model utilizing data assimilation reduced the error by up to 94 cm.