Effects of open boundary bias correction and data assimilation in a regional ocean circulation model for the East Sea

Abstract

Boundary conditions are important constraints when solving partial differential equations to obtain solutions for the interior. Global ocean prediction models have supplied such boundary conditions for regional ocean models. However, the biases present in these global ocean models can significantly affect the accuracy of predictions within nested regional ocean models. In the present study, open boundary bias correction and data assimilation were applied using the observed temperature and salinity data. The bias correction was conducted at the upstream open boundary, the Korea Strait, while the data assimilation was performed in the interior, including Ulleung Basin in the southwestern East Sea, to reduce the prediction errors in the nested regional model. The effects of each correction method were quantified through four numerical experiments. In the Korea Strait and Ulleung Basin, root mean square errors (RMSEs) in temperature decreased by 44% in February using data assimilation compared to free run, while RMSEs in salinity decreased by 31% in August using bias correction. Bias correction of open boundary data enhanced the simulation performance in salinity near the open boundary; however, it did not lead to improvements in temperature distribution within the interior. Conversely, data assimilation improved temperature distribution within the interior; however, salinity bias persisted near the open boundary. Notably, the combined use of the two correction methods resulted in a lower RMSE in temperature in the Ulleung Basin during winter, and a lower RMSE in salinity in the Korea Strait and Ulleung Basin during the summer. Hence, the simultaneous use of open boundary bias correction and data assimilation is expected to improve the interior solution of salinity and temperature in various other regional ocean models.