Assessment of high-resolution regional ocean reanalysis K-ORA22 for the Northwest Pacific

The Korea Institute of Ocean Science and Technology developed the Korea Operational Oceanographic System-Ocean Predictability Experiment for Marine Environment (KOOS-OPEM), a high-resolution (1/24°, 51 vertical levels) ocean prediction model for the Northwest Pacific Ocean that incorporates ensemble optimal interpolation. In this study, we present KOOS-OPEM ReAnalysis version 2022 (K-ORA22), which covers the period from 2011 to 2022. We conducted a comparative analysis between K-ORA22 and other high-resolution (1/10°–1/12°) global reanalyses, including the Hybrid Coordinate Ocean Model, Global Ocean Reanalysis and Simulation (GLORYS), and Bluelink ReAnalysis (BRAN), to demonstrate the reproducibility and reliability of regional characteristics. Statistical comparisons revealed that while K-ORA22 exhibited some warm biases, its sea surface temperature (SST) anomaly correlation after removing the seasonal cycle was approximately 0.87, comparable to other reanalyses. Additionally, K-ORA22 effectively reproduced coastal upwelling, which is characterized by a sharp decrease in SST, as observed by marine meteorological buoys in the Southwest of the East/Japan Sea. K-ORA22 exhibits a warm bias of approximately 0.50 °C around 200 m, slightly higher than those of GLORYS and BRAN, while maintaining a low salinity bias in the subsurface. Notably, K-ORA22 outperformed the other reanalyses in accurately reproducing the unique characteristics of North Pacific and East Sea intermediate waters, characterized by a salinity minimum layer. In addition, K-ORA22 stands out in its ability to accurately reproduce the Yellow Sea Cold Water Mass with a low-temperature root-mean-square error (RMSE) of 0.76 °C in the Yellow Sea (YS) region. However, it exhibited the highest RMSE for salinity in the YS region and Korea/Tsushima Strait, indicating a potential overestimation of river discharge from Korea and China. While the sea surface height (SSH) anomaly correlation of K-ORA22 did not surpass 0.80 in the entire region because of limitations in the background error covariance used, its ability to reproduce the Kuroshio path was comparable to those of other reanalysis datasets. In conclusion, K-ORA22 excels in reproducing the unique characteristics of Korean marginal seas. Still, it exhibits weaknesses, such as the overestimation of river discharge and a somewhat limited ability to simulate SSH variability, compared with other global reanalyses. We plan to enhance K-ORA22 by updating background error covariance, addressing biases related to river discharge and assimilating the best available in situ observations and satellite data.