Effect of prediction accuracy using three-dimensional reconstructed initial seawater temperature based on observed profiling data.

Coastal KOOS (MOHID), developed and operated by the Korea Institute of Ocean Science and Technology (KIOST), is an advanced three-dimensional ocean prediction system designed to simulate and forecast oceanic conditions along the coast of the Korean Peninsula. The system incorporates meteorological factors to predict key ocean parameters, including Sea Surface Temperature (SST). Despite its capability to reproduce SST relatively well, differences occur in certain aspects of predictions. Specifically, while the system can closely match observed SST, errors in the timing, intensity, and duration of cold water events persist. These errors are primarily attributed to differences in how the model represents the vertical distribution of water temperatures. In particular, the model may not fully account for the interaction between cooler waters at deeper layers and surface conditions, affecting the onset, strength, and longevity of cold water events.

To reduce numerical error and improve the accuracy of cold water zone predictions, the study concentrated on enhancing the simulation of the vertical distribution of water temperature. The main objective was to determine how modifications to the initial seawater temperature profile would impact predictions of cold water zones. The initial conditions were reconstructed using quality-checked observational data collected during a cold water event along the southeastern coast of the East Sea of Korea between August 18 and September 4, 2021. This concentrated observational data provided high-resolution information on the vertical distribution of water temperature, enabling the model better to represent the temperature distribution throughout the water column.

By reconstructing the initial vertical distribution of water temperature, the result enhances the accuracy of predicting not only SST but also the timing, intensity, and duration of cold water events. This improvement would offer a more accurate and reliable forecast for the occurrence and behavior of cold water zones. The anticipated benefits of improved cold water zone predictions include better management of marine resources, such as fisheries, which are highly sensitive to temperature changes. Additionally, this improvement could support informed decision-making for coastal infrastructure, such as climate monitoring and environmental protection, particularly in changing weather patterns and evolving oceanic conditions.