Estimation of Three-Dimensional Temperature in the Northern East China Sea Using an Ensemble Model Based on Artificial Neural Networks

초록

This study used an artificial neural network model to predict the three-dimensional temperature field by capturing the non-linear relationships between input and target data. Unlike most previous studies, which focused on open ocean regions, this research develops a model specifically designed to address the unique characteristics of the coastal areas in the Northern East China Sea. Vertical temperature profiles observed from 2000 to 2022 were used as target data, while input data representing temperature structures or forcing temperature variations were utilized for training the artificial neural network model. The optimized artificial neural network model achieved a root mean square error of 1.1°C on the test dataset. Therefore, the artificial neural network model established in this study is expected to be effectively applied to predict the three-dimensional temperature fields in the coastal seas. © 2024 Ocean and Polar Research.

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