## 4 Results and Discussion  
### Typhoon-Induced Temperature Anomaly and Model Validation  
This model reconstructs the impact of typhoons on ocean temperatures at various depths over the decade from 2011 to 2020. While Typhoon Lekima is used as a representative case study due to its distinct characteristics, the model was trained and validated using data from numerous typhoon events between 2011 and 2020, ensuring the robustness and generalizability of the findings. Specifically, 80% of the data was utilized for model training and 20% for validation, allowing for comprehensive evaluation across multiple years and regions. Figure 2 depicts the path of Typhoon Lekima from 7 August to 12 August 2019, along with its corresponding gale force wind radius. The background shows the ocean temperature distribution at a depth of 50 m, derived from the FCT model. The colors in the figure indicate different temperature levels: warm colors (such as orange and red) represent higher temperatures, while cool colors (such as blue) denote lower temperatures. The color bar on the right clearly marks the temperature scale. The black solid line traces the typhoon's path, black circles represent the radius of gale force winds around the typhoon's center, and black dots indicate the typhoon's center at various times, with blue dots highlighting its position on specific days. As Typhoon Lekima moved from the western Pacific towards China's eastern coast, significant changes in the temperature distribution at a depth of 50 m were observed. The ocean temperature on the western side of the typhoon's path was higher, while the eastern side exhibited relatively lower temperatures. This pattern reflects the substantial influence of the typhoon's strong winds and precipitation on the ocean environment. The intense wind field not only sustained higher sea surface temperatures on the western side but also induced strong ocean mixing on the eastern side. In particular, the strong winds and heavy rainfall caused vertical disturbances, bringing cooler deep water to the surface and leading to a pronounced \"upwelling\" effect, resulting in a noticeable cold band [19]. The cooling effect along the typhoon's path was especially pronounced. As the typhoon advanced, the combination of strong winds and heavy precipitation caused significant mixing of the upper ocean layers, pulling cooler deep water to the surface. This led to a marked decrease in sea surface temperature along the typhoon's central path, forming what is known as a \"cold wake\" [20]. This cooling effect was driven not only by upwelling but also potentially by the typhoon's blocking of solar radiation and the dispersal of cooler water due to heavy rainfall, resulting in a distinct cold band along the typhoon's trajectory. After reconstructing the three-dimensional thermal structure of the ocean under the influence of a typhoon, we employed Argo observational data within the affected region to rigorously assess the accuracy of our predictions. Figure 3 displays the prediction errors of ocean temperatures at various depths during the typhoon event as modeled by the fully connected transformer network (FCT). This figure offers a detailed comparison of the variation trends of the mean absolute error (MAE) and root mean squared error (RMSE) with depth, providing critical insights into the model's performance. The blue bars represent the MAE values at each depth, while the orange line delineates the corresponding RMSE values. On average, the model exhibits an MAE of 0.8283 \({}^{\circ}\)C and an RMSE of 1.0338 \({}^{\circ}\)C, reflecting the overall predictive accuracy of the FCT model. Figure 2: Path of Typhoon Lekima and ocean temperature distribution at 50 m depth inferred from the FCT model.