## 4 Conclusions  
The challenges in the real-time interactive visualization of large-volume heterogeneous scalar datasets in a web environment have motivated our design and implementation of the WebGPU-based volume rendering framework for an interactive visualization of large-scale ocean scalar data. The framework proposed in this study first applies the ray casting algorithm, optimized with early ray termination and adaptive sampling methods, as the core algorithm for volume rendering. Next, by completing the initialization of the volume rendering viewer and building vertex and fragment shaders with the Babylon.js 3D rendering engine and the latest WebGPU technology, the framework successfully achieves efficient three-dimensional volume rendering of massive gridded data, which are preprocessed through steps including format conversion, data interpolation, and volume texture generation from complex regular and irregular gridded ocean numerical modeling datasets. It also integrates interactive visual analysis functionalities, including volume cutting, value-based spatial data filtering, and time-series animation playback, supporting visualization with different configurations of parameters. Finally, the WebGPU-based  
Figure 7: Performance comparison of volume rendering of the temperature and acoustic propagation loss data between the WebGPU and WebGL versions based on Babylon.js: (**a**) frame rate comparison; (**b**) GPU utilization comparison. framework is compared to our previous work and an additionally developed WebGL-based version. The experimental results show that the proposed framework performs well in displaying structures and details of ocean scalar data, and it can provide high-quality visual effects while enabling smooth real-time rendering. Although this framework is designed for the visualization of ocean data, we believe that the framework can be easily customized to visualize other scientific data or integrated into different visualization scenarios with some modifications. Its extensibility, along with the technical solutions accumulated from our previous work, also allows for easy-to-implement integration with the visualization of other data types, such as seabed terrain or real-time sensor data. The findings further highlight WebGPU's advantages in visualization tasks requiring high real-time performance and interactivity. In conclusion, visualization solutions based on WebGPU are expected to contribute to the advancement of data visualization and become valuable technical tools in future visualization studies of oceanography, environmental monitoring, and other related research fields. To enable a more comprehensive and insightful analysis of ocean data, future research will focus on incorporating a dynamic three-dimensional visualization of ocean vector fields into this framework and developing more interactive visual analysis tools to enhance intelligent analysis capabilities, as well as further build WebVR applications based on the existing work to provide more intuitive ocean data visualization and presentation. Additionally, WebGPU still faces some challenges, such as the steep learning curve for new developers and a relatively small number of available tools. As it is still in the stage of continuous development, issues related to instability and compatibility across different browsers and browser versions remain challenging. To address these problems, we will pay close attention to the development of WebGPU and continuously upgrade and improve our framework to enhance its stability and reliability while continuing to optimize it in conjunction with other new network technologies, such as WebAssembly. Conceptualization, J.Y. and R.Q. ; methodology, J.Y. ; software, J.Y. ; validation, J.Y. ; data curation, Z.X. ; writing--original draft preparation, J.Y. ; writing--review and editing, J.Y. and R.Q. ; supervision, R.Q. and Z.X. ; project administration, R.Q. ; funding acquisition, R.Q. All authors have read and agreed to the published version of the manuscript.