## 3 Results and Discussion
### Visual Effects of Volume Rendering  
This section examines the visual effects of the proposed WebGPU-based volume rendering framework, with the first experiment comparing the visualization results across various rendering configurations. Figure 3 illustrates the volume rendering results of the temperature and flow velocity magnitude data structured in regular grids. Similarly, Figure 4 illustrates the volume rendering results of the ocean acoustic field structured in irregular grids. As demonstrated in this experiment, the framework can effectively present the complex three-dimensional structures of various volume datasets and enable an insightful visual exploration of large-scale ocean scalar data. By adjusting and optimizing the rendering parameters, the framework can achieve ideal visual effects, accurately revealing the internal features of ocean scalar fields. Figure 3a illustrates the gradual decrease in temperature of the water mass with increasing depth, indicating that surface seawater has a higher temperature than the water at deeper levels in the modeling computational domain. Figure 3b shows the spatial arrangement of regions with different flow velocity magnitudes, depicting the flow characteristics of the water mass at different locations. Meanwhile, as illustrated in Figure 4, the propagation attenuation pattern of the acoustic field in a complex marine environment is effectively demonstrated, and a clear representation of the spatial distribution of acoustic wave energy is provided. By comparing Figures 3a and 4a with Figures 3b and 4b, it is evident that the internal spatiotemporal distribution characteristics of the water masses can be more clearly observed by changing the transparency parameter, which is inversely related to the opacity of each data point, in combination with an appropriate colorbar, while the display of details can be controlled by modifying the sampling step size. The experimental results indicate that the proposed framework can provide  
Figure 4: Volume rendering results of irregular gridded data: **(a)** the visualization of the complete acoustic propagation loss data with a transparency value of 0 and a basic sampling step size of 0.1; **(b)** the visualization of the same data with a transparency value of 0.3 and a basic sampling step size of 0.3. Figure 3: Volume rendering results of regular gridded data: **(a)** the visualization of the complete temperature data with a transparency value of 0 and a basic sampling step size of 0.2; **(b)** the visualization of the complete flow velocity magnitude data with a transparency value of 0.1 and a basic sampling step size of 0.4.  
both a clear and accurate data representation while delivering high-quality visual effects, offering a comprehensive web-based visualization solution. Additionally, we conducted an experiment on the developed interactive visual analysis tools to demonstrate their capacities. Figure 5 illustrates the results of the interactive visual analysis of the ocean scalar data. Figure 5a,b show the volume rendering results of the flow velocity magnitude data, cut along a single direction with vertical and horizontal cutting planes using the volume cutting tool, respectively. Figure 5c further demonstrates the multidirectional cutting capability of this tool, enabling a multifaceted spatial exploration of the acoustic propagation loss data. Unlike traditional slicing methods, the proposed functionality allows for the observation of both the profile and the preserved data block, enabling users to intuitively identify and analyze valuable information on the cutting plane as well as within the data block. Figure 5d presents the volume data within the ROI, filtered with a user-specified value range using the value-based spatial data filtering tool, highlighting the acoustic propagation loss data that users aim to visualize. This tool can effectively isolate the desired feature, enabling a better understanding of the ocean environmental phenomena of interest.