标题： 一种可扩展的海洋数据视觉分析系统 显示英文标题

标题： A Scalable System for Visual Analysis of Ocean Data

摘要： 海洋学家依赖视觉分析来解释模型模拟，识别事件和现象，并跟踪动态海洋过程。 由于海洋数据的动态特性和多变量关系，其分辨率和复杂性不断增加，这需要一种可扩展和适应性强的可视化工具来进行交互式探索。 我们介绍了pyParaOcean，这是一个专门为海洋数据分析设计的可扩展和交互式可视化系统。 pyParaOcean提供了用于常见海洋学分析任务的专业模块，包括涡旋识别和盐度运动跟踪。 这些模块与ParaView作为过滤器无缝集成，确保用户友好且易于使用的系统，同时利用ParaView的并行化能力和大量内置的通用可视化功能。 创建一个存储为Cinema数据库的辅助数据集有助于解决I/O和网络带宽瓶颈问题，同时支持快速概览可视化生成。 我们展示了一个关于孟加拉湾（BoB）的案例研究，以展示该系统的实用性，并进行了缩放研究以评估系统的效率。 显示英文摘要

摘要： Oceanographers rely on visual analysis to interpret model simulations, identify events and phenomena, and track dynamic ocean processes. The ever increasing resolution and complexity of ocean data due to its dynamic nature and multivariate relationships demands a scalable and adaptable visualization tool for interactive exploration. We introduce pyParaOcean, a scalable and interactive visualization system designed specifically for ocean data analysis. pyParaOcean offers specialized modules for common oceanographic analysis tasks, including eddy identification and salinity movement tracking. These modules seamlessly integrate with ParaView as filters, ensuring a user-friendly and easy-to-use system while leveraging the parallelization capabilities of ParaView and a plethora of inbuilt general-purpose visualization functionalities. The creation of an auxiliary dataset stored as a Cinema database helps address I/O and network bandwidth bottlenecks while supporting the generation of quick overview visualizations. We present a case study on the Bay of Bengal (BoB) to demonstrate the utility of the system and scaling studies to evaluate the efficiency of the system.