Visual analysis is well adopted within the field of oceanography for the analysis of model simulations, detection of different phenomena and events, and tracking of dynamic processes. With increasing data sizes and the availability of multivariate dynamic data, there is a growing need for scalable and extensible tools for visualization and interactive exploration. We describe pyParaOcean, a visualization system that supports several tasks routinely used in the visual analysis of ocean data. The system is available as a plugin to Paraview and is hence able to leverage its distributed computing capabilities and its rich set of generic analysis and visualization functionalities. pyParaOcean provides modules to support different visual analysis tasks specific to ocean data, such as eddy identification and salinity movement tracking. These modules are available as Paraview filters and this seamless integration results in a system that is easy to install and use. A case study on the Bay of Bengal illustrates the utility of the system for the study of ocean phenomena and processes.

翻译：可视化分析在海洋学领域被广泛应用于模型模拟分析、不同现象与事件检测以及动态过程追踪。随着数据规模的增长和多变量动态数据的普及，对可扩展且可扩展的可视化与交互式探索工具的需求日益迫切。本文介绍了pyParaOcean可视化系统，该系统支持海洋数据可视化分析中常规使用的多项任务。该系统作为Paraview的插件运行，因此能够利用其分布式计算能力及丰富的通用分析与可视化功能。pyParaOcean提供专门针对海洋数据的不同可视化分析任务模块，例如涡旋识别和盐度运动追踪。这些模块以Paraview过滤器形式提供，这种无缝集成使得系统易于安装和使用。以孟加拉湾为例的案例研究展示了该系统在海洋现象与过程研究中的实用性。