用可视化工具指导水下滑翔机实时采集海洋数据，提升预报系统精度。
Data Visualization to Evaluate and Facilitate Targeted Data Acquisitions in Support of a Real-time Ocean Forecasting System
- 通过三组件软件实现滑翔机路径验证与预测，支持自适应采样。
- 评估路径可行性与信息价值，提供决策置信度等级。
- 基于Python开发，便于集成到现有海洋预报系统中使用。
为支持美国海军研究实验室的实时海洋预报系统RELO，设计了一套稳健的评估工具集，旨在促进自适应采样策略，并为水下滑翔机的航线规划提供更科学的指导。主要挑战在于将工具集成至现有业务系统，并在建模与操作环境之间建立桥梁。本研究采用可视化方法，开发的软件分为三个模块：第一模块验证滑翔机是否按预定航点航行，并预测下一周期的位置；第二模块确保下达航点既有效又可行；第三模块提供推荐路径的置信度水平。整个系统采用Python实现，具备良好的可移植性与模块化设计，便于未来新增可视化功能。该工具已成功嵌入实际运行流程，显著提升了数据采集的效率与预报系统的可靠性。
原文摘要 · Abstract (English)
A robust evaluation toolset has been designed for Naval Research Laboratory's Real-Time Ocean Forecasting System RELO with the purpose of facilitating an adaptive sampling strategy and providing more educated guidance for routing underwater gliders. The major challenges are to integrate into the existing operational system and provide a bridge between the modeling and operative environments. Visualization is the selected approach, and the developed software is divided into 3 packages. The first package verifies that the glider is actually following the waypoints and predicts the position of the glider for the next cycle's instructions. The second package ensures that the delivered waypoints are both useful and feasible. The third package provides the confidence levels for the suggested path. This software's implementation is in Python for portability and modularity to allow for easy expansion of new visuals.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。