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Big data visual analytics for exploratory earth system simulation analysis

机译:大数据可视化分析,用于探索性地球系统仿真分析

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Rapid increases in high performance computing are feeding the development of larger and more complex data sets in climate research, which sets the stage for so-called "big data" analysis challenges. However, conventional climate analysis techniques are inadequate in dealing with the complexities of today's data. In this paper, we describe and demonstrate a visual analytics system, called the Exploratory Data analysis ENvironment (EDEN), with specific application to the analysis of complex earth system simulation data sets. EDEN represents the type of interactive visual analysis tools that are necessary to transform data into insight, thereby improving critical comprehension of earth system processes. In addition to providing an overview of EDEN, we describe real-world studies using both point ensembles and global Community Land Model Version 4 (CLM4) simulations.
机译:高性能计算的快速增长为气候研究中更大,更复杂的数据集的发展提供了动力,这为所谓的“大数据”分析挑战奠定了基础。但是,传统的气候分析技术不足以处理当今数据的复杂性。在本文中,我们描述并演示了一种称为探索性数据分析环境(EDEN)的可视化分析系统,该系统专门用于复杂地球系统仿真数据集的分析。 EDEN代表了交互式视觉分析工具的类型,它是将数据转换为洞察力,从而提高对地球系统过程的关键理解的必要条件。除了提供EDEN概述外,我们还使用点集和全球社区土地模型第4版(CLM4)模拟来描述现实世界的研究。

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