Big data visual analytics for exploratory earth system simulation analysis

doi:10.1016/j.cageo.2013.07.025

2013-12-01

PRE

DOI：10.1016/j.cageo.2013.07.025

原文链接

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摘要

En 中文

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. (C) 2013 Elsevier Ltd. All rights reserved.

Keyword:

Visualization

Parallel coordinates

Climate

Sensitivity analysis

Data intensive computing

Data mining

Statistical visualization

Multivariate

Big data

AI总结

对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Computers and Geosciences

IF:

4.4

论文数:

5.0K

被引数:

1.5W

机构

united states department of energy (doe)

学者数:

11.3W

论文数: 9.6W

被引数: 246

oak ridge national laboratory

学者数:

1.5W

论文数: 1.0W

被引数: 20

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