A Web-Based Geovisual Analytical System for Climate Studies

Future Internet

Min Sun⁴  Jing Li⁴  Chaowei Yang⁴  Gavin A. Schmidt³  Myra Bambacus¹  Robert Cahalan¹  Qunying Huang⁴  Chen Xu⁴  Erik U. Noble² 

[1] NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA; E-Mails:;Center for Science and Technology Policy Research, University of Colorado Boulder, 1333 Grandview Avenue, Campus Box 488, Boulder, CO 80309, USA; E-Mail:;NASA Goddard Institute for Space Studies, and Center for Climate Systems Research, Columbia University, New York, NY 10025, USA; E-Mail:;Center of Intelligent Spatial Computing for Water/Energy Science, College of Science, George Mason University, 4400 University Drive, Fairfax, VA 22030, USA; E-Mails:

关键词: geospatial cyberinfrastructure;    big data;    spatiotemporal;    WebGIS;   

DOI  :  10.3390/fi4041069

来源: mdpi

【 摘 要 】

Climate studies involve petabytes of spatiotemporal datasets that are produced and archived at distributed computing resources. Scientists need an intuitive and convenient tool to explore the distributed spatiotemporal data. Geovisual analytical tools have the potential to provide such an intuitive and convenient method for scientists to access climate data, discover the relationships between various climate parameters, and communicate the results across different research communities. However, implementing a geovisual analytical tool for complex climate data in a distributed environment poses several challenges. This paper reports our research and development of a web-based geovisual analytical system to support the analysis of climate data generated by climate model. Using the ModelE developed by the NASA Goddard Institute for Space Studies (GISS) as an example, we demonstrate that the system is able to (1) manage large volume datasets over the Internet; (2) visualize 2D/3D/4D spatiotemporal data; (3) broker various spatiotemporal statistical analyses for climate research; and (4) support interactive data analysis and knowledge discovery. This research also provides an example for managing, disseminating, and analyzing Big Data in the 21st century.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.