Issue No. 05 - September/October (2017 vol. 37)
Wei Luo , University of California, Santa Barbara
Michael Steptoe , Arizona State University
Zheng Chang , Amazon Corporate
Robert Link , Pacific Northwest National Laboratory
Leon Clarke , Pacific Northwest National Laboratory
Ross Maciejewski , Arizona State University
Scenario analysis has been widely applied in climate science to understand the impact of climate change on the future human environment, but intercomparison and similarity analysis of different climate scenarios based on multiple simulation runs remain challenging. Although spatial heterogeneity plays a key role in modeling climate and human systems, little research has been performed to understand the impact of spatial variations and scales on similarity analysis of climate scenarios. To address this issue, the authors developed a geovisual analytics framework that lets users perform similarity analysis of climate scenarios from the Global Change Assessment Model (GCAM) using a hierarchical clustering approach.
Geographic information systems, Data science, Cluster approximations, Visual analytics, Image analysis, Spatial resolution, Hierarchical systems
W. Luo, M. Steptoe, Z. Chang, R. Link, L. Clarke and R. Maciejewski, "Impact of Spatial Scales on the Intercomparison of Climate Scenarios," in IEEE Computer Graphics and Applications, vol. 37, no. 5, pp. 40-49, 2017.