Understanding Climate Change Patterns with Multivariate Geovisualization

Abstract

Climate change has been a challenging and urgent research problem for many related research fields. Climate change trends and patterns are complex, which may involve many factors and vary across space and time. However, most existing visualization and mapping approaches for climate data analysis are limited to one variable or one perspective at a time. For example, it is common to map the surface temperature anomaly at different locations or plot trends of time series. Although such approaches are useful in presenting information and knowledge, they have limited capability to support discovery and understanding of unknown complex patterns from data that span across multiple dimensions. This paper introduces the application of a multivariate geovisualization approach to explore and understand complex climate change patterns across multiple perspectives, including the geographic space, time, and multiple variables.