Exploring Climate Patterns Embedded in Global Climate Change Datasets

This paper aims to explore the analysis of climate patterns embedded in the Global Climate Data Sets generated by the Community Climate System Model (CCSM) for the 4 Assessment Report of the Intergovernmental Report for Climate Change (IPCC). A Geographic Information Systems (GIS) approach is taken to examine spatiotemporal correlates among climate processes and to draw insights into their relationships and responses to climate change scenarios. With foci on El Nino southern Oscillation (ENSO) events and precipitation anomalies, the research explores three CCSM cases from worst-case, average, and conservative CO2 emission scenarios, respectively. The scenarios used are A2: continental economic regions dominate with an economic focus (representing a worst case scenario), B1: a global economy with environmental focus (representing an average scenario), CC: CO2 levels are stable at the current level (representing the best case scenario). GIS methods were used to examine the spatial and temporal development of precipitation anomalies under these three scenarios. A GIS spatiotemporal object growth classification scheme is proposed and then developed further in this paper. Further research is proposed to further the development and use of the GIS spatiotemporal object growth classification scheme.