A Spatiotemporal GIS Framework Applied to the Analysis of Changes in Temperature Patterns

Abstract

AbstractThis research develops a new temporal Geographic Information System (GIS) framework and applies it to compare General Circulation Model (GCM) products and reanalysis datasets in order to discern differences in patterns and locations of change as a proof of concept. The proposed framework incorporates the concept of kinematics to represent the movement of isolines as advection displacement vectors. Comparison of displacement vectors from the four datasets shows differences in isotherm shifts for both median values and interquartile ranges along with several prominent, well defined difference regions across the globe. Among the four datasets used in the study, the two reanalysis datasets have the smallest median difference in displacement vectors indicating the least spatiotemporal difference. As both reanalysis datasets are based on actual observations, this result validates the displacement vector representation. The CNRM CM3 20C3M dataset contains an Antarctic Cooling that led to most of the differences in displacement vectors against the other datasets. The research shows the effectiveness of GIS enabled displacement vectors analysis to elicit spatial differences in climate patterns among GCM data and reanalysis data. While temperature data were used in the case study, the proposed method is based on concepts applicable to other isolines of geographic variables (such as isobars or isohyets).