Enhanced Data Exploration and Visualization Tool for Large Spatio-Temporal Climate Data

Abstract

Predictions of climate variables like precipitation and maximum/minimum temperatures play crucial role in assessing the impact of decadal climate changes on regional water availability. This technical report describes a Graphical User Interface (GUI) called CMIViz developed as part of the 2016 REU program at UMBC. CMIViz is an R tool used for exploration and visualization of spatio-temporal climate data from the Missouri River Basin (MRB). The tool is developed using the R package `Shiny', which facilitates access on a web browser. Since prediction of precipitation is more challenging than the prediction of maximum/ minimum temperatures, CMIViz provides more visualization options for precipitation. Speci cally, the tool provides an easy intercomparison of data from the Global Climate Models (GCM): MIROC5, HadCM3, and NCAR-CCSM4 in terms of bias relative to the observed data, root mean-squared error (RMSE), and other measures of interest for daily precipitation. The tool has options to explore the temporal trends and autocorrelation patterns given a location and spatial patterns using contour plots, surface plots, and semivariograms given a time point. CMIViz also provides visualization of canonical correlation analysis (CCA) to help find similarities between the models.