Table of Contents - HUNAGI

iGlobe: Bringing Weather and Climate to a 3D Globe
Varun Chandola, Oak Ridge National Laboratory
The growing understanding of changing climate and its impact on the environment and society has
propelled heavy research investment in the area of climate modeling resulting in sophisticated
models that can capture multitudes of scenarios and produce realistic forecasts at decadal and
century scales and produce simulation outputs which are valuable data sources for understanding
climate change impacts.
At the same time, path breaking advances in remote
sensing technology has enabled measuring and
storing weather data at an unprecedented rate.
The dense scientific format in which such climate
and weather data is stored, NetCDF and HDF, makes
it a challenge to visualize as geospatial data in 4D
environments such as NASA WorldWind and Google
Earth, where they truly belong for effective
visualization and analysis in concert with traditional
geospatial data sets, such as terrain, infrastructure, demographics, and other data.
The Geographic Information Science and Technology (GIST) group at Oak Ridge National
Laboratory, in collaboration with researchers from Australia’s Commonwealth Scientific and
Industrial Research Organization (CSIRO), University Corporation
for Atmospheric Research (UCAR) and University of Kansas has
developed iGlobe, an open source desktop application that puts
climate research and weather data in a 3D globe where it can be
visualized and analyzed with other geospatial data.
iGlobe is based on NASA World Wind with significant
enhancements to ingest climate model outputs (i.e., NetCDF files)
and display them on a 3D globe. The application is capable of
handling complex visualizations such as time varying animations,
elevations, and vector field rendering.
The analytic core of iGlobe allows users to interact with the
different data sets using sophisticated data analysis tools to
perform complex operations such as anomaly detection,
spatiotemporal change detection, signal analysis, and connected
component detection that all take place on the ‘back-end’ server.
The server-side analysis component of iGlobe allows analysis on
high-end servers with the results visualized on the client. Since the
analysis outputs are typically magnitudes smaller than the original
data sets, the burden on network resources is minimized.
chandolav@ornl.gov