Guided Analysis of Hurricane Trends Using Statistical Processes Integrated with Interactive Parallel Coordinates
Chad A. Steed, J. Edward Swan II, T.J. Jankun-Kelly, and Patrick J. Fitzpatrick. Guided Analysis of Hurricane Trends Using Statistical Processes Integrated with Interactive Parallel Coordinates. In Proceedings of the IEEE Symposium on Visual Analytics Science and Technology (VAST 2009), pp. 19–26, October 2009.
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Abstract
This paper demonstrates the promise of augmenting interactive multivariate representations with information from statistical processes in the domain of weather data analysis. Statistical regression, correlation analysis, and descriptive statistical calculations are integrated via graphical indicators into an enhanced parallel coordinates system, called the Multidimensional Data eXplorer (MDX). These statistical indicators, which highlight significant associations in the data, are complemented with interactive visual analysis capabilities. The resulting system allows a smooth, interactive, and highly visual workflow. The system's utility is demonstrated with an extensive hurricane climate study that was conducted by a hurricane expert. In the study, the expert used a new data set of environmental weather data, composed of 28 independent variables, to predict annual hurricane activity. MDX shows the Atlantic Meridional Mode increases the explained variance of hurricane seasonal activity by 7-15% and removes less significant variables used in earlier studies. The findings and feedback from the expert (1) validate the utility of the data set for hurricane prediction, and (2) indicate that the integration of statistical processes with interactive parallel coordinates, as implemented in \appname, addresses both deficiencies in traditional weather data analysis and exhibits some of the expected benefits of visual data analysis.
Additional Information
Acceptance rate: 38% (26 out of 69)
BibTeX
@InProceedings{VAST09-htpc,
author = {Chad A. Steed and J. Edward {Swan~II} and T.J. Jankun-Kelly and
Patrick J. Fitzpatrick},
title = {Guided Analysis of Hurricane Trends Using Statistical Processes
Integrated with Interactive Parallel Coordinates},
booktitle = {Proceedings of the IEEE Symposium on Visual
Analytics Science and Technology (VAST 2009)},
year = 2009,
location = {Atlantic City, New Jersey, USA},
date = {October 12--13},
month = {October},
pages = {19--26},
abstract = {
This paper demonstrates the promise of augmenting interactive
multivariate representations with information from statistical processes
in the domain of weather data analysis. Statistical regression,
correlation analysis, and descriptive statistical calculations are
integrated via graphical indicators into an enhanced parallel coordinates
system, called the Multidimensional Data eXplorer (MDX).
These statistical indicators, which highlight significant
associations in the data, are complemented with interactive visual
analysis capabilities. The resulting system allows a smooth, interactive,
and highly visual workflow.
The system's utility is demonstrated with an extensive hurricane
climate study that was conducted by a hurricane expert.
In the study, the expert used a new data set of environmental weather
data, composed of 28 independent variables, to predict annual
hurricane activity. MDX shows the Atlantic Meridional
Mode increases the explained variance of hurricane seasonal activity by 7-15\%
and removes less significant variables used in earlier studies.
The findings and feedback from the expert (1) validate the utility of
the data set for hurricane prediction, and (2) indicate that the
integration of statistical processes with interactive parallel
coordinates, as implemented in \appname,
addresses both deficiencies in traditional weather data analysis and
exhibits some of the expected benefits of visual data analysis.
},
}