SimVis: An Interactive Visual Field Exploration Tool Applied to Climate Research
Abstract
Climate research often deals with large multi-dimensional fields describing the state of the atmosphere. A novel approach to gain information about these large data sets has become feasible only recently using 4D visualization techniques. The Simulation Visualization (SimVis) software tool, developed by the VRVis Research Center (Vienna, Austria), uses such techniques to provide access to the data interactively and to explore and analyze large three-dimensional time-dependent fields. Non-trivial visualization approaches are applied to provide a responsive and useful interactive experience for the user. In this study we used SimVis for the investigation of climate research data sets. An ECHAM5 climate model run and the ERA-40 reanalysis data sets were explored, with the ultimate goal to identify parameters and regions reacting most sensitive to climate change, representing robust indicators. The focus lies on the upper troposphere-lower stratosphere (UTLS) region, in view of future applications of the findings to radio occultation (RO) climatologies. First results showing the capability of SimVis to deal with climate data, including trend time series and spatial distributions of RO parameters are presented.
F. Ladstädter, A. K. Steiner, B. C. Lackner, G. Kirchengast, P. Muigg, J. Kehrer, and H. Doleisch, "SimVis: An Interactive Visual Field Exploration Tool Applied to Climate Research," in New Horizons in Occultation Research, A. Steiner, B. Pirscher, U. Foelsche, and G. Kirchengast, Eds., Springer, 2009, p. 235–245.
[BibTeX]
Climate research often deals with large multi-dimensional fields describing the state of the atmosphere. A novel approach to gain information about these large data sets has become feasible only recently using 4D visualization techniques. The Simulation Visualization (SimVis) software tool, developed by the VRVis Research Center (Vienna, Austria), uses such techniques to provide access to the data interactively and to explore and analyze large three-dimensional time-dependent fields. Non-trivial visualization approaches are applied to provide a responsive and useful interactive experience for the user. In this study we used SimVis for the investigation of climate research data sets. An ECHAM5 climate model run and the ERA-40 reanalysis data sets were explored, with the ultimate goal to identify parameters and regions reacting most sensitive to climate change, representing robust indicators. The focus lies on the upper troposphere-lower stratosphere (UTLS) region, in view of future applications of the findings to radio occultation (RO) climatologies. First results showing the capability of SimVis to deal with climate data, including trend time series and spatial distributions of RO parameters are presented.
@INCOLLECTION {ladstaedter09opac,
author = "Florian Ladst{\"a}dter and Andrea K. Steiner and Bettina C. Lackner and Gottfried Kirchengast and Philipp Muigg and Johannes Kehrer and Helmut Doleisch",
title = "SimVis: An Interactive Visual Field Exploration Tool Applied to Climate Research",
booktitle = "New Horizons in Occultation Research",
publisher = "Springer",
year = "2009",
editor = "A. Steiner and B. Pirscher and U. Foelsche and G. Kirchengast",
pages = "235--245",
abstract = "Climate research often deals with large multi-dimensional fields describing the state of the atmosphere. A novel approach to gain information about these large data sets has become feasible only recently using 4D visualization techniques. The Simulation Visualization (SimVis) software tool, developed by the VRVis Research Center (Vienna, Austria), uses such techniques to provide access to the data interactively and to explore and analyze large three-dimensional time-dependent fields. Non-trivial visualization approaches are applied to provide a responsive and useful interactive experience for the user. In this study we used SimVis for the investigation of climate research data sets. An ECHAM5 climate model run and the ERA-40 reanalysis data sets were explored, with the ultimate goal to identify parameters and regions reacting most sensitive to climate change, representing robust indicators. The focus lies on the upper troposphere-lower stratosphere (UTLS) region, in view of future applications of the findings to radio occultation (RO) climatologies. First results showing the capability of SimVis to deal with climate data, including trend time series and spatial distributions of RO parameters are presented.",
images = "images/ladstaedter09opac.jpg",
thumbnails = "images/ladstaedter09opac_thumb.jpg",
isbn = "978-3-642-00321-9",
url = "//dx.doi.org/10.1007/978-3-642-00321-9_19"
}