TY - JOUR
T1 - SimilarityExplorer
T2 - A visual inter-comparison tool for multifaceted climate Data
AU - Poco, J.
AU - Dasgupta, A.
AU - Wei, Y.
AU - Hargrove, W.
AU - Schwalm, C.
AU - Cook, R.
AU - Bertini, E.
AU - Silva, C.
PY - 2014/6
Y1 - 2014/6
N2 - Inter-comparison and similarity analysis to gauge consensus among multiple simulation models is a critical visualization problem for understanding climate change patterns. Climate models, specifically, Terrestrial Biosphere Models (TBM) represent time and space variable ecosystem processes, like, simulations of photosynthesis and respiration, using algorithms and driving variables such as climate and land use. While it is widely accepted that interactive visualization can enable scientists to better explore model similarity from different perspectives and different granularity of space and time, currently there is a lack of such visualization tools. In this paper we present three main contributions. First, we propose a domain characterization for the TBM community by systematically defining the domain-specific intents for analyzing model similarity and characterizing the different facets of the data. Second, we define a classification scheme for combining visualization tasks and multiple facets of climate model data in one integrated framework, which can be leveraged for translating the tasks into the visualization design. Finally, we present SimilarityExplorer, an exploratory visualization tool that facilitates similarity comparison tasks across both space and time through a set of coordinated multiple views. We present two case studies from three climate scientists, who used our tool for a month for gaining scientific insights into model similarity. Their experience and results validate the effectiveness of our tool.
AB - Inter-comparison and similarity analysis to gauge consensus among multiple simulation models is a critical visualization problem for understanding climate change patterns. Climate models, specifically, Terrestrial Biosphere Models (TBM) represent time and space variable ecosystem processes, like, simulations of photosynthesis and respiration, using algorithms and driving variables such as climate and land use. While it is widely accepted that interactive visualization can enable scientists to better explore model similarity from different perspectives and different granularity of space and time, currently there is a lack of such visualization tools. In this paper we present three main contributions. First, we propose a domain characterization for the TBM community by systematically defining the domain-specific intents for analyzing model similarity and characterizing the different facets of the data. Second, we define a classification scheme for combining visualization tasks and multiple facets of climate model data in one integrated framework, which can be leveraged for translating the tasks into the visualization design. Finally, we present SimilarityExplorer, an exploratory visualization tool that facilitates similarity comparison tasks across both space and time through a set of coordinated multiple views. We present two case studies from three climate scientists, who used our tool for a month for gaining scientific insights into model similarity. Their experience and results validate the effectiveness of our tool.
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U2 - 10.1111/cgf.12390
DO - 10.1111/cgf.12390
M3 - Article
AN - SCOPUS:84904431375
SN - 0167-7055
VL - 33
SP - 341
EP - 350
JO - Computer Graphics Forum
JF - Computer Graphics Forum
IS - 3
ER -