Information Visualization in Climate Research

Christian Tominski1, Jonathan F. Donges2,3, Thomas Nocke3

1University of Rostock, Rostock, Germany2Humbold University, Berlin, Germany

3Potsdam Institute for Climate Impact Research, Potsdam, Germany

Motivation

• Complex heterogeneous data in climate research– Excellent use case for information visualization– However, existing solutions and tools hardly used to solve

problems

• Gap between application and research• What are the reasons for the low pervasion of state-

of-the-art visualization tools?– Find answer by interviewing climate researchers!– Take first steps to accommodate information visualization

in researchers’ daily work!

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Participants

• 76 people fromPotsdam Institute forClimate Impact Research

• Mixed experience:– senior researchers, researchers,

post-docs, PhD students,student assistants

• Various work backgrounds:– Meteorologists, climatologists, oceanographers,

hydrologists / economists, sociologists / ecologists, biologists / physicists / Geo-statisticians, geographers

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Interviews

Questions in the context of:• For which tasks is information visualization applied?• Which visualization techniques are used?• Which systems and tools are utilized to generate

visual representations?• Which are important features of visualization

software?

Answers collected in questionnaires for later analysis

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Answers

• Tasks accomplished with visualization:– Presentation of results in scientific contexts (93%)– Evaluation of models (76%)– Evaluation of hypotheses (70%)– Exploration of unknown data (69%)– Presentation of results for non-scientists (58%)

• Visualization techniques:– Time charts (90%)– Bar charts (77%)– Basic maps (66%)– Scatter plots (56%)– Height fields (18%)

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Answers

• Applied tools and systems:– Office suites (75%)– Script-based systems: R, Ferret, Grads, GMT (44%)– Math packages: Mathlab, Mathematica (44%)– Geographic Information Systems (38%)– Tailored systems: Ocean Data View, Vis5D (20%)– !!! Visualization systems: OpenDX, AVS/Express, IDL, Spotfire,

InfoVis Toolkit, prefuse (7%) !!!

• Requested software features:– Appropriate labeling (81%)– Faithfully represent geo-spatial aspects (56%)– !!! High degree of interactivity (14%) !!!

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Discussion• Utilization

presentation of results vs. integration in scientific workflow

• Familiarizationone system vs. many tools

• Innovativenessclassic plots vs. state-of-the art techniques

• Dimensionality2D vs. 3D

• Reproducibilitycomputing vs. interactive and visual

• Interactivitymistrust in interaction vs. human-in-the-loop

• User requirementshighly user-rated features vs. rather unimportant implementation detail

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Discussion

• Situation: Many gaps and discrepancies between application and research

• Our goal:– Go beyond presentation– Promote interactive exploration and analysis– Integrate visualization in researchers’ daily work

• First steps:– Increase awareness of well-accepted visualization concepts

by introductory lessons and demonstrations– First positive feedbacks for visualizing climate networks

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Climate Data Analysis

• Standard way: linear statistical analysis (PCA, …)• Recent movement: network analysis (graph theory)

– Construct network G=(V,E)– Vertices:

• Measurement or grid points located in geo context• Represent time series data

– Edges: introduced if statistically relevant association between time series at vertices

• Successes: El-Nino Southern Oscillation, “Climate backbone”, …

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Climate Network Visualization

• Support climate network analysis with information visualization

• Requirements:– Efficiently handle |V| = O(104) and |E| = O(106)– Flexible dynamic filtering – Interactive adjustment of visual encoding within

reasonable limits– Linking and coordination of views– Geographical references are of utmost importance– Tackle edge congestion

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Climate Network Visualization

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Climate Network Visualization

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Climate Network Visualization

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Climate Network Visualization

Straight edges

Bundled edges

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Climate Network Visualization

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Conclusion

• Summary:• Investigated situation of use of information visualization• Introduced visualization of climate networks to researchers• Positive feedback of real users

• Future work:• Raise awareness and keep informed• Follow-up questionnaire on climate network visualization• Seamless integration of analytical, visual, and interactive

components into researchers’ workflows Visual Analytics

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