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Using Generative Art to Convey Past and Future Climate Transitions
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Improving the visual communication of environmental model projections.

Hayley J Bannister1,2,3, Paul G Blackwell4, Kieran Hyder5,6

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Visualizing multi-model ensembles (MMEs) effectively is crucial for environmental management. Dot and box plots are superior for accurately communicating complex climate model data, outperforming other visualization types.

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Area of Science:

  • Environmental modeling
  • Climate science
  • Data visualization

Background:

  • Environmental and ecosystem models project future states for natural system management.
  • Multi-model ensembles (MMEs) enhance projection reliability but introduce communication challenges due to uncertainty.
  • Effective data visualization is needed to accurately convey complex MME outputs.

Purpose of the Study:

  • To identify the most effective data visualization methods for communicating outputs from global climate model ensembles.
  • To establish an evidence base for designing visually appealing and accurate MME visualizations.
  • To guide the development of visualizations that enhance the impact and societal relevance of climate models.

Main Methods:

  • Conducted a survey assessing interpretation accuracy, confidence, and ease of 10 different visualizations of MME outputs.
  • Collected participant preferences for various visualization techniques.
  • Analyzed performance metrics across different visualization types.

Main Results:

  • Dot and box plots demonstrated superior performance in accuracy and ease of interpretation.
  • Heat maps and radar plots were found to be less effective for communicating MME data.
  • An infographic, while visually appealing, lacked sufficient detail for accurate interpretation.

Conclusions:

  • Dot and box plots are recommended for effectively communicating MME outputs.
  • Guidelines are provided to optimize MME visualizations for clarity and impact.
  • Improved visualization practices can enhance the societal impact of climate models in management decisions.