Interpreting Seasonal Forecast Visualizations: Differences in Mental Models Between Experts and Users

Weather and climate forecasting tools are becoming indispensable in helping individuals and communities prepare and cope with future conditions. However, despite considerable improvements in the physics behind forecasting in recent decades, forecasting still comes with inherent uncertainty. This study compares the accuracy and completeness of the mental models of expert ( N = 8) and general ( N = 20) users of a seasonal forecasting visualization. In addition, half the users were presented with the short narrative that normally accompanies the seasonal forecasting visualization and the other half were not shown the narrative. As expected, expert users had more accurate and complete mental models than general users, but even the expert users had misconceptions that would have had an impact on correct planning and would erode trust in seasonal forecasting. The short narrative improved the mental models and had a bigger impact on general users than expert users.

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Publication Details

Journal
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Published
2026-09-06
DOI
https://doi.org/10.1177/10711813261485941
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.00

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article

Interpreting Seasonal Forecast Visualizations: Differences in Mental Models Between Experts and Users

Olivier Crespo, Andrew Thatcher, Ammaarah Darsot, Andiswa Mlindazwe
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Data Visualization and Analytics
article

Interpreting Seasonal Forecast Visualizations: Differences in Mental Models Between Experts and Users

Olivier Crespo, Andrew Thatcher, Ammaarah Darsot, Andiswa Mlindazwe
article en

Abstract

Weather and climate forecasting tools are becoming indispensable in helping individuals and communities prepare and cope with future conditions. However, despite considerable improvements in the physics behind forecasting in recent decades, forecasting still comes with inherent uncertainty. This study compares the accuracy and completeness of the mental models of expert ( N = 8) and general ( N = 20) users of a seasonal forecasting visualization. In addition, half the users were presented with the short narrative that normally accompanies the seasonal forecasting visualization and the other half were not shown the narrative. As expected, expert users had more accurate and complete mental models than general users, but even the expert users had misconceptions that would have had an impact on correct planning and would erode trust in seasonal forecasting. The short narrative improved the mental models and had a bigger impact on general users than expert users.

Proceedings of the Human Factors and Ergonomics Society Annual Meeting
University of Cape Town (ZA), University of the Witwatersrand (ZA)
National Research Foundation
Climate action
Openalex Percentile: Top 13%
Data Visualization and Analytics
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