Color Coding of Large Value Ranges Applied to Meteorological Data

Daniel Braun, Kerstin Ebell, Vera Schemann, Laura Pelchmann, Susanne Crewell, Rita Borgo, Tatiana von Landesberger

View presentation:2022-10-20T19:00:00ZGMT-0600Change your timezone on the schedule page
2022-10-20T19:00:00Z
Exemplar figure, described by caption below
Order of Magnitude Colors: A new color coding approach to encode data with large value ranges applied to meteorological cloud data.

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Keywords

Color Coding—Perception—Large Value Ranges—User study

Abstract

This paper presents a novel color scheme designed to address the challenge of visualizing data series with large value ranges, where scale transformation provides limited support. We focus on meteorological data, where the presence of large value ranges is common. We apply our approach to meteorological scatterplots, as one of the most common plots used in this domain area. Our approach leverages the numerical representation of mantissa and exponent of the values to guide the design of novel ``nested'' color schemes, able to emphasize differences between magnitudes. Our user study evaluates the new designs, the state of the art color scales and representative color schemes used in the analysis of meteorological data: ColorCrafter, Viridis, and Rainbow. We assess accuracy, time and confidence in the context of discrimination (comparison) and interpretation (reading) tasks. Our proposed color scheme significantly outperforms the others in interpretation tasks, while showing comparable performances in discrimination tasks.