Color Coding of Large Value Ranges Applied to Meteorological Data

Daniel Braun, K. Ebell, V. Schemann, L. Pelchmann, S. Crewell, R. Borgo, T. V. Landesberger
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引用次数: 1

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 meteo-rological 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 rep-resentative 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 signifi-cantly outperforms the others in interpretation tasks, while showing comparable performances in discrimination tasks.
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大数值范围彩色编码在气象数据中的应用
本文提出了一种新的配色方案,旨在解决具有大值范围的可视化数据序列的挑战,其中尺度转换提供有限的支持。我们关注的是气象数据,其中存在较大的值范围是常见的。我们将我们的方法应用于气象散点图,这是该领域最常用的图之一。我们的方法利用尾数和指数的数值表示来指导新颖的“嵌套”配色方案的设计,能够强调数量级之间的差异。我们的用户研究评估了气象数据分析中使用的新设计、最先进的色阶和代表性配色方案:ColorCrafter、Viridis和Rainbow。我们在辨别(比较)和解释(阅读)任务的背景下评估准确性、时间和信心。我们提出的配色方案在解释任务中显著优于其他配色方案,而在辨别任务中表现相当。
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