  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.
