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Crameri - Accurate and accessible colour use for representing numerical models.

THURSDAY 16 JANUARY 2025 Accurate and accessible colour use for representing numerical models. Fabio Crameri (1,2) (1) Undertone.design, Bern, Switzerland (fabiocrameri@undertone.design) (2) International Space Science Institute (ISSI), Bern, Switzerland The deliberate use of colour in scientific visualization enriches our understanding and enables us to appreciate the beauty and complexity of the natural world and numerical models alike. As of today, scientific visualization—even though universally used—is rarely part of the obligatory curriculum of an upcoming geodynamic modeller. In terms of colour use, the numerical modelling community therefore swings back and forth between self-educated science-proof application and peer-endorsed misuse. When misused, data visualization can exclude readers or misguide them. In the worst case, it does both. From the properties of the light source to the ultimate recognition in the visual cortex, the study of human colour perception is extensive and has a long history. Creating accessible and accurate scientific visualization with colour has, in contrast, become easy. All necessary aspects are understood. All necessary tools exist. Here, I will provide you with the basic understanding to use—and not misuse—colour for visualising everything from the simplest bar plot to the most elaborate mantle convection model. Pioneering science-proof colour palettes and gradients have started their journey in the first fully automated post-processing tool for numerical mantle convection models, StagLab (www.fabiocrameri.ch/staglab/), and have since spread across codes, models, and modellers. To avoid any form of colour confinement, I will introduce you to the newest version of the Scientific colour maps (www.fabiocrameri.ch/colourmaps/) and the different palette and gradient types available therein. After just this one lecture, you shall be equipped to navigate the most-basic use of colour in your daily work routine. I also hope you will then become an advocate of the scientific use of colour yourself so that after having mastered to run the most insightful models, we as a community will not fail the one job left: to accurately show them to everybody else.