With increasing computing power, more accurate and affordable weather monitoring instruments, and progress in remote sensing technology, the amount and frequency of meteorological, climatological, and related data collected every day grows continuously. Consequently, data analysis becomes a time-consuming and oftentimes difficult task. This is also due to the complexity of the datasets, which are usually spatially dependent, time varying, multivariate, or even multimodal. Adequate visualization and interaction techniques can help to explore such large and heterogeneous datasets. Visualization enables researchers to find interesting features, to detect spatial, temporal, or multivariate relationships, or to evaluate uncertainties in the data. This facilitates the understanding of atmospheric processes or mutual feedbacks between Earth system components. At the same time, visualization can be used to communicate important findings to stakeholders or the general public. For this session, we welcome contributions from research fields—such as scientific visualization, information visualization, or visual analytics—that are applicable to datasets from climatology, meteorology, or related disciplines.

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