Interactive Earth system data cube visualization in Jupyter notebooks

Visualization is key for interpreting the rapid growth of gridded, spatio-temporal data sets in Earth system sciences. However, today's tools are often designed as standalone applications, insufficiently integrated into scientific workflows, and typically not designed for directly interacting with data. Here, we introduce "Lexcube for Jupyter", an open-source tool designed to facilitate the interactive visualization of 3D data cubes within Jupyter notebooks. This integration aims to empower researchers to more effectively interpret complex datasets, e.g. during model development, data curation, or for model-data comparisons. Lexcube for Jupyter builds upon the established Lexcube.org architecture by S & ouml;chting et al. (2024), but is substantially advanced in order to make it part of a scientific Python workflow. Lexcube for Jupyter includes efficient data handling strategies, such as chunked data access and caching, as well as the implementation of LZ4 compression to optimize performance during interactive sessions. Employing the described techniques, Lexcube for Jupyter significantly reduces data processing and visualization times compared to existing tools, facilitating real-time data exploration.