Static XAI techniques can support users in understanding AI models , but interactive tools are needed to aid users in exploration and understanding of complex models . The use of visualizations and visual analytics tools can aid humans in understanding complex datasets in a variety of domains . Currently, many scientists fall back to using spreadsheets as their main analysis tool. Although there is little overhead to learning how to use spreadsheet tools, they are mainly suited for simple analysis tasks, like sorting or filtering by some value of interest. More elaborate general-purpose dashboard tools, such as Spotfire , enable users to interactively explore their datasets . However, these off-the-shelf tools often lack the ability to accommodate the challenging aspects of RO datasets, like large parameter spaces that contain a mix of static and temporal data, and have data uncertainty arising both from limited data availability for the model and uncertainty and error in the measured data points. (see Section User tasks and challenges for more details). Similarities to prior work about visual analysis of parameter spaces from other areas exist but are not directly applicable to RO data and its challenges.