  Sensitivity analyses of simulation ensembles determine how simulation
parameters influence the simulation's outcome. Commonly, one global numerical
sensitivity value is computed per simulation parameter. However, when
considering 3D spatial simulations, the analysis of localized sensitivities in
different spatial regions is of importance in many applications. For analyzing
the spatial variation of parameter sensitivity, one needs to compute a spatial
sensitivity scalar field per simulation parameter. Given $n$ simulation
parameters, we obtain multi-field data consisting of $n$ scalar fields when
considering all simulation parameters. We propose an interactive visual
analytics solution to analyze the multi-field sensitivity data. It supports the
investigation of how strongly and in what way individual parameters influence
the simulation outcome, in which spatial regions this is happening, and what
the interplay of the simulation parameters is. Its central component is an
overview visualization of all sensitivity fields that avoids 3D occlusions by
linearizing the data using an adapted scheme of data-driven space-filling
curves. The spatial sensitivity values are visualized in a combination of a
Horizon Graph and a line chart. We validate our approach by applying it to
synthetic and real-world ensemble data.
