  Empirical models, fitted to data from observations, are often used in natural
sciences to describe physical behaviour and support discoveries. However, with
more complex models, the regression of parameters quickly becomes insufficient,
requiring a visual parameter space analysis to understand and optimize the
models. In this work, we present a design study for building a model describing
atmospheric convection. We present a mixed-initiative approach to visually
guided modelling, integrating an interactive visual parameter space analysis
with partial automatic parameter optimization. Our approach includes a new,
semi-automatic technique called IsoTrotting where we optimize the procedure by
navigating along isocontours of the model. We evaluate the model with unique
observational data of atmospheric convection based on flight trajectories of
paragliders.
