IsoTrotter: Visually Guided Empirical Modelling of Atmospheric Convection

TL;DR

IsoTrotter introduces a visually guided modeling approach for atmospheric convection, combining interactive analysis with semi-automatic parameter optimization via isocontour navigation, validated with real flight data.

Contribution

The paper presents a novel semi-automatic technique called IsoTrotting that enhances empirical model fitting through visual parameter space exploration.

Findings

Successful modeling of atmospheric convection using flight trajectory data

Effective integration of visual analysis with automatic parameter optimization

Improved understanding of complex atmospheric phenomena

Abstract

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.