Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 6
Articles | Volume 19, issue 6
https://doi.org/10.5194/gmd-19-2385-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-2385-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 6
Development and technical paper
 | 
25 Mar 2026
Development and technical paper |  | 25 Mar 2026

The spatio-temporal visualization tool HMMLVis in renewable energy applications

Rainer Wöß, Kateřina Hlaváčková-Schindler, Irene Schicker, Petrina Papazek, and Claudia Plant

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Short summary
Our tool is an easy-to-use, interpretable causal inference software. It can be applied in any scientific discipline exploring time series. The tool uses heterogeneous Granger causality. It can be used on time-series data to infer causal relationships between multiple variables and a target time-series. The tool is demonstrated on different types of applications related to meteorological events in a renewable energy, air pollution, and postprocessing benchmark data.
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