Articles | Volume 19, issue 6
https://doi.org/10.5194/gmd-19-2407-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-2407-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models
Konstantin Gregor
CORRESPONDING AUTHOR
TUM School of Life Sciences, Technical University of Munich, Freising, Germany
Benjamin F. Meyer
TUM School of Life Sciences, Technical University of Munich, Freising, Germany
Tillmann Gaida
Goto10 GmbH, Munich, Germany
Victor Justo Vasquez
Thoughtworks GmbH, Hamburg, Germany
Karina Bett-Williams
Global Systems Institute, University of Exeter, Exeter EX4 4PY, UK
UK Met Office, Fitzroy Road, Exeter EX1 3PB, UK
Matthew Forrest
Seckenberg Biodiversity and Climate Research Centre, Frankfurt, Germany
João P. Darela-Filho
TUM School of Life Sciences, Technical University of Munich, Freising, Germany
Sam Rabin
NSF National Center for Atmospheric Research, Boulder, Colorado, USA
Marcos Longo
Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Division of Numerical Modelling of the Earth System, General Coordination of Earth Sciences, National Institute for Space Research (INPE), Cachoeira Paulista, SP, Brazil
Joe R. Melton
Climate Research Division, Environment, and Climate Change Canada, Victoria, BC, V8N 1V8, Canada
Johan Nord
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 22362 Lund, Sweden
Peter Anthoni
Karlsruhe Institute of Technology, Institute of Meteorology and Climate, Research/Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen, Germany
Vladislav Bastrikov
Science Partners, Paris 75010, France
Thomas Colligan
University of Maryland, College Park, MD 20742, USA
NASA Goddard Space Flight Center, Earth Sciences Division, Biospheric Sciences Lab, 6 Greenbelt, MD 20771, USA
Christine Delire
CNRM, Météo-France, CNRS, Université de Toulouse, Toulouse, France
Michael C. Dietze
Department of Earth & Environment, Boston University, Boston, MA 02215, USA
George Hurtt
Department of Geographical Sciences, University of Maryland, College Park, MD 20770, USA
Akihiko Ito
The University of Tokyo, Tokyo, Japan
Lasse T. Keetz
Department of Geosciences, University of Oslo, Oslo, Norway
Jürgen Knauer
School of Life Sciences, Faculty of Science, University of Technology Sydney, Ultimo, NSW 2007, Australia
Johannes Köster
Bioinformatics and Computational Oncology, Institute for AI in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, Essen, Germany
Tzu-Shun Lin
NSF National Center for Atmospheric Research, Boulder, Colorado, USA
Lei Ma
Department of Geographical Sciences, University of Maryland, College Park, MD 20770, USA
Marie Minvielle
CNRM, Météo-France, CNRS, Université de Toulouse, Toulouse, France
Stefan Olin
Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 22362 Lund, Sweden
Sebastian Ostberg
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany
State Key Laboratory for Ecological Security of Regions and Cities, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
Reiner Schnur
Max Planck Institute for Meteorology, Hamburg, Germany
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
Wyss Academy for Nature, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Peter E. Thornton
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Anja Rammig
TUM School of Life Sciences, Technical University of Munich, Freising, Germany
Model code and software
Model workflow showcase Konstantin Gregor https://doi.org/10.5281/zenodo.15191115
Editorial statement
The manuscript presents a perspective on the reproducibility of geoscientific models, which fits in the type of manuscript.
The manuscript presents a perspective on the reproducibility of geoscientific models, which fits...
Short summary
Geoscientific models are crucial for understanding Earth’s processes. However, they sometimes do not adhere to highest software quality standards, and scientific results are often hard to reproduce due to the complexity of the workflows. Here we gather the expertise of 20 modeling groups and software engineers to define best practices for making geoscientific models maintainable, usable, and reproducible. We conclude with an open-source example serving as a reference for modeling communities.
Geoscientific models are crucial for understanding Earth’s processes. However, they sometimes do...