Articles | Volume 19, issue 15
https://doi.org/10.5194/gmd-19-7389-2026
© 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-19-7389-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
11 Aug 2026
Model description paper |
| 11 Aug 2026
| 11 Aug 2026
GLIDE-SOL: a GPU-accelerated global lightweight infrastructure for diagnostic environmental modeling with SOLWEIG
Andrea Zonato
CORRESPONDING AUTHOR
CIMA Research Foundation, Savona, Italy
Harsh G. Kamath
Jackson School of Geosciences, University of Texas at Austin, Austin, TX, USA
Naveen Sudharsan
Jackson School of Geosciences, University of Texas at Austin, Austin, TX, USA
Luca Monaco
CIMA Research Foundation, Savona, Italy
Jonas Kittner
Bochum Urban Climate Lab, Ruhr University Bochum, Bochum, Germany
Luise Wolf
Bochum Urban Climate Lab, Ruhr University Bochum, Bochum, Germany
Matthias Demuzere
B-Kode VOF, Ghent, Belgium
Global Facility for Disaster Reduction and Recovery, World Bank Group, Washington, DC, USA
Ariane Middel
The GAME School, Arizona State University, Tempe, AZ, USA
School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, USA
Benjamin Bechtel
Bochum Urban Climate Lab, Ruhr University Bochum, Bochum, Germany
Massimo Milelli
CIMA Research Foundation, Savona, Italy
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Short summary
Cities need fast, reliable heat-stress maps to plan cooling measures and protect people. We built an automated workflow that gathers global public data, runs an outdoor comfort model much faster on graphics processing units, and adds simple corrections for wind and night-time warming. Tested in Dortmund against many sensors, errors fell from about ten to under three °C.
Cities need fast, reliable heat-stress maps to plan cooling measures and protect people. We...
