Zooming in: SCREAM at 100&thinsp;m using regional refinement  over the San Francisco Bay Area

Zhang, Jishi; Bogenschutz, Peter; Taylor, Mark; Cameron-Smith, Philip

doi:10.5194/gmd-19-795-2026

Articles | Volume 19, issue 2

https://doi.org/10.5194/gmd-19-795-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-795-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 2

Model description paper

|

26 Jan 2026

Model description paper |

| 26 Jan 2026

Zooming in: SCREAM at 100 m using regional refinement over the San Francisco Bay Area

Jishi Zhang, Peter Bogenschutz, Mark Taylor, and Philip Cameron-Smith

Data sets

Code and Model Data for SCREAM 100 m San Francisco Bay Area Regionally Refined Model 0.0 version Jishi Zhang https://doi.org/10.5281/zenodo.15288872

Model code and software

Code and Model Data for SCREAM 100 m San Francisco Bay Area Regionally Refined Model 0.0 version Jishi Zhang https://doi.org/10.5281/zenodo.15288872

Video supplement

Supplementary videos for “Zooming In: SCREAM at 100 m Using Regional Refinement over the San Francisco Bay Area” (Geoscientific Model Development) Jishi Zhang https://doi.org/10.5446/s_1996

Short summary

We pushed a global cloud-resolving model to a novel 100 m setup over the San Francisco Bay Area using a regionally refined mesh. The model captured fine-scale air motions over complex terrain and coastal regions at large-eddy scales with comprehensive global modeling configuration, enabled by scale-aware turbulence parameterization. Performance tests demonstrated that graphics processing unit (GPU) acceleration make such high-resolution simulations feasible within practical timeframes.