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

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Abstract

Pushing global climate models to large-eddy simulation (LES) scales over complex terrain has remained a major challenge. This study presents the first known implementation of a global model-SCREAM (Simple Cloud-Resolving E3SM Atmosphere Model)-at 100 m horizontal resolution using a regionally refined mesh (RRM) over the San Francisco Bay Area. Two hindcast simulations were conducted to test performance under both strong synoptic forcing and weak, boundary-layer-driven conditions. We demonstrate that SCREAM can stably run at LES scales while realistically capturing topography, surface heterogeneity, and coastal processes. The 100 m SCREAM-RRM substantially improves near-surface wind speed, temperature, humidity, and pressure biases compared to the baseline 3.25 km simulation, and better reproduces fine-scale wind oscillations and boundary-layer structures. These advances leverage SCREAM's scale-aware SHOC turbulence parameterization, which transitions smoothly across scales without tuning. Performance tests show that while CPU-only simulations remain costly, GPU acceleration with SCREAMv1 on NERSC's Perlmutter system enables two-day hindcasts to complete in under two wall-clock days. Our results open the door to LES-scale studies of orographic flows, boundary-layer turbulence, and coastal clouds within a fully comprehensive global modeling framework.

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APA

Zhang, J., Bogenschutz, P., Taylor, M., & Cameron-Smith, P. (2026). Zooming in: SCREAM at 100 m using regional refinement over the San Francisco Bay Area. Geoscientific Model Development, 19(2), 795–826. https://doi.org/10.5194/gmd-19-795-2026

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