GLIDE-SOL: A GPU-accelerated Global Lightweight Infrastructure for Diagnostic Environmental Modeling with SOLWEIG

Abstract. GLIDE-SOL is a fully scripted and globally re-deployable Python workflow that operationalizes SOLWEIG for rapid and repeatable thermal-comfort mapping across diverse urban environments. GLIDE-SOL is built on the SOLWEIG radiative balance libraries, but rewrites the surrounding system—including automated input generation, the execution engine, and post-processing—so that the model can be driven by globally available datasets and executed efficiently on GPUs. All inputs (terrain, building morphology, canopy height, land cover, and meteorology) are automatically derived from global products, eliminating local preprocessing while enabling consistent applications from neighborhood-scale analyses to city-wide and multi-city experiments. In addition, GLIDE-SOL introduces lightweight physical diagnostics to improve realism when driven by coarse meteorological forcing, targeting key urban controls on wind and near-surface temperature.

The workflow incorporates two physical augmentations: (i) roughness- and obstacle-based directional wind attenuation to approximate near-surface ventilation; and (ii) diagnostic temperature adjustments that combine a simple urban heat island (UHI) cycle with an elevation-based correction using high-resolution DEM information, to better capture nocturnal warming and local lapse-rate effects. 

To scale to large metropolitan areas, GLIDE-SOL uses explicit domain tiling with cross-tile synchronization to preserve radiative consistency across tile boundaries, enabling meter-scale simulations over tens to hundreds of square kilometers without sacrificing reproducibility. Daily outputs (24 radiative and meteorological fields) are stored as compressed GeoTIFFs to reduce disk usage and accelerate downstream processing.

GLIDE-SOL is implemented through three reproducible components: an automated global-input generator; a SOLWEIG execution engine with coordinated tiling; and a post-processing module for systematic sampling, time-series extraction, and visualization. An operational demonstration in Dortmund, using hourly measurements from 25 urban and peri-urban stations and simulations run at 2 m grid spacing between August 2024 and December 2025, shows that incorporating wind attenuation and the diagnostic temperature corrections substantially improves UTCI performance (RMSE reduced from 9.9 °C to 2.7 °C), alongside improvements in mean radiant and air temperature, and wind speed simulations.

By integrating harmonized global inputs with physics-based diagnostics, GPU acceleration, and scalable tiling, GLIDE-SOL supports applications such as operational UTCI nowcasting, retrospective and climatological analyses of heat stress, sensitivity tests of urban morphology and greening strategies, and coordinated multi-city experiments requiring consistent modeling protocols.