UTCIcast: A Scalable Urban Thermal Stress Forecasting System Powered by GLIDE-SOL

UTCIcast is an operational framework for forecasting urban thermal stress that combines numerical weather prediction with high-resolution urban climate modeling. At its core lies GLIDE-SOL, a fully scripted and globally deployable Python workflow that enables rapid, consistent, and repeatable simulations of urban thermal conditions based on the SOLWEIG model.

GLIDE-SOL builds upon the SOLWEIG radiative balance formulation but redesigns the full modeling pipeline—including automated input generation, execution, and post-processing—to operate exclusively with globally available datasets. All required inputs, such as terrain, building morphology, vegetation structure, land cover, and meteorological forcing, are automatically derived from harmonized global products. This removes the need for local preprocessing and allows consistent applications across cities worldwide, from neighborhood to metropolitan scales.

Within UTCIcast, GLIDE-SOL is driven by short-range numerical weather prediction (e.g., ICON-EU forecasts up to 72 hours), enabling near-real-time simulations of the urban radiative environment. The model is implemented on GPUs, allowing meter-scale resolution simulations with reduced computational time. It produces key fields such as mean radiant temperature (Tmrt), shadow patterns, and near-surface meteorological variables, which are combined to compute the Universal Thermal Climate Index (UTCI), a physically consistent indicator of outdoor thermal stress.

To improve performance under coarse meteorological forcing, GLIDE-SOL incorporates lightweight physical diagnostics that capture key urban processes. These include a directional wind attenuation scheme based on urban roughness and obstacles, and diagnostic air temperature corrections that combine a simplified urban heat island (UHI) cycle with elevation-based adjustments derived from high-resolution digital elevation models. These additions enhance the representation of ventilation, nocturnal warming, and local temperature gradients.

Scalability is achieved through domain tiling with cross-tile synchronization, preserving radiative consistency while enabling simulations over large urban areas at fine spatial resolution. Outputs are generated as compressed georeferenced rasters and integrated into interactive web maps with hourly time navigation and pixel-level inspection.

The workflow is structured into three reproducible components: automated global input generation, a GPU-accelerated SOLWEIG execution engine, and a post-processing module for systematic analysis and visualization. An operational application in Dortmund, based on hourly observations from 25 stations and simulations at 2 m resolution over more than one year, demonstrates substantial improvements in UTCI accuracy, with RMSE reduced from 9.9°C to 2.7°C when including wind and temperature diagnostics.

By integrating global data, GPU-accelerated urban physics, and scalable processing, UTCIcast—powered by GLIDE-SOL—provides a flexible platform for near-real-time heat monitoring, forecast-based risk assessment, and consistent multi-city urban climate analyses.