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SimSat Studio, published by Fahrenheit Research, is a physically-based rendering tool that generates simulated satellite imagery from WRF (Weather Research and Forecasting) model output, currently available at version 0.3.0 across two released versions. Its purpose is to show what a geostationary weather satellite would observe when viewing a WRF simulation, producing visible true-color, infrared, water vapor, GeoColor, and Sandwich imagery along with derived fields. The rendering engine incorporates NASA Blue Marble ground textures with terrain shadows and seasonal blending, a finite-disk sun with realistic twilight, volumetric clouds featuring multiple scattering, and Cox-Munk water sun-glint modeling. Its synthetic thermal infrared output is processed through the same true-Kelvin enhancement pipeline used by operational GOES and Himawari satellite products, lending the simulated imagery a high degree of physical fidelity. The software is delivered in three forms to suit different workflows: a desktop application named simsat_studio, built on Rust with egui and wgpu; a headless command-line interface for automated or batch processing; and a Python binding that returns numpy arrays, accessible via a simple import simsat statement. This makes it suitable for meteorological research, model verification, forecast visualization, educational demonstrations, and integration into larger scientific Python pipelines. Within a software catalog, SimSat Studio falls under scientific visualization and atmospheric modeling utilities, specifically serving the weather simulation and remote sensing communities. Researchers can use the desktop studio for interactive exploration of model runs, while the CLI and Python interfaces support scripted generation of synthetic satellite products at scale. By bridging numerical weather prediction output and satellite-style imagery, the tool enables direct visual comparison between model forecasts and the kinds of observations that operational meteorologists routinely interpret.
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