This dataset accompanies the publication “Enhancing Energy System Modeling with Global Weather Forecast Integration: A German Case Study with European Outlook”. It contains the full code and configuration required to reproduce the presented case study, which integrates short-term weather prediction data into the open-source energy system model PyPSA-Eur. The dataset includes: Python scripts for pre-processing weather forecasts, updating PyPSA networks, and running the two-step optimization (market and redispatch model), All relevant configuration files and parameters, Custom modifications to the following open-source tools: PyPSA-Eur (network representation and optimization setup), atlite (support for forecast-based weather inputs), powerplantmatching (integration of MaStR data), Example input data for forecasted renewable generation, inflow, and day-ahead demand, Output NetCDF files of both market-clearing and redispatch power flow simulations. The dataset supports research into the operational flexibility and resilience of power systems under weather uncertainty and is designed to enable further work on real-time modeling, curtailment analysis, and grid congestion management across Europe. All data and code are provided in a structured folder for reproducibility and transparency.