Tools and Datasets
CURA Lab develops and maintains advanced tools and methodologies to support research on climate change, urban resilience, and sustainable buildings. These tools are used by our team and shared with the wider research community to foster collaboration and innovation.
Future Weather Generator (FWG)
The Future Weather Generator is a computational tool created and maintained by CURA Lab to produce future weather datasets for use in dynamic building and urban simulations. By combining historical weather records with climate projections, FWG generates high-resolution climate files that enable researchers, engineers, and planners to assess building performance, renewable energy systems, and urban heat adaptation strategies under future climate scenarios.
- Applications:
- Building energy simulations and retrofitting strategies.
- Assessment of renewable system resilience (e.g., PV, thermal storage).
- Urban climate studies and heat island mitigation.
- Policy and planning analysis for climate adaptation.
- Key Features:
- Integration of climate change scenarios (IPCC, regional models).
- Compatibility with leading simulation platforms (e.g., EnergyPlus, TRNSYS, Urban modeling tools).
- Flexible outputs tailored to different spatial and temporal resolutions.
Datasets
- Rodrigues E, Tinseth J, Global Household Size and Energy Use Intensity Under Shared Socioeconomic Pathways from 1960 to 2100, figshare, 2025. URL: https://doi.org/10.6084/m9.figshare.28207895.
- Rodrigues E, Fernandes MS, Dataset of the energy performance of synthetic residential buildings in Europe and Africa under climate change, figshare, 2022. URL: https://doi.org/10.6084/m9.figshare.21287883.
- Rodrigues E, Azimi Fereidani N, Fernandes MS, Gaspar AR, Dataset of the energy performance of synthetic residential buildings in Iran under climate change, figshare, 2023. URL: https://doi.org/10.6084/m9.figshare.21905682.
- Rodrigues E, Parente JM, Dataset of 2500 synthetic single-family floor plan images ranging from T0 to T4, figshare, 2025. URL: https://doi.org/10.6084/m9.figshare.28282802.