{Link for the Iberian Peninsula dashboard}

Current version of the dashboard: 1.0.0.

1. Introduction

This project aims to address the impacts of climate change on the built environment by developing a set of future Iberian Peninsula EPW (Energy Plus Weather Format) files and a dashboard to interpret and evaluate the data. The future climate files were obtained using the Future Weather Generator (FWG) (v4.1.0) [1] with climate projections for Portuguese and Spanish cities in islands and continental territory, integrating these projections into a code pipeline for automation. In this part of the project, thermal comfort indices, such as the Universal Thermal Climate Index (UTCI) and the Discomfort Index (DI), were also evaluated to understand future thermal comfort conditions. The methodology followed the structure available in the future-EPW-analysis repository:

1. Climate-One-Building (COB) web-scrapping for all available files (we recommend doing this carefully so as not to damage the COB infrastructure);
2. Automatic organisation of all EPW files in a folder, extracting them from the ZIP format;
3. Simulation of future climate files using FutureWeatherGenerator [1] (v4.1.0) in a line of code with default parameters (shown in Table 1);
4. Organisation of all available EPWs (original and simulated) in a single database;
5. Calculation of thermal comfort indices using pythermalcomfort [2].

The main objective is to provide researchers, policymakers, and professionals with a comprehensive tool for assessing and mitigating the impacts of climate change across different cities, offering accurate data for thermal comfort and energy-efficiency modelling. The methodology involves generating future EPW files, validating them against existing literature and visualising the results through a user-friendly dashboard. The study highlights the importance of adaptive and climate-resilient strategies in urban planning and building design. Expected climate changes include increased dry-bulb temperatures and variations in relative humidity, radiation, and wind speed. This research is similar to the one conducted in "Interpreting future climate conditions in Brazilian cities – Dashboard and EPW files". It is also similar to the paper published by Vaz et al. (2025) [3].

The dashboard has been designed to simplify the visualisation of future climate data, focusing on the main climate variables, thermal comfort indices and data visualisation. It allows users to filter by city and automatically calculate all the indices, providing detailed analyses and comparisons of different scenarios. By offering a free, open-access, multi-platform, extensible, customisable and easy-to-maintain tool, the project aims to facilitate continuous updates, new features and corrections. This tool supports decision-making in public policy and urban planning, promoting a more sustainable and resilient built environment in the face of climate change.

2. Further details on the methodology

Table 1 presents the simulation parameters. The GitHub repository for future-EPW-analysis [4] also includes procedures. The simulation was conducted in CMD using Python.

Table 1 - Parameters used in the FWG (4.1.0) simulation:

3. References

[1] E. Rodrigues, M.S. Fernandes, D. Carvalho, Future weather generator for building performance research: An open-source morphing tool and an application, Building and Environment 233 (2023) 110104. https://doi.org/10.1016/j.buildenv.2023.110104.

[2] F. Tartarini, S. Schiavon, pythermalcomfort: A Python package for thermal comfort research, SoftwareX 12 (2020) 100578. https://doi.org/10.1016/j.softx.2020.100578.

[3] Vaz, I.C.M.; Ghisi, E.; Thives, L.P.; Vieira, A.S.; Rupp, R.F.; da Rosa, A.S.; Flores, R.A.; Bastos, M.B.; Marinoski, D.L.; Silva, A.S.; Weeber, M.; Invidiata, A. (2024). Dashboard for interpreting future climate files used in the simulation of buildings – an outdoor thermal comfort approach. Under submission.

[4] Future EPW Analysis - A pipeline of processes aimed at providing future EPW files based on existing models from the literature. Available at: https://github.com/igorcmvaz/future-EPW-analysis.

Suggestions for improvements can be made directly in the GitHub repository at future-EPW-analysis or sent to igor.catao@posgrad.ufsc.br