One of the inspiring presentations of the CLIMAAX Virtual Regions Forum came from Portugal, where the Municipality of Viana do Castelo (VC_Climaax project) showcased how improving data resolution can significantly enhance climate risk assessment and decision-making. Presented by Liliana De Sousa, the case highlighted a key challenge faced by many regions: bridging the gap between European-scale datasets and local planning needs, a challenge defined as the “utility gap”.

From macro to micro

In its first phase, the region relied on European datasets with a 100-metre resolution, but feedback from local stakeholders made it clear that this level of detail was insufficient for operational decision-making. In response, the project shifted towards a higher-resolution, localised approach, prioritising heavy rainfall, floods and wildfires, moving from generalised climate signals to locally validated, decision-oriented analysis.

To refine heavy rainfall risk, the team analysed over 1,300 historical events, identifying ten critical hotspots where drainage capacity needs to be strengthened. For river flooding, advanced modelling techniques enabled mapping at ten-metre resolution, improving accuracy and avoiding modelling errors.

This allowed the team to estimate €25 million in expected annual damages and around 285 people potentially displaced each year. In the case of wildfires, machine learning was used to assess risk at the wildland–urban interface, revealing critical vulnerabilities in the strategic road network, essential for emergency evacuation.

From data to planning

Using the CLIMAAX Project framework, the region ranked its priorities based on severity, urgency and local capacity, identifying wildfires as the top strategic priority while extreme precipitation and river flooding were also considered high priorities.

A key innovation was the localisation of datasets, replacing European land cover data with national datasets and adapting economic parameters to better reflect the territorial reality. This enabled the mapping of critical infrastructure, including hospitals, schools and fire stations, making the results directly usable in municipal emergency plans and climate action plans.

Key lessons for other regions

The Portuguese case offers clear lessons for other regions, demonstrating that high-resolution data can make a decisive difference, historical data is essential to validate climate models, and stakeholder engagement is critical to ensure relevance and usability. Looking ahead, the project will move into Phase 3, focusing on selecting adaptation measures through multi-criteria analysis, with a strong emphasis on nature-based solutions. As highlighted during the CLIMAAX Virtual Regions Forum, this experience demonstrates how transforming abstract climate data into local, high-resolution intelligence is a key step towards effective and actionable climate adaptation.