EGU26-5739, updated on 13 Mar 2026
https://doi.org/10.5194/egusphere-egu26-5739
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Wednesday, 06 May, 14:27–14:30 (CEST)
 
vPoster spot 4
Poster | Wednesday, 06 May, 16:15–18:00 (CEST), Display time Wednesday, 06 May, 14:00–18:00
 
vPoster Discussion, vP.107
An Indicator Service Framework for assessing and integrating climate adaptation–mitigation interdependencies across spatial scales
Ivan Murano, Gigliola D'Angelo, Venera Pavone, Paola Del Prete, and Giulio Zuccaro
Ivan Murano et al.
  • Plinivs APS, Napoli, Italy (plinivs.ets@gmail.com)

As climate change impacts intensify, cities and regions are increasingly required to address adaptation and mitigation in parallel. In practice, however, these two dimensions are often planned and implemented separately, leading to missed co-benefits or unintended trade-offs. Thus, there is a growing need for traceable and operational methods capable of revealing, assessing, and integrating the interdependencies between adaptation and mitigation across sectors and spatial scales. To address this gap, this paper introduces the Indicator Service Framework (ISF), produced in the context of the ClimEmpower project (EU Horizon 2020) This methodological approach translates climate indicators into actionable insights, bridging the two fields of study to improve spatial analysis and local-to-regional decision-making.

The ISF operationalizes climate science by translating robust climate indicators into actionable policy insights. Its design is deliberately anchored in three core principles: multi-scale applicability, ensuring relevance from local to regional levels; data-agnostic design, allowing compatibility with any data source derived from hazard, exposure, and vulnerability assessments; and explicitness of decision logic. A central element of the ISF is the focus on identifying the most appropriate indicators for specific policy objectives, clearly establishing their relationship to the underlying climate risks and local conditions.

The framework employs a streamlined two-step process: first, indicator values are rigorously classified according to their scientific meaning,or against a defined benchmark (e.g., a European average or median value), which subsequently establishes the threshold for policy recommendations; second, they are standardized into harmonized classes. This standardization is crucial, as it enables systematic comparability across regions and facilitates the mapping of results to tailored recommendations. This mechanism is key to identifying concrete opportunities for co-benefits, such as mobility policies that simultaneously reduce emissions and enhance urban thermal comfort.

By structuring a clear pathway from climate data to policy decisions, the ISF functions as more than just a tool; it provides a clear strategic "reading frame" upon which climate actions can be anchored. This approach ensures that the resulting recommendations are systematically adapted to foster the overarching objective of 'climate resilient development' (IPCC 2022). The framework offers a practical contribution to integrated climate governance, enhancing stakeholder awareness and supporting more coherent, resilient, and sustainable strategies under conditions of multi-sectoral complexity.

How to cite: Murano, I., D'Angelo, G., Pavone, V., Del Prete, P., and Zuccaro, G.: An Indicator Service Framework for assessing and integrating climate adaptation–mitigation interdependencies across spatial scales, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5739, https://doi.org/10.5194/egusphere-egu26-5739, 2026.