The division is dedicated to the development and application of models for climate analysis and its impacts at the local scale, supporting communities in managing climate risks and defining adaptation policies. By combining advanced research and climate services, the division aims to strengthen local resilience, addressing the challenges posed by climate change at both the national and international levels.
A key aspect of the division is the development of high-resolution regional climate models, with a particular focus on extreme events, which are becoming more frequent and intense due to climate change. The research primarily focuses on the development of “convection-permitting” models, which allow for more accurate simulation of intense and localized atmospheric phenomena. In addition to this established expertise, innovative techniques such as statistical downscaling and the use of artificial intelligence are being adopted to enhance the understanding of local climate. Furthermore, the division utilizes in situ and satellite data platforms for verifying and developing climate analyses, providing advanced tools for increasingly accurate knowledge of the local climate and its impacts across different contexts. The division participates in numerous national and international research programs, such as EURO-CORDEX and MENA-CORDEX, to improve climate downscaling tools and foster a more detailed understanding of expected local climate changes. For over ten years, it has been collaborating on the development of limited-area models for weather forecasting, including COSMO and ICON, and uses the WRF model for various meteorological applications.
To ensure optimal use of data and analyses on climate change and its related impacts, the division also develops customized climate services. These services integrate advanced data analysis techniques and artificial intelligence to offer effective solutions in analyzing impacts and risks, supporting the definition of adaptation strategies at the local level. Through the Dataclime digital platform (www.dataclime.com), users can visualize and study extreme events and their impacts, utilizing high-resolution data and easily integrating this climate information into decision-support systems. Dataclime also offers numerous other climate services, developed over the years by the division, thanks to close collaboration with companies, local authorities, and national and international research projects.
The division is also committed to improving traditional civil engineering tools, adapting them to the challenges posed by climate change and identifying new opportunities for sustainable development. Advanced methods are being developed for geo-hydrological risk management, resilient infrastructure design, and updating technical regulations to ensure the safety and efficiency of constructions.
Particular attention is given to managing climate risks in urban areas. In this context, the division studies urban resilience at both micro and macro levels, integrating interdisciplinary skills, local knowledge, and scientific methodologies to promote social change and ensure the long-term sustainability of urban contexts. In addition to using the tools described above, the division adopts participatory models for planning and designing innovative adaptation solutions, collaborating with local governance and communities.
All these tools are applied to support public and private entities, both nationally and internationally, contributing to the development of effective solutions for decision-making in key sectors such as health, infrastructure, and many others.
REMHI Projects
The IRIDE program is an innovative project undertaken by the Italian government,…
The IRIDE program is an innovative project undertaken by the Italian government…
REMHI Publications
Quantile-based bias-correction of extreme rainfall: Pros & cons of popular methods for climate signal preservation
Padulano R.; Gomez L., Napolitano L., Rianna G.
2025, Journal of Hydrology, doi: 10.1016/j.jhydrol.2025.132814
Published articles
Km-scale climate simulations over Madeira and Canary Islands under present and future conditions: a model intercomparison study.
Adinolfi M., Loprieno L., Demory, ME. et al.
2025, Climate Dynamics, Volume 63, article number 89, doi: 10.1007/s00382-024-07563-x
Published articles
Heatwave Future Changes From an Ensemble of Km‐Scale Regional Climate Simulations Within CORDEX‐FPS Convection
Sangelantoni L., Sobolowski S.P. ; Soares P.M.M. ; Goergen K.; Cardoso R.M.; Adinolfi M., Dobler A.; Katragkou E.; Scoccimarro E., et al.
2025, Geophysical Research Letters, Volume 52, Issue 2, doi: 10.1029/2024GL111147
Published articles
Research Units
Research Unit Leader
Mario Raffa
The Regional model research unit develops downscaling tools, combining physical models, statistical approaches, and machine learning techniques to provide detailed meteorological and climate analyses in various parts of the world. Through its participation in numerous international projects, REM is widely recognized for its work on regional and limited-area atmospheric climate models. Since 2006, it has played a significant role in developing COSMO and ICON models, in collaboration with the COSMO consortium and the CLM Assembly. REM performs high-resolution simulations to assess climate impacts on a local scale, thereby supporting effective adaptation strategies and providing assistance to all divisions within the ICR Institute. Its main activities include developing ‘convection-permitting’ models to better simulate localized atmospheric phenomena in complex contexts, studying extreme events, and analyzing climate dynamics in urban areas. REM uses advanced computing infrastructures and integrates artificial intelligence techniques to enhance the quality of meteorological and climate analyses. It is also actively involved in the EURO-CORDEX and MENA-CORDEX programs, as well as other related strategic initiatives.
Research Unit Leader
Giuliana Barbato
The Climate service research unit addresses climate change challenges by bridging research and end users. It leverages data from weather-and climate models, observations, and machine learning methods to quantify hazards in climate risk analysis processes for key sectors such as energy, infrastructure, and water, in collaboration with other division of the institute ICR. CS’s mission is to provide tailored support, linking climate data, potential impacts, and areas of interest to facilitate informed decision-making. This approach relies on co-design, capacity-building, and continuous scientific updates, integrating new products and methodologies to create specific digital twins. The data is made accessible through the DATACLIME platform, a key resource for researchers, businesses, and policymakers. CS also develops innovative procedures for impact analysis in complex urban contexts, supporting the planning of adaptation strategies.
Research Unit Leader
Guido Rianna
Research Unit Leader
Alfredo Reder
The Urban risk adaptation research unit with experts in engineering, architecture, planning, social sciences, and communication, specializes in urban-scale climate risk assessment and adaptation. URA develops qualitative and quantitative frameworks to assess climate resilience and risk across key scales (territorial, urban, built environment) and subsystems (buildings, infrastructure, population, heat-health nexus). These frameworks integrate interdisciplinary knowledge with local information gathered through participatory engagement, promoting exchange and dialogue with other research areas. URA focuses on heat and flood stresses, using satellite, in situ data, and specialized climate simulations for urban environments. Additionally, URA advances urban adaptation planning and management, with a focus on behavioral changes, social acceptance, and the built environment’s role in resilience.
Dataclime
Design your “Climate Solution”
Dataclime is a software, developed in GIS environment, with the main goal to manage climate data, link climate and impact studies and assist a wide range of users.
It is a user-friendly interactive web platform allowing users to evaluate multiple features of simulated and observed data over different geographical domains having local, national and continental extension.