Squintu et al. (2026) Heatwaves in a 15 °C World: Exploring remote drivers’ influence on Northern Italy with a storyline-based approach

Identification

• Journal: Weather and Climate Extremes
• Year: 2026
• Date: 2026-08-31
• Authors: Antonello Squintu, Ronan McAdam, Jorge Pérez-Aracil, César Peláez-Rodríguez, M. Carmen Álvarez-Castro, Harilaos Loukos, David Barriopedro, Sancho Salcedo‐Sanz, Enrico Scoccimarro
• DOI: 10.1016/j.wace.2026.100949

Research Groups

• CMCC Foundation - Euro-Mediterranean Center on Climate Change, Bologna, Italy
• Department of Signal Processing and Communications. University of Alcalá., Alcalá de Henares, Spain
• Physical, Chemical and Natural Systems Department, University Pablo de Olavide, Seville, Spain
• The Climate Data Factory, Paris, France
• Instituto de Geociencias (IGEO), Consejo Superior de Investigaciones Científicas - Universidad Complutense de Madrid (CSIC-UCM), Madrid, Spain

Short Summary

This study proposes an application of the storylines technique to investigate the influence of global temperature conditions on heatwaves in Northern Italy. The results highlight relevant contributions from precipitation depletion over different Euro-Mediterranean domains and connections with tropical modes such as El Niño Southern Oscillation.

Objective

• Investigate the relationships between global thermodynamic states and local phenomena, such as heatwaves and their drivers.
• Identify the most relevant drivers of heatwaves in Northern Italy using a Machine Learning-based framework.

Study Configuration

• Spatial Scale: Regional (Northern Italy) and global scales.
• Temporal Scale: Daily to yearly time scales.

Methodology and Data

• Models used: CMIP6 models, including ACCESS-CM2, AWI-CM-1-1-MR, BCC-CSM2-MR, CAMS-CSM1-0, CMCC-ESM2, CMCC-CM2-SR5, CNRM-CM6-1, CNRM-CM6-1-HR, EC-Earth3, GFDL-CM4, HadGEM3-GC31-MM, INM-CM4-8, KACE-1-0-G, KIOST-ESM, MIROC6, MPI-ESM1-2-HR, MRI-ESM2-0, NorESM2-MM, and UKESM1-0-LL.
• Data sources: ERA5 reanalysis dataset and CMIP6 simulations.

Main Results

• The study identifies relevant contributions from precipitation depletion over different Euro-Mediterranean domains and connections with tropical modes such as El Niño Southern Oscillation.
• The results highlight the importance of considering global thermodynamic states in understanding local phenomena, such as heatwaves.

Contributions

• This study contributes to advancing scientific understanding of extreme events in a changing climate by employing a Machine Learning-based framework to identify relevant drivers of heatwaves.
• The use of storylines technique allows for the generation of physically consistent scenarios and the identification of relationships between drivers and extreme events.

Funding

• This research was funded by the Climate Intelligence (CLINT) project.

Citation

@article{Squintu2026Heatwaves,
  author = {Squintu, Antonello and McAdam, Ronan and Pérez-Aracil, Jorge and Peláez-Rodríguez, César and Álvarez-Castro, M. Carmen and Loukos, Harilaos and Barriopedro, David and Salcedo‐Sanz, Sancho and Scoccimarro, Enrico},
  title = {Heatwaves in a 15 °C World: Exploring remote drivers’ influence on Northern Italy with a storyline-based approach},
  journal = {Weather and Climate Extremes},
  year = {2026},
  doi = {10.1016/j.wace.2026.100949},
  url = {https://doi.org/10.1016/j.wace.2026.100949}
}