Garderen et al. (2026) The essential role of conditional attribution in understanding complex extreme weather

Identification

• Journal: Nature Communications
• Year: 2026
• Date: 2026-02-17
• Authors: Linda van Garderen, Dalena León-FonFay
• DOI: 10.1038/s41467-026-69056-1

Research Groups

• Institute for Marine and Atmospheric Research Utrecht, Utrecht University, The Netherlands
• Institute of Coastal Systems - Analysis and Modeling, Helmholtz-Zentrum Hereon, Germany

Short Summary

This comment emphasizes the critical role of conditional attribution in understanding complex extreme weather events, using the 2024 Valencia flash flood as a striking example of how human-driven climate warming intensified the storm's rainfall intensities beyond thermodynamic expectations. It advocates for an integrated approach combining conditional and unconditional attribution for comprehensive impact assessments.

Objective

• To highlight the essential role and unique insights provided by conditional attribution in understanding the physical mechanisms and climate change influence on complex, convective extreme weather events.
• To advocate for the integration of conditional (storyline) and unconditional (statistical) attribution approaches for a more comprehensive and societally relevant extreme weather attribution science.

Study Configuration

• Spatial Scale: Local to regional (e.g., Valencia, Spain; storm-scale dynamics).
• Temporal Scale: Event-specific (e.g., hours for the Valencia rainfall event); also discusses the evolution of attribution science over two decades.

Methodology and Data

• Models used: High-resolution regional models (as discussed in the referenced Calvo-Sancho et al. study for process-based attribution).
• Data sources: Observations, observation-based datasets (e.g., reanalyses) for model validation; satellite imagery (as shown in Fig. 1).

Main Results

• Conditional attribution, exemplified by the Valencia flash flood study, effectively uncovers climate-change signals even in highly convective, microscale extreme events that challenge traditional models.
• The Valencia study demonstrated that human-driven climate warming significantly intensified the storm, with precipitation increases exceeding the approximately 7% per kelvin expected from Clausius–Clapeyron scaling due to nonlinear storm dynamics.
• Conditional attribution provides unique insights into how warming alters storm-scale dynamics, moisture pathways, and local feedbacks, which are nearly inaccessible through unconditional approaches alone.
• An integrated approach combining both conditional (process-based, event-specific) and unconditional (statistical, probability-based) attribution methods is crucial for comprehensive impact assessments and translating scientific knowledge into societal resilience.

Contributions

• Provides a timely commentary on the significance of conditional attribution for understanding complex extreme weather events, particularly in light of recent devastating events like the Valencia flash flood.
• Articulates the distinct yet complementary roles of conditional and unconditional attribution methods, advocating for their integration to advance attribution science.
• Emphasizes the importance of model validation against observations for robust attribution results, especially for high-resolution, process-based studies.
• Highlights the societal relevance of bridging physical understanding and probability shifts in attribution science for adaptation strategies.

Funding

Not specified in the provided text.

Citation

@article{Garderen2026essential,
  author = {Garderen, Linda van and León-FonFay, Dalena},
  title = {The essential role of conditional attribution in understanding complex extreme weather},
  journal = {Nature Communications},
  year = {2026},
  doi = {10.1038/s41467-026-69056-1},
  url = {https://doi.org/10.1038/s41467-026-69056-1}
}