Riboldi et al. (2026) Storm Boris (2024) in the current and future climate: a dynamics-centered contextualization, and some lessons learnt

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Repository for Publications and Research Data (ETH Zurich)
• Year: 2026
• Date: 2026-01-12
• Authors: Jacopo Riboldi, Robin Noyelle, Ellina Agayar, Hanin Binder, Marc Federer, Katharina Hartmuth, Michael Armand Sprenger, Iris Thurnherr, Selvakumar Vishnupriya
• DOI: 10.3929/ethz-c-000793072

Research Groups

Information not provided in the paper text.

Short Summary

This study investigates how "Boris-like" storms and their associated precipitation will change in a high warming scenario by comparing conditional (analog-based) and unconditional (statistics-based) attribution methods. It finds that while same-season analogs may show less precipitation, non-season-restricted analogs exhibit a seasonality shift and increased precipitation in a warmer climate, contrasting with the general intensification found by statistics-based approaches.

Objective

• To understand how the characteristics of heavy precipitation events, exemplified by Storm Boris, will change in an end-of-the-century high warming scenario, considering both thermodynamic and dynamic influences.
• To compare the outcomes of conditional (analog-based) and unconditional (statistics-based) methodologies for attributing extreme precipitation events to anthropogenic global warming.

Study Configuration

• Spatial Scale: Central Europe (case study of Storm Boris), large-scale circulation patterns over Europe.
• Temporal Scale: Present-day climate versus an end-of-the-century high warming scenario. Analysis of seasonal and yearly precipitation maxima.

Methodology and Data

• Models used: CESM1 (Community Earth System Model version 1)
• Data sources: Large ensemble simulations from CESM1 for present-day and future climates. Key circulation features (upper-level potential vorticity (PV) cutoff, surface cyclone track, forcing for ascent) are identified to define event characteristics and find analogs.

Main Results

• The quality of circulation analogs for heavy precipitation events is substantially improved by the combined use of upper-level potential vorticity (PV) and a surface cyclone identification algorithm.
• Analogs of Storm Boris restricted to the same season in a warmer climate exhibit, on average, less precipitation due to an overall weakening of upper-level-driven ascent over Europe.
• Analogs of Storm Boris not restricted to the same season show a seasonality shift in a warmer climate: they become less frequent at the end of the warm season and more frequent in the shoulder seasons, where they exhibit an increase in mean precipitation.
• An unconditional, statistics-based approach focusing on seasonal and yearly precipitation maxima recovers the expected intensification of extreme precipitation in a warmer climate, but at the cost of considering events that may not share the same dynamics as Storm Boris.
• The study highlights the significant sensitivity of attribution outcomes to implicit and explicit methodological choices and emphasizes the importance of process understanding.

Contributions

• Proposes a two-step methodology for identifying more reliable circulation analogs of heavy precipitation events by integrating upper-level potential vorticity and surface cyclone characteristics.
• Provides a systematic comparison of conditional (analog-based) and unconditional (statistics-based) approaches for attributing extreme precipitation events to climate change, revealing their respective strengths and limitations.
• Demonstrates the complex interplay of thermodynamic and dynamic changes on extreme precipitation, including potential seasonality shifts for specific storm types in a warming climate.
• Emphasizes the critical role of process understanding and the systematic comparison of different attribution approaches for investigating the impact of climate change on specific weather extremes.

Funding

Information not provided in the paper text.

Citation

@article{Riboldi2026Storm,
  author = {Riboldi, Jacopo and Noyelle, Robin and Agayar, Ellina and Binder, Hanin and Federer, Marc and Hartmuth, Katharina and Sprenger, Michael Armand and Thurnherr, Iris and Vishnupriya, Selvakumar},
  title = {Storm Boris (2024) in the current and future climate: a dynamics-centered contextualization, and some lessons learnt},
  journal = {Repository for Publications and Research Data (ETH Zurich)},
  year = {2026},
  doi = {10.3929/ethz-c-000793072},
  url = {https://doi.org/10.3929/ethz-c-000793072}
}