Bartfeld et al. (2026) Intrinsic predictability of heavy precipitation influenced by atmospheric rivers in the Western Iberian Peninsula

Identification

• Journal: Weather and Climate Extremes
• Year: 2026
• Date: 2026-04-07
• Authors: Ehud Bartfeld, A. M. Ramos, Assaf Hochman
• DOI: 10.1016/j.wace.2026.100895

Research Groups

• Fredy and Nadine Herrmann Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
• Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany

Short Summary

This study investigates the dynamics and intrinsic predictability of Heavy Precipitation Events (HPE) in Portugal, emphasizing the role of Atmospheric Rivers (AR). It reveals that AR-linked HPE are more intense and predictable, primarily driven by strong low-level winds, with high-predictability events associated with well-defined, deep extra-tropical cyclones.

Objective

• To investigate how Atmospheric Rivers (AR) influence the dynamics and intrinsic predictability of Heavy Precipitation Events (HPE) in Portugal, and to demonstrate that a single intrinsic variable can be used to map the predictability of such events.

Study Configuration

• Spatial Scale:
  • Red box (34°–44°N; 6°–10°W): Mainland Portugal, used for aggregating total daily precipitation and Integrated Water Vapor Transport (IVT).
  • Blue box (35°–45°N; 10°–30°W): Eastern North Atlantic Ocean, west of Portugal, used for computing dynamical systems metrics.
• Temporal Scale: Extended winter season (October–March) for the period 1959–2023.

Methodology and Data

• Models used: Dynamical systems framework (combining extreme value theory and Poincaré recurrences) for local dimension (d) and inverse persistence (θ) metrics; objective weather pattern classification.
• Data sources: ERA5 reanalysis (European Center for Medium-Range Weather Forecasts - ECMWF).
  • Spatial resolution: 0.25° × 0.25°
  • Temporal resolution: Hourly (daily means used for analysis)
  • Variables: Total daily precipitation, Integrated Water Vapor Transport (IVT) (kg m⁻¹ s⁻¹), horizontal wind magnitudes (m s⁻¹) at 1000 to 300 hPa.

Main Results

• Atmospheric River (AR)-linked Heavy Precipitation Events (HPE) exhibit 36% higher precipitation intensity than non-AR events.
• This higher intensity is primarily attributed to stronger low-level winds that increase moisture fluxes, rather than a greater total column water vapor content.
• High-predictability events are associated with well-defined, deep extra-tropical cyclones near 50°N, 15°W, whose mean sea-level pressure anomaly is approximately -40.6 hPa, nearly double that of low-predictability systems (-20.6 hPa).
• High-predictability events exhibit enhanced jet stream interaction, more coherent Rossby wave patterns, and average precipitation intensities approximately 80% greater (mean R-intensity of 70) than those of low-predictability events (mean R-intensity of 39).
• The extreme mid-December 2022 event, which caused record-breaking rainfall (120.3 mm in 24 hours), transitioned from a more predictable to a less predictable state as it intensified.

Contributions

• Integrates Atmospheric River (AR) diagnostics with a dynamical systems perspective to provide a novel understanding of Heavy Precipitation Events (HPE) dynamics and intrinsic predictability.
• Offers a process-based foundation for enhanced forecasts in Portugal and similar mid-latitude coastal regions by identifying flow-dependent measures of forecast confidence.
• Demonstrates that wind magnitude, rather than moisture content alone, is the primary driver of Integrated Water Vapor Transport (IVT) during AR-linked extreme precipitation events.
• Provides a framework for identifying "windows of opportunity" for sub-seasonal to seasonal prediction of extremes by linking large-scale flow organization to predictable intervals.

Funding

• The Israel Science Foundation (grant #978/23)
• Planning and Budgeting Committee of the Israeli Council for Higher Education, under the ‘MedWORLD’ Consortium
• COST Actions CA19109 ‘MedCyclones’
• COST Actions CA22162 ‘FutureMed’
• AMOTHEC project (DRI/India/0098/2020; DOI: 10.54499/DRI/India/0098/2020), funded by the Fundação para a Ciência e a Tecnologia (FCT) I.P./ MCTES, Israel
• Helmholtz ‘‘Changing Earth — Sustaining our Future’’ program

Citation

@article{Bartfeld2026Intrinsic,
  author = {Bartfeld, Ehud and Ramos, A. M. and Hochman, Assaf},
  title = {Intrinsic predictability of heavy precipitation influenced by atmospheric rivers in the Western Iberian Peninsula},
  journal = {Weather and Climate Extremes},
  year = {2026},
  doi = {10.1016/j.wace.2026.100895},
  url = {https://doi.org/10.1016/j.wace.2026.100895}
}