Lima et al. (2025) STABLE: An open-source atmospheric blocking and subtropical ridge detection system

Identification

• Journal: Environmental Modelling & Software
• Year: 2025
• Date: 2025-10-10
• Authors: Miguel M. Lima, Pedro M. Sousa, Tahimy Fuentes-Alvarez, Carlos Ordóñez, Ricardo García‐Herrera, David Barriopedro, Pedro M. M. Soares, Ricardo M. Trigo
• DOI: 10.1016/j.envsoft.2025.106729

Research Groups

• Instituto Dom Luiz (IDL), Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
• Instituto Português do Mar e da Atmosfera (IPMA), Lisboa, Portugal
• Departamento de Física de la Tierra y Astrofísica, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, Madrid, Spain
• Instituto de Geociencias (IGEO), Consejo Superior de Investigaciones Científicas–Universidad Complutense de Madrid (CSIC–UCM), Madrid, Spain
• Departamento de Meteorologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil

Short Summary

This paper introduces STABLE, an open-source Python algorithm for detecting and tracking atmospheric blockings (ABs) and subtropical ridges (SRs), demonstrating improved accuracy and adaptability over previous methods through validation with reanalysis data.

Objective

• To develop and validate STABLE, an open-source Python algorithm for the comprehensive identification, classification, and spatio-temporal tracking of atmospheric blockings (ABs) and subtropical ridges (SRs), offering customizable refinements over existing methodologies.

Study Configuration

• Spatial Scale: Global/hemispheric, with data tested at 0.25, 1, and 2.5 degrees of resolution; validation performed using 1 degree × 1 degree grid.
• Temporal Scale: Daily spatial structures; validation period 1991–2020; ERA5 data retrieved for 1950–2020; minimum event duration of 4 days.

Methodology and Data

• Models used: STABLE algorithm (Python-based), building upon the Tibaldi-Molteni index, extended by Scherrer et al. (2006), and further improved by Sousa et al. (2021).
• Data sources:
  • ERA5 global reanalysis (Hersbach et al., 2020) at 1 degree × 1 degree grid (1950–2020, with 1991–2020 for validation).
  • Japanese 55-year reanalysis (JRA-55, Kobayashi et al., 2015) at 2.5 degrees × 2.5 degrees grid (for sensitivity tests).
  • NCEP/NCAR 40-year reanalysis (Kalnay et al., 1996) at 2.5 degrees × 2.5 degrees grid (for sensitivity tests).
  • Input variables: 500 hPa geopotential height (Z500). For near-surface impacts: 3-hour Z500, 3-hour mean sea level pressure (MSLP), 3-hour 850 hPa temperature, and hourly precipitation data from ERA5.

Main Results

• STABLE successfully identifies and tracks high-pressure systems, distinguishing between subtropical ridges (SRs) and various atmospheric blocking (AB) types (Rex, Omega, Hybrid, Polar).
• Customizable refinements introduced in STABLE lead to:
  • Zonally varying subtropical boundary (LATmin): Increased daily occurrences and events by 11% in the Northern Hemisphere (NH) and 29% in the Southern Hemisphere (SH), particularly for SRs (+26% NH) and omega/hybrid ABs (SH). This approach emphasizes anomalous subtropical intrusions.
  • Refined polar blocking criteria (using GHGN): Resulted in a more confined and consistent identification of polar ABs, with decreases of approximately 5% in daily patterns/events (NH) and approximately 11% (SH), and approximately 30% reduction in "Rex (polar)" type. This filters open structures, emphasizing closed-circulation high-pressure systems.
  • Advanced hybrid blocking classification: Reclassified approximately 3000 daily patterns as hybrids in the NH (+78% increase) and approximately 150 in the SH (+21%), improving the morphological classification of transitional structures.
• Sensitivity tests showed identical catalogues across different operating systems, minor differences across reanalyses (JRA-55 yielded slightly lower counts), and higher spatial resolution (1 degree vs 2.5 degrees) led to slightly fewer structures (approximately 2–4% reduction) due to splitting large-scale systems.
• Near-surface impact analysis revealed that modified SRs lead to intensified precipitation anomalies (up to approximately 3 mm/day) and stronger anticyclonic surface patterns over western Europe. Modified polar ABs showed more pronounced positive temperature anomalies over the high-pressure center.

Contributions

• Development of STABLE, an open-source, user-friendly, Python-based algorithm for comprehensive identification, classification, and tracking of ABs and SRs.
• Introduction of novel, customizable methodological refinements: zonally varying subtropical boundary, refined polar blocking criteria, and an advanced hybrid blocking classification scheme.
• Improved accuracy and adaptability in capturing high-pressure events compared to previous state-of-the-art methods (e.g., Sousa et al., 2021), while maintaining replicability.
• Provides a flexible framework for researchers to conduct customizable studies on atmospheric dynamics, climate variability, historical trends, future projections, and region-specific impact assessments.
• The code and example data are freely available, promoting transparency, traceability, and community collaboration.

Funding

• Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC): UIDB/50019/2023 and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020).
• PhD MIT Portugal MPP2030-FCT programme grant PRT/BD/154680/2023 (M. M. Lima).
• MALONE (PID2021-122252OB-I00) project, funded by MICIU/AEI/10.13039/501100011033 and ERDF, EU.

Citation

@article{Lima2025STABLE,
  author = {Lima, Miguel M. and Sousa, Pedro M. and Fuentes-Alvarez, Tahimy and Ordóñez, Carlos and García‐Herrera, Ricardo and Barriopedro, David and Soares, Pedro M. M. and Trigo, Ricardo M.},
  title = {STABLE: An open-source atmospheric blocking and subtropical ridge detection system},
  journal = {Environmental Modelling & Software},
  year = {2025},
  doi = {10.1016/j.envsoft.2025.106729},
  url = {https://doi.org/10.1016/j.envsoft.2025.106729}
}