Lalić et al. (2026) Tracking Seasonal Transitions Using a Meteorological Seasonality Index

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Identification

• Journal: International Journal of Climatology
• Year: 2026
• Date: 2026-06-13
• Authors: Branislava Lalić, Ana Firanj Sremac
• DOI: 10.1002/joc.70447

Research Groups

Not specified in the provided text.

Short Summary

The study introduces the Normalised Daily Temperature Range (NDTR), a physically based index that defines seasonal boundaries based on atmospheric regime transitions rather than fixed calendar dates, significantly reducing intra-seasonal meteorological variability.

Objective

• To develop and validate a continuous, threshold-independent framework (NDTR) for identifying seasonal transitions and durations using routine temperature observations.

Study Configuration

• Spatial Scale: Euro-Mediterranean region (applied at both site and regional scales).
• Temporal Scale: Annual cycle of near-surface temperature.

Methodology and Data

• Models used: Normalised Daily Temperature Range (NDTR) index; smoothed NDTR curves using extreme values and inflection points for boundary identification.
• Data sources: ERA5-Land reanalysis data; vegetation indicators (Leaf Area Index [LAI], Enhanced Vegetation Index [EVI]); observed phenology data.

Main Results

• Meteorological Consistency: NDTR-defined seasons reduced intra-seasonal variability in temperature and dew-point metrics by 12%–14% compared to calendar-based seasons, with reductions reaching 28% during transition seasons.
• Phenological Coherence:
  • Start of Season (SOS): NDTR-derived onset occurs later than observed (median difference of ~10 days at low elevations and 3–4 days at mid-elevations).
  • End of Season (EOS): NDTR-derived onset occurs earlier than observed (differences ranging from 12 days above 700 m to 22.8 days at low elevations).
• Regional Dynamics: In the Euro-Mediterranean region, the NDTR reveals a decrease in winter duration (6–21 days) and an increase in summer duration (4–12 days).

Contributions

• Establishes a physically based, threshold-independent method for seasonal classification that is independent of biosphere-specific signals.
• Provides a tool for improved monitoring and forecasting of seasonal dynamics for climate analysis and health systems.

Funding

Not specified in the provided text.

Citation

@article{Lalić2026Tracking,
  author = {Lalić, Branislava and Sremac, Ana Firanj},
  title = {Tracking Seasonal Transitions Using a Meteorological Seasonality Index},
  journal = {International Journal of Climatology},
  year = {2026},
  doi = {10.1002/joc.70447},
  url = {https://doi.org/10.1002/joc.70447}
}