Thomas et al. (2025) The Role of Internal Variability in Seasonal Hindcast Trend Errors

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

Identification

• Journal: Journal of Climate
• Year: 2025
• Date: 2025-07-22
• Authors: Rhidian Thomas, Tim Woollings, Nick Dunstone
• DOI: 10.1175/jcli-d-24-0367.1

Research Groups

Not specified in the provided text.

Short Summary

The study demonstrates that seasonal hindcast models exhibit a wide range of multidecadal trends due to short-term variability, indicating that benchmarking against observations using only the ensemble mean can lead to a misdiagnosis of model trend errors.

Objective

• To investigate the role of short-time-scale variability in contributing to long-term trends in seasonal and decadal hindcast models and to evaluate whether the ensemble mean is a sufficient metric for comparison with observed trends.

Study Configuration

• Spatial Scale: Global (including specific focus on land surface temperatures and extratropical jet streams).
• Temporal Scale: 1981–2022.

Methodology and Data

• Models used: A single-model coupled hindcast ensemble.
• Data sources: Hindcast data; a distribution of 10,000 trends was generated by randomly sampling a single ensemble member for each year.

Main Results

• Hindcast models support a wide range of trends in large-scale climate features, even when sampled at short leads of 1–3 months post-initialization.
• The spread in global surface temperature trends is approximately 1/6 of the total observed warming over the 1981–2022 period, primarily driven by seasonal temperature variability over land.
• While the models support observed poleward shifts of the jet streams, the magnitude of these shifts varies significantly across the ensemble.

Contributions

• The research establishes that accounting for the full range of model trends, rather than relying solely on the ensemble mean, is essential for a fair comparison with observations.
• It proposes the use of hindcast trend distributions as a tool for studying multidecadal climate trends using existing large-ensemble hindcast data.

Funding

Not specified in the provided text.

Citation

@article{Thomas2025Role,
  author = {Thomas, Rhidian and Woollings, Tim and Dunstone, Nick},
  title = {The Role of Internal Variability in Seasonal Hindcast Trend Errors},
  journal = {Journal of Climate},
  year = {2025},
  doi = {10.1175/jcli-d-24-0367.1},
  url = {https://doi.org/10.1175/jcli-d-24-0367.1}
}