Fathalli et al. (2023) Weather regimes and rainfall over Tunisia in a multi-model ensemble versus a multi-member ensemble

Identification

• Journal: Climate Dynamics
• Year: 2023
• Authors: Bilel Fathalli, Benjamin Pohl, Pere Quintana Seguí, Yves Tramblay, Albin Ullmann, Thierry Castel
• DOI: 10.1007/s00382-022-06656-9

Research Groups

• Tunisian Ministry of Agriculture, Water Resources and Fisheries, Tunis, Tunisia
• Centre de Recherches de Climatologie, UMR6282 Biogéosciences, CNRS/Université de Bourgogne Franche-Comté, Dijon, France
• Observatori de l’Ebre (OE), Universitat Ramon LLull-CSIC, Roquetes, Spain
• HydroSciences Montpellier (Univ. Montpellier, CNRS, IRD), Montpellier, France

Short Summary

This study establishes a 7-regime Weather Regime (WR) classification for the North African-Mediterranean domain and evaluates the performance of WRF multi-member and Euro-Cordex multi-model ensembles in simulating these regimes and their associated daily rainfall over Tunisia. Results show that model performance and uncertainty are highly regime-dependent, with wet conditions driven by WR5 and WR3, and the WRF ensemble generally outperforming Euro-Cordex.

Objective

• To investigate the links between daily rainfall over Tunisia and large-scale atmospheric conditions by establishing a Weather Regime (WR) classification over a North African-Mediterranean domain.
• To evaluate the capabilities of a WRF 10-member ensemble and a Euro-Cordex regional climate simulations ensemble in reproducing the ERA-Interim WR characteristics and the main features of observed rainfall over Tunisia for each WR.

Study Configuration

• Spatial Scale: North African-Mediterranean domain (for WR classification); focus area: Tunisia (for rainfall evaluation).
• Temporal Scale: Daily resolution; 20-year period (1992–2011); seasonal analysis (DJF, JJA).

Methodology and Data

• Models used: Weather Research and Forecasting (WRF) model (10-member ensemble); Euro-Cordex Regional Climate Simulations ensemble.
• Data sources: Reanalysis (ERA-Interim, ERA5); Satellite-gauge merged rainfall products (MSWEP V2.2, CHIRPS V2.0, GPCP); Local high-resolution observational rainfall dataset (SAFRAN_Tun); Mean Sea Level Pressure (MSLP) field (used for WR classification); Mediterranean Sea SST Analysis L4; Daily North Atlantic Oscillation (NAO) index.

Main Results

• Seven Weather Regimes (WRs) were identified using the ERA-Interim Mean Sea Level Pressure field over the 1992–2011 period.
• The models demonstrated the best performance in reproducing the characteristics of the two wintertime NAO-like WRs (WR1 and WR3).
• Wet and extremely wet conditions, mainly observed north of Tunisia, are primarily driven by WR5 and WR3 (and partly WR7), which feature strong negative MSLP anomalies and anomalous cyclonic circulation impacting the region.
• Anomalously dry conditions prevailing across the entire country are particularly associated with WR1.
• The WRF multi-member ensemble generally showed better performance and smaller spread compared to the Euro-Cordex multi-model ensemble across all WRs.
• Model errors (annual and DJF) are regime-dependent, with the highest errors frequently obtained during WR1 and the lowest errors during WR3 and WR7.
• Model uncertainties, quantified by the Signal-to-Noise ratio, are lower during the winter season (DJF) than during the summer season (JJA).
• The internal variability of simulated rainfall within the WRF ensemble is persistently smaller than the inter-model spread observed in the Euro-Cordex ensemble for all WRs and timescales.

Contributions

• Provides the first systematic investigation linking daily rainfall variability over Tunisia directly to a comprehensive classification of large-scale atmospheric Weather Regimes established over the North African-Mediterranean domain.
• Offers a rigorous comparison of two distinct ensemble approaches (multi-member internal variability vs. multi-model structural uncertainty) in simulating WRs and their regional rainfall impacts.
• Demonstrates that model performance, error intensity, and uncertainty are strongly dependent on the specific atmospheric circulation regime, providing critical context for interpreting regional climate projections in North Africa.

Funding

• This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Citation

@article{Fathalli2023Weather,
  author = {Fathalli, Bilel and Pohl, Benjamin and Quintana‐Seguí, Pere and Tramblay, Yves and Ullmann, Albin and Castel, Thierry},
  title = {Weather regimes and rainfall over Tunisia in a multi-model ensemble versus a multi-member ensemble},
  journal = {Climate Dynamics},
  year = {2023},
  doi = {10.1007/s00382-022-06656-9},
  url = {https://doi.org/10.1007/s00382-022-06656-9}
}

Generated by BiblioAssistant using gemini-flash-latest (Google API)