Wang et al. (2025) Key drivers and predictability of the unprecedented 2024 United Arab Emirates flood

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

Identification

• Journal: Environmental Research Letters
• Year: 2025
• Date: 2025-12-23
• Authors: Jingyu Wang, Xianfeng Wang, Shuyu Sun, Wen Yonggang, Raju Pathak, Luojie Dong, Edward Park, Ibrahim Hoteit
• DOI: 10.1088/1748-9326/ae3096

Research Groups

Not explicitly stated in the provided abstract.

Short Summary

This study investigates the extreme rainfall event that struck the Arabian Peninsula in mid-April 2024, identifying a rare convergence of a strengthened Somali low-level jet and an unusually strong Arabian Cold Vortex as the primary drivers, while highlighting significant underestimation by forecast models.

Objective

• To investigate the mesoscale convective system responsible for the extreme rainfall event in the Arabian Peninsula in mid-April 2024.

Study Configuration

• Spatial Scale: Arabian Peninsula, specifically the United Arab Emirates.
• Temporal Scale: Mid-April 2024 (event period); 24 hours (event duration); 1940–2024 (long-term reanalysis period).

Methodology and Data

• Models used: 11 models from the International Grand Global Ensemble (TIGGE) archive.
• Data sources: Multiple precipitation datasets, state-of-the-art storm-tracking algorithm, long-term reanalysis data.

Main Results

• The mid-April 2024 event was the most intense daily rainfall event ever recorded in the Arabian Peninsula.
• Peak intensity occurred on 16 April, contributing more than 70% of the total event rainfall.
• The event was driven by the rare convergence of an enhanced Somali low-level jet (SLLJ) and an unusually strong Arabian Cold Vortex in the mid-troposphere.
• This specific combination of drivers is extremely rare, observed on only 0.006% of all days in the 1940–2024 daily record.
• Forecasts from 11 TIGGE models consistently underestimated rainfall with a mean bias of −63.6%.
• Model underestimation was attributed to severe underestimation of the SLLJ and moderate overestimation of 500 hPa geopotential height.

Contributions

• Identified the specific, rare synoptic-scale drivers (enhanced SLLJ and strong Arabian Cold Vortex) responsible for an unprecedented extreme rainfall event in an arid region.
• Quantified the significant underperformance of state-of-the-art forecast models in predicting such extreme events, highlighting specific deficiencies in representing moisture dynamics and upper-level disturbances.
• Underscored the increasing threat of extreme precipitation in arid regions under a changing climate and the urgent need for model improvements.

Funding

Not explicitly stated in the provided abstract.

Citation

@article{Wang2025Key,
  author = {Wang, Jingyu and Wang, Xianfeng and Sun, Shuyu and Yonggang, Wen and Pathak, Raju and Dong, Luojie and Park, Edward and Hoteit, Ibrahim},
  title = {Key drivers and predictability of the unprecedented 2024 United Arab Emirates flood},
  journal = {Environmental Research Letters},
  year = {2025},
  doi = {10.1088/1748-9326/ae3096},
  url = {https://doi.org/10.1088/1748-9326/ae3096}
}