Davies et al. (2025) Application of the Davies four-stage conceptual model for life-threatening rainfall extremes on the April 2024 United Arab Emirates and Oman floods

Identification

• Journal: Weather and Climate Extremes
• Year: 2025
• Date: 2025-12-11
• Authors: Paul Davies, David L. A. Flack, Jennifer Pirret, Hayley J. Fowler
• DOI: 10.1016/j.wace.2025.100846

Research Groups

• Met Office, Exeter, UK
• School of Engineering, Newcastle University, Newcastle upon Tyne, UK
• Tyndall Centre for Climate Change Research, Newcastle upon Tyne, UK

Short Summary

This study investigates the environmental conditions leading to the April 2024 UAE and Oman floods, applying a four-stage conceptual model to numerical weather prediction (NWP) models and observations. It finds that a combination of deep Moist Absolute Unstable Layers (MAULs) and high saturation fractions are key indicators for predicting extreme rainfall events, distinguishing between organised and isolated convection.

Objective

• To investigate the utility and applicability of the Davies et al. (2024) four-stage conceptual model for extreme rainfall in a tropical forecasting framework, specifically for the April 2024 UAE and Oman floods.
• To determine if proxies (MAULs, saturation fraction) exist for identifying extreme rainfall events prior to their occurrence.
• To examine the relationship between the conceptual model, Normalized Gross Moist Stability (NGMS), and saturation fraction.

Study Configuration

• Spatial Scale: United Arab Emirates and Oman. Global model resolution of approximately 10 km grid squares horizontally, with 70 hybrid vertical levels up to 80 km, and MAUL identification limited to 6 km altitude.
• Temporal Scale: Extreme rainfall event from 14–16 April 2024. Forecasts initiated at 00 UTC from 14–16 April 2024, with a maximum lead time of 24 hours. Analysis of 3-hour precipitation accumulations.

Methodology and Data

• Models used:
  • Met Office operational Unified Model (UM) global configuration (suite 45, version 11.2)
  • Global Atmosphere version 8 (GA8) dynamical core (ENDGAME)
  • Joint UK Land Environment Simulator (JULES) GL9 configuration
  • NEMO ocean model (GO6 configuration, 0.25° resolution)
  • GSI8 sea ice model
• Data sources:
  • Numerical Weather Prediction (NWP) model outputs (Met Office UM)
  • MODIS visible satellite imagery
  • GPM IMERG product for precipitation rate
  • NOAA worldview
  • Radiosonde ascents from Seeb International Airport (Oman) and Abu Dhabi Airport (UAE)

Main Results

• The extreme rainfall event was driven by moisture convergence in the lower troposphere and a cut-off low-pressure vortex coupled with high pressure, funneling warm, moist air towards the Arabian Gulf, characteristic of an Active Red Sea Trough (ARST).
• The environment was saturated in depth with Moist Absolute Unstable Layers (MAULs) present in and around areas of extreme rainfall.
• A strong association was found between MAUL depth, saturation fraction, and total rainfall. Deep MAULs (≥2 km) and saturation fractions close to one (e.g., >0.9) are prerequisites for heavy rainfall enhancement.
• The deepest MAULs are typically located just ahead of or partially cover regions of the largest rainfall, and are qualitatively associated with the largest saturation fractions.
• A new method is proposed using the combination of MAUL presence/depth and saturation fraction as a proxy for extreme rainfall, which is more beneficial than either predictor alone. This combination can help discriminate between organised convective events (deep MAULs, high saturation fraction) and isolated thunderstorms (deep MAULs, mid-range saturation fraction around 0.6).

Contributions

• Enhanced the Davies et al. (2024) four-stage, three-layered conceptual model for precipitation extremes by applying it to NWP models and observations of a real-world extreme event.
• Demonstrated the global applicability of the conceptual model, extending its utility to tropical regions and Rex-like vortex systems (ARSTs).
• Developed a new method for identifying extreme precipitation risks by combining MAUL depth and saturation fraction, providing a more robust indicator than either parameter alone.
• Provided a tool to help forecasters characterize extreme rainfall events (e.g., distinguishing between organised vs. isolated convection), thereby improving early warnings and accounting for model uncertainties.

Funding

• FUTURE-STORMS (NE/R01079X/1)
• Co-Centre for Climate+Biodiversity+Water (NE/Y006496/1) funded by UKRI

Citation

@article{Davies2025Application,
  author = {Davies, Paul and Flack, David L. A. and Pirret, Jennifer and Fowler, Hayley J.},
  title = {Application of the Davies four-stage conceptual model for life-threatening rainfall extremes on the April 2024 United Arab Emirates and Oman floods},
  journal = {Weather and Climate Extremes},
  year = {2025},
  doi = {10.1016/j.wace.2025.100846},
  url = {https://doi.org/10.1016/j.wace.2025.100846}
}