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Lookup NU author(s): Professor Paul Davies, Professor Hayley Fowler
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2025. This study investigates the environmental conditions that resulted in the extreme rainfall and flash floods in the United Arab Emirates and Oman: 14–16 April 2024. We use a combination of numerical weather prediction modelling and observational analysis to examine the dynamics and thermodynamics of the event. Moisture convergence in the lower troposphere and a cut-off low pressure vortex coupled with high pressure over the northern Arabian Sea funnelled warm, moist air towards the Arabian Gulf. These dynamics lead to an environment that is not particularly unstable, but it is saturated in depth, with moist absolute unstable layers (MAULs) in and around areas of extreme rainfall. We apply the concept of normalized gross moist stability alongside a recently proposed four-stage conceptual model in a spatial context. We identify large-scale indicators useful for augmenting forecast models, finding an association between MAUL depth, saturation fraction, and total rainfall. The presence of deep MAULs and a saturation fraction close to one are prerequisites for heavy rainfall enhancement in the hours preceding and during the rainfall peak. We propose a new method to predict the characteristics of an extreme rainfall event using both the presence of MAULs and saturation fraction as a proxy for extremes, as either one on their own is not as beneficial. We infer that together these predictors can be used to discriminate between embedded convection in fronts versus isolated convective events producing the extremes.
Author(s): Davies PA, Flack DLA, Pirret JSR, Fowler HJ
Publication type: Article
Publication status: Published
Journal: Weather and Climate Extremes
Year: 2026
Volume: 51
Print publication date: 01/03/2026
Online publication date: 11/12/2025
Acceptance date: 10/12/2025
Date deposited: 22/12/2025
ISSN (electronic): 2212-0947
Publisher: Elsevier BV
URL: https://doi.org/10.1016/j.wace.2025.100846
DOI: 10.1016/j.wace.2025.100846
Data Access Statement: Data will be made available on request.
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