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A new conceptual model for understanding and predicting life-threatening rainfall extremes

Lookup NU author(s): Professor Paul Davies, Professor Hayley Fowler, Dr Roberto Villalobos Herrera

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

Abstract

© 2024The motivation of our study is to provide forecasters and users complementary guidance and tools to identify and predict atmospheric conditions that could lead to life-threatening flash floods. Using hourly and sub-hourly rainfall datasets, proximity radiosondes, ERA5 reanalysis of extreme rainfall events in the UK during 2000–2020, and case studies in 2021, we observe a three-layered atmospheric structure, consisting of Moist Absolute Unstable Layers (MAULs) embedded in a conditional unstable layer sandwiched between a stable upper layer and a near-stable low layer. Based on our analysis, we propose a conceptual model to describe the atmospheric properties of a ‘rainfall extreme’ environment, with a particular focus on the thermodynamics associated with sub-hourly rainfall production processes. We then set this model within a wider framework to describe the precursor synoptic and mesoscale environments necessary for sub-hourly rainfall extremes in the mid-latitudes. We show that evolution of the Omega block and Rex Vortex couplet provides the optimal environmental conditions for sub-hourly rainfall extremes. These results provide the potential to develop a ‘4-stage’ warning system to assist in the identification and forecasting of life threatening short-duration extreme rainfall intensities and flash floods.

Publication metadata

Author(s): Davies PA, Fowler HJ, Villalobos Herrera R, Slingo J, Flack DLA, Taszarek M

Publication type: Article

Publication status: Published

Journal: Weather and Climate Extremes

Year: 2024

Volume: 45

Print publication date: 01/09/2024

Online publication date: 10/06/2024

Acceptance date: 24/05/2024

Date deposited: 15/07/2024

ISSN (print): 2212-0947

Publisher: Elsevier B.V.

URL: https://doi.org/10.1016/j.wace.2024.100696

DOI: 10.1016/j.wace.2024.100696

Data Access Statement: Data will be made available on request.

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