The detection of atmospheric rivers in atmospheric reanalyses and their links to British winter floods and the large-scale climatic circulation

Authors

  • David A. Lavers,

    Corresponding author
    1. Department of Meteorology, University of Reading, Reading, UK
    2. Walker Institute, University of Reading, Reading, UK
    • Corresponding author: D. A. Lavers, Department of Meteorology, University of Reading, Earley Gate, Reading RG6 6AR, UK. (d.a.lavers@reading.ac.uk)

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  • Gabriele Villarini,

    1. Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
    2. Willis Research Network, London, UK
    3. Now at IIHR-Hydroscience & Engineering, University of Iowa, Iowa City, Iowa, USA
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  • Richard P. Allan,

    1. Department of Meteorology, University of Reading, Reading, UK
    2. National Centre for Atmospheric Science, University of Reading, Reading, UK
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  • Eric F. Wood,

    1. Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
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  • Andrew J. Wade

    1. Walker Institute, University of Reading, Reading, UK
    2. Department of Geography and Environmental Science, University of Reading, Reading, UK
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Abstract

[1] Atmospheric Rivers (ARs), narrow plumes of enhanced moisture transport in the lower troposphere, are a key synoptic feature behind winter flooding in midlatitude regions. This article develops an algorithm which uses the spatial and temporal extent of the vertically integrated horizontal water vapor transport for the detection of persistent ARs (lasting 18 h or longer) in five atmospheric reanalysis products. Applying the algorithm to the different reanalyses in the vicinity of Great Britain during the winter half-years of 1980–2010 (31 years) demonstrates generally good agreement of AR occurrence between the products. The relationship between persistent AR occurrences and winter floods is demonstrated using winter peaks-over-threshold (POT) floods (with on average one flood peak per winter). In the nine study basins, the number of winter POT-1 floods associated with persistent ARs ranged from approximately 40 to 80%. A Poisson regression model was used to describe the relationship between the number of ARs in the winter half-years and the large-scale climate variability. A significant negative dependence was found between AR totals and the Scandinavian Pattern (SCP), with a greater frequency of ARs associated with lower SCP values.

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