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Physical factors influencing regional precipitation variability attributed using an airmass trajectory method

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De Leeuw, J., Methven, J. and Blackburn, M. (2017) Physical factors influencing regional precipitation variability attributed using an airmass trajectory method. Journal of Climate, 30 (18). pp. 7359-7378. ISSN 1520-0442

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To link to this item DOI: 10.1175/JCLI-D-16-0547.1

Abstract/Summary

A novel Lagrangian framework is developed to attribute monthly precipitation variability to physical processes. Precipitation variability is partitioned into a combination of 5 factors: air mass origin location, origin surface temperature variation, ascent intensity, mass fraction of ascending air and the number of ‘wet’ analysis times per month (> 1 mm/6hrs). Precipitation in a target region is linked to ‘origin’ locations of air masses where the water vapour mixing ratio was last set by boundary layer moistening and is a maximum along back trajectories. Applying the technique to the England and Wales region, the factors together account for 83-89% of the observed summer precipitation variability. The dominant contributor is the number of ‘wet’ analyses, which is shown to be associated with cyclone statistics. The wettest summer months are mainly associated with anomalous cyclone duration rather than the number of cyclones. In addition, surface temperature and saturation humidity at the ‘origin’ locations are found to be below their climatological averages (1979-2013). Therefore the direct thermodynamic effect of anomalous surface temperature on marine boundary layer humidity acts to reduce monthly precipitation anomalies. The decadal precipitation change between phases of the Atlantic Multidecadal Oscillation is approximately 20% of the interannual variability between summer months. Changes in cyclone statistics have an effect six times larger than the direct thermodynamic factor in both monthly and decadal precipitation variability.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > NCAS
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:67132
Publisher:American Meteorological Society

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