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Earlier awareness of extreme winter precipitation across the western Iberian Peninsula

Lavers, D. A. ORCID:, Richardson, D. S., Ramos, A. M., Zsoter, E., Pappenberger, F. and Trigo, R. M. (2018) Earlier awareness of extreme winter precipitation across the western Iberian Peninsula. Meteorological Applications, 25 (4). pp. 622-628. ISSN 1469-8080

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To link to this item DOI: 10.1002/met.1727


Extreme winter precipitation across the western Iberian Peninsula is frequently connected to atmospheric rivers, which are bands of intense water vapour transport (integrated vapour transport, IVT). Recent research over Western Europe has shown that by using the IVT forecasts in the form of the extreme forecast index (EFI), a tool that identifies anomalous conditions, it is possible to provide earlier awareness of extreme precipitation events than by using the precipitation EFI directly. The aim of the present paper is to assess these findings further by identifying the regions of Iberia where such IVT forecasts are skilful and for what lead times. Employing the EFI on the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System ensemble for winters 2015/2016 and 2016/2017 and using high-density daily surface precipitation observations, the IVT EFI is shown to have slightly more skill (than the precipitation EFI) in discriminating extreme precipitation anomalies across the western Iberian Peninsula (Portugal and northwestern Spain) from forecast day 11 onwards. The reasoning is that the higher IVT predictability means that the IVT EFI is more able to detect the approximate location of extreme events at earlier lead times than the precipitation EFI. In contrast, for shorter forecast lead times, the precipitation EFI is more skilful. Also, when considering the entire Iberian Peninsula, the precipitation EFI is more skilful and more appropriate to monitor for potential extremes even at longer lead times.

Item Type:Article
Divisions:Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:106840
Publisher:Royal Meteorological Society


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