2014
DOI: 10.1002/asl2.507
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A ranking of high‐resolution daily precipitation extreme events for the Iberian Peninsula

Abstract: A method for ranking daily precipitation events is presented based on the most comprehensive database of daily gridded precipitation dataset available for the Iberian Peninsula spanning from 1950 to 2008. The magnitude of an event is obtained after considering the area affected as well as its intensity in every grid point and taking into account the daily normalized departure from climatology. Different precipitation rankings are presented considering the entire Iberian Peninsula, Portugal and also the six lar… Show more

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Cited by 60 publications
(103 citation statements)
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“…This ranking of wet spell events in the area of the Danube River Basin is based on the method developed by Ramos et al [20,21], which used daily-normalised precipitation anomalies for the ranking of multi-day extreme precipitation events according to the accumulated amount of precipitation and the spatial distribution in the Iberian Peninsula.…”
Section: Ranking Of Wet Spell Extreme Precipitation Eventsmentioning
confidence: 99%
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“…This ranking of wet spell events in the area of the Danube River Basin is based on the method developed by Ramos et al [20,21], which used daily-normalised precipitation anomalies for the ranking of multi-day extreme precipitation events according to the accumulated amount of precipitation and the spatial distribution in the Iberian Peninsula.…”
Section: Ranking Of Wet Spell Extreme Precipitation Eventsmentioning
confidence: 99%
“…This method [20] for the Iberian Peninsula was partially adapted from another approach [28], that has suggested some criteria to classify each day in terms of extremeness using different meteorological variables. The use of normalised precipitation departures from the seasonal climatology allows us to measure the rarity of an event given by the standardised precipitation anomalies.…”
Section: Ranking Of Wet Spell Extreme Precipitation Eventsmentioning
confidence: 99%
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