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Emerging trends in heavy precipitation and hot temperature extremes in Switzerland
Author(s) -
Scherrer S. C.,
Fischer E. M.,
Posselt R.,
Liniger M. A.,
CrociMaspoli M.,
Knutti R.
Publication year - 2016
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2015jd024634
Subject(s) - precipitation , environmental science , percentile , mean radiant temperature , climatology , climate change , intensity (physics) , atmospheric sciences , meteorology , geography , mathematics , statistics , geology , physics , oceanography , quantum mechanics
Changes in intensity and frequency of daily heavy precipitation and hot temperature extremes are analyzed in Swiss observations for the years 1901–2014/2015. A spatial pooling of temperature and precipitation stations is applied to analyze the emergence of trends. Over 90% of the series show increases in heavy precipitation intensity, expressed as annual maximum daily precipitation (mean change: +10.4% 100 years −1 ; 31% significant, p < 0.05) and in heavy precipitation frequency, expressed as the number of events greater than the 99th percentile of daily precipitation (mean change: +26.5% 100 years −1 ; 35% significant, p < 0.05). The intensity of heavy precipitation increases on average by 7.7% K −1 smoothed Swiss annual mean temperature, a value close to the Clausius‐Clapeyron scaling. The hottest day and week of the year have warmed by 1.6 K to 2.3 K depending on the region, while the Swiss annual mean temperature increased by 1.9 K. The frequency of very hot days exceeding the 99th percentile of daily maximum temperature has more than tripled. Despite considerable local internal variability, increasing trends in heavy precipitation and hot temperature extremes are now found at most Swiss stations. The identified trends are unlikely to be random and are consistent with climate model projections, with theoretical understanding of a human‐induced change in the energy budget and water cycle and with detection and attribution studies of extremes on larger scales.