Summary of observed changes in precipitation and temperature extremes (D9)

Objective Are extremes becoming more severe? Are extremes becoming more severe? Are they becoming more frequent? Are they becoming more frequent? How is the spatial pattern of the observed changes? How is the spatial pattern of the observed changes? Is there seasonal variability in the changes? Is there seasonal variability in the changes?

Method of analysis Time series of Time series of Daily precipitation, Daily precipitation, Daily max/min temperatures Daily max/min temperatures Definition of indices that correspond to extremes Definition of indices that correspond to extremes Calculation of annual seasonal values of the indices Calculation of annual seasonal values of the indices Linear regression applied on the time series of the calculated indices Linear regression applied on the time series of the calculated indices Non-parametric test of significance Non-parametric test of significance

Study regions and numbers of stations investigated RegionPartner No. P.stat No. T.stat EuropeUEA EnglandUEA4021 GermanyUSTUTT-IWS GreeceAUTH2222 N. Italy ARPA-SMR6244 SwitzerlandETH104None French Alps CNRS 3+gridded data 3

Extreme indices investigated DesignationDescription Precipitation related indices Prec90p90th percentile of rainday amounts (mm/day) 644R5dGreatest 5-day total rainfall 646SDIISimple Daily Intensity (rain per rainday) 641CDDMax no. of consecutive dry days 691R90T% of total rainfall from events > long-term 90th percentile 692R90NNo. of events > long-term 90th percentile of raindays Temperature related indices Tmax90pTmax 90th percentile Tmin10pTmin 10th percentile 125FdNumber of frost days Tmin < 0 °C 144HWDIHeat wave Duration

ResultsEurope Heavy precipitation extremes: Winter  Increased in central Europe, the UK and Scandinavia.  Decreased in Eastern Europe, Greece, and western Iberian Peninsula. Summer  increased across northern Scandinavia and Russia  decreased across the UK and NE Europe  increased through SW Europe  decreased across the northern Iberian Peninsula.

Dry day persistence Winter  increased in the southern part of the region  decreased in the north  the increase is generally greater than the decrease Summer  Less coherent signal  Most stations in the central part, the UK, and southern Scandinavia showed an increase.

Temperature extremes Winter  Extreme maximum temperature increased over most of the region except the SE  Extreme minimum temperature increased over the entire region apart from small decreases in parts of Greece, the Iberian Peninsula and Scandinavia  Extreme minimum temperature increased to a larger degree than the corresponding extreme maximum temperature Summer  Extreme maximum temperature incresed in most area of the region except in northern Scandinavia, Eastern Europe, and Russia  Extreme minimum temperature increaded in most areas except that a few stations showed a decrease

Local scale trends in extreme heavy precipitation indices RegionWinterSpringSummerAutumn England++-- Germany N. Italy --++ Greece-- Swizerland French Alps Variablevariablevariable+

Local scale trends in extreme maximum temperature RegionWinterSpringSummerAutumn England++++ Germany+++ N. Italy ++++ Greece++++ Swizerland French Alps ++++

Precipitation trends / Floods Areal precipitation vs. Point precipitation Areal precipitation vs. Point precipitation Simultaneous occurrence of extremes Simultaneous occurrence of extremes Differences between trends corresponding to nearby stations Differences between trends corresponding to nearby stations Trend  Interpolation or Interpolation  Trend Trend  Interpolation or Interpolation  Trend

Trends in the areal precipitation indices Point scaleGrid size of 10km x10km Winter trends in the 5 day total rainfall amount

Summary There are significant trends in the extreme indices There are significant trends in the extreme indices Variability increases (Ex.: dry day duration and 5 day sums both increase) Variability increases (Ex.: dry day duration and 5 day sums both increase) Trends in downscaled series Trends in downscaled series