%0 Figure %A A Stainforth, David %A C Chapman, Sandra %A W Watkins, Nicholas %D 2013 %T Changing cumulative distribution functions for maximum daily (daytime) summer temperatures for three E-OBS grid boxes %U https://iop.figshare.com/articles/figure/_Changing_cumulative_distribution_functions_for_maximum_daily_daytime_summer_temperatures_for_three_/1011614 %R 10.6084/m9.figshare.1011614.v1 %2 https://iop.figshare.com/ndownloader/files/1479439 %K decision makers %K summer days %K adaptation planners %K policy makers %K temperature distributions %K Red cdfs %K ct %K temperature distribution %K quantile %K climate forecasting methods %K Abstract Climate change %K summer temperatures %K support decisions %K distribution functions %K Northern France %K climate change %K warming %K Environmental Science %X

Figure 1. Changing cumulative distribution functions for maximum daily (daytime) summer temperatures for three E-OBS grid boxes. Red cdfs are centred on each year from 1954 to 1963 (1954 only in (a)). Green cdfs are centred on each year from 1997 to 2006 (1997 only in (a)). In (a) the blue horizontal line shows ΔTq for the median quantile (q = 0.5), the vertical red line ΔCT at T = 28 °C. In (b)–(d) the vertical red line (thin black line) is the smallest (largest) ΔCT at T = 28 °C; the corresponding cdfs are shown as solid (dashed) blue and black lines representing the earlier and later period respectively. Locations are: (a) and (b) Bordeaux, France, (c) western Algarve, Portugal, (d) eastern Piedmont, Italy.

Abstract

Climate change poses challenges for decision makers across society, not just in preparing for the climate of the future but even when planning for the climate of the present day. When making climate sensitive decisions, policy makers and adaptation planners would benefit from information on local scales and for user-specific quantiles (e.g. the hottest/coldest 5% of days) and thresholds (e.g. days above 28 ° C), not just mean changes. Here, we translate observations of weather into observations of climate change, providing maps of the changing shape of climatic temperature distributions across Europe since 1950. The provision of such information from observations is valuable to support decisions designed to be robust in today's climate, while also providing data against which climate forecasting methods can be judged and interpreted. The general statement that the hottest summer days are warming faster than the coolest is made decision relevant by exposing how the regions of greatest warming are quantile and threshold dependent. In a band from Northern France to Denmark, where the response is greatest, the hottest days in the temperature distribution have seen changes of at least 2 ° C, over four times the global mean change over the same period. In winter the coldest nights are warming fastest, particularly in Scandinavia.

%I IOP Publishing