SUPPLEMENTARY INFORMATION

Transcription

1 doi: /nature12310 We present here two additional Tables (Table SI-1, 2) and eight further Figures (Figures SI-1 to SI-8) to provide extra background information to the main figures of the paper. Table SI-1 gives the Standard Deviations (SDs) of the distributions of normalised two-metre temperature data from the ECMWF ERA-40 dataset. These distributions are those presented in Figure 1a (yearly values) and Figure SI-1a (seasonal values and by hemisphere; see below). Values are for the identical four periods of these figures, and where anomalies are calculated relative to their local mean values for period For each year and at all gridpoints, anomalies are divided by their local SD for period Table SI-2 gives the SDs of the distributions of normalised ECMWF ERA-40 datasets, as presented in Figure 1b (yearly values) and Figure SI-2 (seasonal values and by hemisphere; see below). In this instance anomalies are again first calculated by subtracting local mean values, but now with these means corresponding to each of the four different periods. This is before dividing by the SD of these anomalies for period Figure SI-3 is the alteration in zonal (latitudinal) SD (panel (a)) and change in zonal temperature (panel (b)). Panel (a) shows the change in SD values between period and period (Later period minus earlier period). These are based on yearly temperature anomalies of the ECMWF ERA-40 gridded data, found by de-trending with an 11-year running mean for each gridbox. For each gridbox, a pair of SD values are calculated from these anomalies and for the two periods. These are then averaged for each latitudinal band of the data; panel (a) is the difference between the two periods. Panel (b) shows the mean zonal change in temperature between the same two periods. The purpose of this plot is to see if any correlation between the two panels exists, as a potential driver of SD zonal changes. For the two periods considered, we are unable to see any simple correlation between temperature rise (or its latitudinal gradient) and mean latitudinal SD change. Hemispheric mean changes are the coloured straight lines in both panels. The map of Figure 1e, in the main part of the paper, shows the average percentage change in SD for each gridbox of ECMWF data, again corresponding to 11-year de-trended data before and after year 1980 (i.e. using the same SD pairs as for Figures SI-3a). Although we find very little change for globally-averaged SD (Figure 1c, black and cyan curves), map Figure 1e shows profound regional alterations. The ECMWF re-analysis dataset entrains a vast number of meteorological measurements, and given the implications of Figure 1e, we return to direct weather station temperature datasets for additional verification of major SD changes. In Figure SI-4 we consider only stations where complete years of temperature data are available between years 1950 and These are de-trended (11-year), and moving averages (11- year) of SD calculated and shown. With these two 11-year timescales, this covers years in period For easier comparison, the timeseries have been normalised such that the time-evolving SD value is unity for average of year values. Panel (a) shows a large spread before and after the period centred on year 1980, verifying major changes, and with the 5% and 95% bounds marked. Figure 1e implies large SD enhancement for much of Europe and North America, and in panels (b) and (c) we show station data for those regions only. Almost all curves are red, corresponding to a mean increase after The years selected as criteria for whether SD has increased after 1980 (red) or decreased after 1980 (blue) are 1963 to 1980 vs 1981 to 1996; same timeperiods as used for ECMWF data in Figure 1e. Figure SI-5 is identical to the global map of Figure 1e, showing the percentage change in SD 1

2 Figure SI-5 is identical to the global map of Figure 1e, showing the percentage change in SD after year 1980 compared to the period before that. However in this Figure, the maps instead correspond to the four different seasons. Figure SI-6 shows predictions of time-evolving global SD of the 17 models of the CMIP5 database where simulations are available for the scenario of all historical forcings, followed by the RCP8.5 concentration pathway. The curves are averaged across ensemble members, and calculated identically to the one specific to HadGEM2-ES in Figure 3a. That is detrending with local 11-year running means (i.e. removing local 11-year moving averages) to obtain anomalies, and then calculating 11-year moving averages of the global SD of those anomalies. The notable feature is that the majority of models predict a decrease in SD towards the end of the 21 st Century. It is the average of these curves that creates the summary cross-model black curve in Figure 3f, and their normalised spread that gives the turquoise region of Figure 3f. Figure SI-7 is identical to Figure SI-6, except that now local anomalies are de-trended with a 31-year running mean. The time-evolving global yearly SD values, based on these anomalies, are then smoothed with a 31-year moving average. It is the average of these curves that creates the summary cross-model black curve in Figure 3g. Figure SI-8 shows the 31-year moving average SD values for each CMIP5 model (Figure SI- 7), plotted against the 31-year moving average of their predictions of average annual sea-ice cover. 2

3 Data Presented / Period SD of Fig 1a: Global, anomalies from mean and division by their SD SD of Fig SI-1a Identical to Fig 1a, except for MAM season and Northern Hemisphere only SD of Fig SI-1b Identical to Fig 1a, except for JJA season and Northern Hemisphere only SD of Fig SI-1c Identical to Fig 1a, except for SON season and Northern Hemisphere only SD of Fig SI-1d Identical to Fig 1a, except for DJF season and Northern Hemisphere only SD of Fig SI-1e Identical to Fig 1a, except for MAM season and Southern Hemisphere only SD of Fig SI-1f Identical to Fig 1a, except for JJA season and Southern Hemisphere only SD of Fig SI-1g Identical to Fig 1a, except for SON season and Southern Hemisphere only SD of Fig SI-1h Identical to Fig 1a, except for DJF season and Southern Hemisphere only Table SI-1: SDs of distributions of Figure 1a and Figure SI-1 3

4 Data Presented / Period SD of Fig 1b: Global, anomalies from means for each of the four periods, and division by their SD SD of Fig SI-2a Identical to Fig 1a, except for MAM season and Northern Hemisphere only SD of Fig SI-2b Identical to Fig 1a, except for JJA season and Northern Hemisphere only SD of Fig SI-2c Identical to Fig 1a, except for SON season and Northern Hemisphere only SD of Fig SI-2d Identical to Fig 1a, except for DJF season and Northern Hemisphere only SD of Fig SI-2e Identical to Fig 1a, except for MAM season and Southern Hemisphere only SD of Fig SI-2f Identical to Fig 1a, except for JJA season and Southern Hemisphere only SD of Fig SI-2g Identical to Fig 1a, except for SON season and Southern Hemisphere only SD of Fig SI-2h Identical to Fig 1a, except for DJF season and Southern Hemisphere only Table SI-2: SDs of distributions of Figure 1b and Figure SI-2 4

5 (a) (b) (c) (d) (e) (f) (g) (h) Figure SI-1: Normalised seasonal ECMWF temperature anomalies. These plots are identical to Figure 1a, showing the distribution of normalised anomalies relative to period However here, instead, the curves are for the individual seasons (MAM: March-May; JJA: June-August; SON: September-November; DJF: December-February) and are also divided in to hemisphere (NH: Northern hemisphere; SH: Southern hemisphere). 5

6 (a) (b) (c) (d) (e) (f) (g) (h) Figure SI-2: Normalised seasonal ECMWF temperature anomalies. These plots are identical to Figure 1b, and hence anomalies are first calculated relative to local mean value for each of the four periods indicated. Local SDs of these anomalies are calculated for period , and the anomalies are divided by these SD values, to give the normalised distributions shown. However here, unlike Figure 1b, curves are for individual seasons (MAM: March-May; JJA: June-August; SON: September-November; DJF: December-February) and are also divided in to hemisphere (NH: Northern hemisphere; SH: Southern hemisphere). 6

7 (a) (b) Figure SI-3: Mean zonal changes. Panel (a) is zonal change in SD, given as average latitudinal SD for period minus average for period 1963 to Panel (b) is zonal average temperature change between the same periods. For panels (a) and (b) the red and blue lines are the area-weighted hemispheric changes in the two quantities. 7

8 (a) (b) (c) Figure SI-4: Weather station data. Panel (a) is the timeseries of SD of individual CRU station data, calculated over 11-year segments of anomalies that have in turn been de-trended by 11-year running means. To understand the spread before and after 1980, we have then normalised so that the mean value is unity. The top panel is the full set of timeseries for stations having data complete for period Also shown are 5% and 95% bounds, based simply on ordering station values at each year. Panels (b) and (c) are the same as for panel (a), but for mid-europe (defined as rectangle E and N) and North America (defined as rectangle W and N) respectively. For panels (b) and (c), the trajectories are colour coded as red if average SD is higher in period compared to period , and blue if lower. These two periods correspond to those of ERA-40 availabililty, and timeperiod associated with map Figure 1e. Green dashed line is at value unity. 8

9 (a) (b) (c) (d) Figure SI-5: Seasonal map of SD changes. Global maps of percentage change in SD for each gridbox of the ERA-40 data, comparing before and after year Identical to Figure 1e, but here presented for the different seasons of (a) March-May, (b) June-July, (c) September-November and (d) December-February. Yellow, orange and red indicates an increase in SD after year

10 Figure SI-6: Global SD of CMIP5 models, 11-yr averaging. Each panel is for a different GCM contributing to the CMIP5 database, and shows the 11-year running mean of the average, across available ensembles, of the global spatially-averaged time evolving SDs of anomalies in yearly temperature. Climate modelling centre and model version name are in the panel titles. The curves are for the historical period followed by RCP8.5 scenario forced simulations. The number of ensemble members available is given in the plot annotation. The calculations use yearly temperature anomalies derived relative to local running means, also over 11 years. The dashed lines are the means of curves between simulation start and year The MOHC/HadGEM2-ES curve is identical to the black curve in the top panel of Figure

11 Figure SI-7: Global SD of CMIP5 models, 31-yr averaging. This figure is identical to Figure SI-6, except that in this instance gridbox anomalies are calculated relative to their local 31-year running mean. The average area-weighted global SD is again calculated across the number of ensembles for each model. Presented are the 31-year running mean of these global values. Climate modelling centre and model version name are in the panel titles. 11

12 Figure SI-8: Global SD of annual temperature fluctuations vs sea-ice cover of CMIP5 models. We use the 31-year running mean SD values from Figure SI-7, and plot these against the 31-year running mean of annual sea-ice cover from each of the 17 CMIP5 models. Presented are values from period centred on year 2000 (green diamonds) through to the end of the simulations (red diamonds). Climate modelling centre and model version name are in the panel titles. 12