Enhanced summer convective rainfall at Alpine high elevations in response to climate warming

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1 SUPPLEMENTARY INFORMATION DOI: /NGEO2761 Enhanced summer convective rainfall at Alpine high elevations in response to climate warming Filippo Giorgi, Csaba Torma, Erika Coppola, Nikolina Ban, Christoph Schär and Samuel Somot NATURE GEOSCIENCE 1

2 Supplementary Figure 1. Analysis region and topography over the Alpine. a) Location of the analysis region within the whole European domain (red area); b) topography at a resolution intermediate across the GCMs (1.32 ); c) topography at the resolution of the RCMs (0.11 ). Units in b) and c) are m.

Supplementary Figure 2. Mean summer precipitation during the reference period (June- July-August, 1975-2004).

3 Supplementary Figure 2. Mean summer precipitation during the reference period (June- July-August, ). a) GCM ensemble; b) RCM ensemble; c) Observations 15. Thin contour lines represent topography with intervals of 500 meters. Units are mm/day.

Supplementary Figure 3. Mean observed 15 summer precipitation trend over the Alpine region for the period 1975-2004.

4 Supplementary Figure 3. Mean observed 15 summer precipitation trend over the Alpine region for the period Dotting indicates areas where the trend is significant at the 90% significance level according to a two-sided t-test.

5 Supplementary Figure 4. Projected summer precipitation change over the Alpine region for the late century time slice The changes are computed for June-July-August with respect to the reference period (units of % of reference values) for each GCM and RCM of Supplementary Table 1. Dotting indicates that the change is statistically significant at the 90% confidence level according to a two-sided t-test. Thin contour lines represent topography with intervals of 500 meters.

Supplementary Figure 5. Summer precipitation downscaling signal (DS, see text) over the Alpine region for the late century time slice 2070-2099.

6 Supplementary Figure 5. Summer precipitation downscaling signal (DS, see text) over the Alpine region for the late century time slice The changes are calculated for June- July-August with respect to the reference period (units of %) for each GCM and RCM of Supplementary Table 1. Dotting indicates that the DS is statistically significant at the 90% confidence level according to a two-sided t-test. Thin contour lines represent topography with intervals of 500 meters.

7 Supplementary Figure 6. Projected change in summer surface air temperature over the Alpine region for three different future time slices. The changes are calculated for June-July- August with respect to the reference period , and for the GCM and RCM ensembles (see Supplementary Table 1; units of C): a) GCM ensemble, ; b) GCM ensemble, ; c) GCM ensemble, ; d) RCM ensemble, ; e) RCM ensemble, ; f) RCM ensemble, Panels g), h), i) show the ensemble average RCM Downscaling Signal (see text, units of C) for the three future time slices, respectively, and dotting indicates areas where at least 5 out of 6 RCMs agree in the sign of this signal. Thin contour lines represent topography with intervals of 500 meters.

Supplementary Figure 7. Projected change in summer convective precipitation (June-July-August) over the Alpine region for the late century time slice 2070-2099.

8 Supplementary Figure 7. Projected change in summer convective precipitation (June-July-August) over the Alpine region for the late century time slice The changes are calculated for June-July-August with respect to the reference period , (units of %) for each GCM and RCM of Supplementary Table 1. Dotting indicates that the change is statistically significant at the 90% confidence level according to a two-sided t-test. Thin contour lines represent topography with intervals of 500 meters.

9 Supplementary Figure 8. Change in convection for convection permitting and corresponding 12 km resolution projections 11. a) Change in the Convection Index (CI) (see text and Methods) in a 2 km resolution convection permitting model simulation; b) Change in convective precipitation in the 12 km resolution model; The simulations are driven by the MPI- ESM-LR global model for control (CTRL: ) and scenario (SCEN: ) periods using RCP8.5 greenhouse gas concentration pathway 20. A prevailing increase in convective rainfall along the Swiss Alps chain is indicated by both model metrics.

10 Supplementary Table 1: Overview of global and regional climate models used in the present study. For the regional models the letter in parenthesis indicates the driving GCM (from CMIP5) and whether the run uses the EURO-CORDEX (EC) or MED-CORDEX (MC) domain. Model Modelling group Horizontal resolution Centre National de Recherches Meteorologiques and Centre Europeen de Recherches et de Formation Avancee en Calcul Scientifique, France a, CNRM-CM5 (Voldoire et al., 2012) b, EC-EARTH (Hazeleger et al., 2010) c, HadGEM2-ES (Collins et al., 2011) d, MPI-ESM-LR (Jungclaus et al., 2010) ALADIN (a-mc) (Colin et al., 2010) Convection scheme º x º Bougeault (1985) with a Kuo type closure (Kuo 1965) Irish Centre for High-End º x º Bechtold et al. (2008) Computing, Ireland Met Office Hadley Centre, UK º x º Derbyshire et al. (2010) Max Planck Institute for Meteorology, Germany Centre National de Recherches Meteorologiques, France º x º Tiedtke (1989) 0.11 º Bougeault (1985) with a Kuo type closure (Kuo 1965) CCLM (d-ec) (Rockel et al., 2008) RCA4 (c-ec) (Kupiainen et al., 2011) RACMO (b-ec) (Meijgaard van et al., 2012) REMO (d-ec) (Jacob et al., 2001) RegCM4 (c-mc) (Giorgi at al., 2012) Climate Limited-area Modelling Community, Germany Swedish Meteorological and Hydrological Institute, Rossby Centre, Sweden Royal Netherlands Meteorological Institute, The Netherlands Max-Planck-Institut für Meteorologie, Germany International Centre for Theoretical Physics, Italy 0.11 º Tiedtke (1989) 0.11 º Kain and Fritsch (1990, 1993) 0.11 º Tiedtke (1989), Nordeng (1994), Neggers et al. (2009) 0.11 º Tiedtke (1989), Nordeng (1994), Pfeifer (2006) 0.11 º Grell (1993), Emanuel (1991) Bougeault P (1985) A Simple Parameterization of the Large-Scale Effects of Cumulus Convection. Mon Weather Rev 113: Kuo HL (1965) On Formation and Intensification of Tropical Cyclones Through Latent Heat Release by Cumulus Convection. J Atmos Sci 22: Grell, G., 1993: Prognostic evaluation of assumptions used by cumulus parameterizations, Mon. Wea. Rev., 121, Emanuel, K. A., 1991: A scheme for representing cumulus convection in large-scalemodels, J. Atmos. Sci., 48(21),

11 Tiedtke, M.: A comprehensive mass flux scheme for cumulus parameterization in large-scale models, Mon. Weather Rev., 117, , Nordeng, T. E.: Extended versions of the convection parametrization scheme at ECMWF and their impact upon the mean climate and transient activity of the model in the tropics, ECMWF Tech. Memo. No. 206, Pfeifer, S.: Modeling cold cloud processes with the regional climate model REMO, MPI for Meteorology, Hamburg, Reports on Earth System Science No. 23, Neggers, R. A. J., Koehler, M., and Beljaars, A. C. M.: A dual mass flux framework for boundary layer convection, Part I: Transport, J. Atmos. Sci., 66, , Kain, J. S. and Fritsch, J. M.: Convective parameterization for mesoscale models: the Kain- Fritsch scheme. The representation of cumulus convection in numerical models, Meteorol. Monogr.24, , Derbyshire, S.H., I. Beau, P. Bechtold, J.-Y.Grandpeix, J.-M. Piriou,J.-L. Redelsperger, and P. M. M. Soares, 2004: Sensitivity of moist convection to environmental humidity. Quart. J. Roy. Meteor. Soc., 130, Bechtold, P., Koehler, M., Jung, T., Leutbecher, M., Rodwell, M., Vitart, F. and Balsamo, G. (2008). Advances in predicting atmospheric variability with the ECMWF model: From synoptic to decadal time-scales. Q. J. R. Meteorol. Soc., 134,

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