Climate Dynamics

, Volume 51, Issue 3, pp 857–876 | Cite as

Evaluation of simulated decadal variations over the Euro-Mediterranean region from ENSEMBLES to Med-CORDEX

  • Alessandro Dell’AquilaEmail author
  • Annarita Mariotti
  • Sophie Bastin
  • Sandro Calmanti
  • Leone Cavicchia
  • Michel Deque
  • Vladimir Djurdjevic
  • Marta Dominguez
  • Miguel Gaertner
  • Silvio Gualdi


Med-CORDEX simulations over the period 1979–2011 are evaluated with regard to their capability to represent observed decadal variations over the Euro-Mediterranean region and improve upon previous generation simulations from the ENSEMBLES project in their various experimental set-ups. Such an evaluation is needed to inform the use of these simulations and also future model development. For temperature, both Med-CORDEX and ENSEMBLES simulations tend to provide comparable results: they generally capture the sign and timing of the anomalies but not the amplitude. In general, no clear stratification appears when considering different types of Med-CORDEX regional modeling systems. Rather, it is remarkable that certain periods are poorly represented by all systems with a general underestimation of the observed long-term temperature trend, mostly in the summer season, even with respect to the corresponding global drivers. For precipitation, the Med-CORDEX simulations are closer to observations than the other datasets, with some improvement with respect to ENSEMBLES dataset. In general, all the systems experience difficulties in representing anomalies during specific periods or for specific regions. These appear in part due to limitations in the reanalysis boundary forcing data. For instance, in the second part of 1980s, the spatial patterns of surface air temperature during DJF/MAM are generally poorly represented, as well as the regionally averaged MAM/JJA surface air temperature decadal anomalies. Overall, the evaluation suggests limited improvement in Med-CORDEX simulations compared to ENSEMBLES, and a lack of sensitivity to resolution or coupling configuration, with persisting problems in part likely related to the representation of surface processes that could also affect the viability of future projections (e.g. the estimation of temperature trends). A set of decadal variability evaluation metrics, as applied in this study, could be useful in the context of a broader evaluation framework.


Regional climate modelling Long term variations Euro-Mediterranean region Evaluation metrics 



This work has been supported by the EU-FP7 2007–2013 projects IMPACT2C (282746), SPECS (308378) and by the Italian DTA-MIUR NextData national Project. UCLM contribution has been partially funded by the Spanish Government and the European Regional Development Fund, through grants CGL2007-66440-C04-02, CGL2010-18013 and CGL2013-47261-R. This work is part of the Med-CORDEX initiative ( supported by the HyMeX programme ( The comments of the two anonymous referees contributed to a notable improvement to this paper.

Supplementary material

382_2016_3143_MOESM1_ESM.docx (9.8 mb)
Supplementary material 1 (DOCX 10025 kb)


  1. Akthar N, Brauch J, Ahrens B (2016) Impact of resolution and ocean-coupling on regional climate model simulations over the Mediterranean Sea (in preparation)Google Scholar
  2. Allan R, Ansell T (2006) A new globally complete monthly historical gridded mean sea level pressure dataset (HadSLP2): 1850–2004. J Clim 19:5816–5842CrossRefGoogle Scholar
  3. Artale V, Calmanti S, Carillo A, Dell’Aquila A, Hermann M, Pisacane G, Ruti PM, Sannino G, Struglia MV, Giorgi F, Bi X, Pal JS, Rauscher S (2010) An atmosphere-ocean regional climate model for the mediterranean area: assessment of a present climate simulation. Clim Dyn. doi: 10.1007/s00382-009-0691-8 Google Scholar
  4. Beniston M et al (2007) Future extreme events in European climate: an exploration of regional climate model projections. Clim Change 81(S1):71–95. doi: 10.1007/s10584-006-9226-z CrossRefGoogle Scholar
  5. Boé J, Terray L (2014) Land–sea contrast, soil-atmosphere and cloud-temperature interactions: interplays and roles in future summer European climate change. Clim Dyn 42:683–699. doi: 10.1007/s00382-013-1868-8 CrossRefGoogle Scholar
  6. Cavicchia L, Gualdi S, Sanna A, Oddo P (2015) The regional ocean–atmosphere coupled model COSMO-NEMO_MFS. CMCC research paper RP0254.
  7. Cheruy F, Dufresne JL, Hourdin F, Ducharne A (2014) Role of clouds and land-atmosphere coupling in midlatitude continental summer warm biases and climate change amplification in CMIP5 simulations. Geophys Res Lett 41:6493–6500CrossRefGoogle Scholar
  8. Colin JM, Déqué M, Radu R, Somot S (2010) Sensitivity study of heavy precipitations in limited area model climate simulation: influence of the size of the domain and the use of the spectral nudging technique. Tellus Ser A Dyn Meteorol Oceanogr 62(5):591–604. doi: 10.1111/j.1600-0870.2010.00467.x CrossRefGoogle Scholar
  9. Dee DP et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597CrossRefGoogle Scholar
  10. Dell’Aquila A, Calmanti S, Ruti PM, Struglia MV, Pisacane G, Adriana C, Sannino G (2012) Impacts of seasonal cycle fluctuations over the Euro-Mediterranean area using a regional earth system model. Clim Res 2:135CrossRefGoogle Scholar
  11. Diffenbaugh NS, Giorgi F (2012) Climate change hot-spots in the CMIP5 global climate model ensemble. Clim Change Lett 114:813–822CrossRefGoogle Scholar
  12. Djurdjevic V, Rajkovic B (2008) Verification of a coupled atmosphere-ocean model using satellite observations over the Adriatic Sea. Ann Geophys 26(7):1935–1954. doi: 10.5194/angeo-26-1935-2008 CrossRefGoogle Scholar
  13. Domínguez M, Romera R, Sánchez E, Fita L et al (2013) Present-climate precipitation and temperature extremes over Spain from a set of high resolution RCMs. Clim Res 58:149–164CrossRefGoogle Scholar
  14. Drobinski P, Ducrocq V et al (2014) HyMeX: a 10-year multidisciplinary program on the Mediterranean water cycle. Bull Am Meteorol Soc 95:1063–1082. doi: 10.1175/BAMS-D-12-00242.1 CrossRefGoogle Scholar
  15. Fan Y, van den Dool H (2004) Climate prediction center global monthly soil moisture data set at 0.5 degree resolution for 1948 to present. J Geophys Res 109:D10102. doi: 10.1029/2003JD004345 CrossRefGoogle Scholar
  16. Feser F, Rockel B, von Storch H, Winterfeldt J, Zahn M (2011) Regional climate models add value to global model data: a review and selected examples. Bull Am Meteorol Soc 92:1181–1192. doi: 10.1175/2011BAMS3061.1 CrossRefGoogle Scholar
  17. Flaounas E, Drobinski P, Bastin S (2013) Dynamical downscaling of IPSL-CM5 CMIP5 historical simulations over the Mediterranean: benefits on the representation of regional surface winds and cyclogenesis. Clim Dyn. doi: 10.1007/s00382-012-1606-7 Google Scholar
  18. Giorgi F (2006) Climate change hot-spots. Geophys Res Lett 33:L08707. doi: 10.1029/2006GL025734 CrossRefGoogle Scholar
  19. Giorgi F, Jones C, Asrar GR (2009) Addressing climate information needs at the regional level: the CORDEX framework. WMO Bull 58(3):175Google Scholar
  20. Giorgi F, Coppola E, Solmon F, Mariotti L et al (2012) RegCM4: model description and preliminary tests over multiple CORDEX domains. Clim Res 52:7–29CrossRefGoogle Scholar
  21. Gleckler P, Ebert E, Eyring V, Pincus R, Taylor K, Wood R (2010) A world climate research programme (WCRP) panel tasked to identify and promote performance metrics for climate models. In: Stocker T, et al Meeting report of the IPCC expert meeting on assessing and combining multi model climate projections, pp 47–48, IPCC, Boulder, Colo.
  22. Hagemann S, Jones R, Christensen OB, Deque M, Jacob D, Machenhauer B, Vidale PL (2004) Evaluation of water and energy budgets in regional climate models applied over Europe. Clim Dyn 23:547–567CrossRefGoogle Scholar
  23. Harris I, Jones PD, Osborn TJ, Lister DH (2014) Updated high-resolution grids of monthly climatic observations—the CRU TS3.10 Dataset. Int J Climatol 34:623–642. doi: 10.1002/joc.3711 CrossRefGoogle Scholar
  24. Hourdin F, Musat I, Bony S, Braconnot P, Codron F, Dufresne JL, Fairhead L, Filiberti MA, Friedlingstein P, Grandpeix JY, Krinner G, Levan P, Li ZX, Lott F (2006) The LMDZ4 general circulation model: climate performance and sensitivity to parametrized physics with emphasis on tropical convection. Clim Dyn 27(7–8):787–813CrossRefGoogle Scholar
  25. IPCC (2007) Climate change 2007: the physical science basis. Contribution of working group I to the 4th assessment report of the intergovernmental panel on climate change. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USAGoogle Scholar
  26. IPCC (2013) Climate change 2013: the physical science basis. Contribution of working group I to the 5th assessment report of the intergovernmental panel on climate change. In: Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp. doi:  10.1017/CBO9781107415324
  27. Jones PD, Harris I (2008) Climatic research unit (CRU) time-series datasets of variations in climate with variations in other phenomena. NCAS British Atmospheric Data Centre.
  28. Kjellström E, Thejll P, Rummukainen M, Christensen JH, Boberg F, Christensen OB, Maule CF (2013) Emerging regional climate change signals for Europe under varying large-scale circulation conditions. Clim Res 56:103–119CrossRefGoogle Scholar
  29. Krzic A, Tosic I, Djurdjevic V, Veljovic K, Rajkovic B (2011) Changes in some indices over Serbia according to the SRES A1B and A2 scenarios. Clim Res 49:73–86. doi: 10.3354/cr01008 CrossRefGoogle Scholar
  30. Lebeaupin-Brossier C, Drobinski P, Beranger K, Bastin S, Orain F (2013) Ocean memory effect on the dynamics of coastal heavy precipitation preceded by a mistral event in the north-western Mediterranean. Q J R Meteorol Soc 139(675):1583–1597. doi: 10.1002/qj.2049 CrossRefGoogle Scholar
  31. Lorenz P, Jacob D (2010) Validation of temperature trends in the ENSEMBLES regional climate model runs driven by ERA40. Clim Res 44:167–177CrossRefGoogle Scholar
  32. Mariotti A, Dell’Aquila A (2012) Decadal climate variability in the Mediterranean region: roles of large-scale forcings and regional processes. Clim Dyn. doi: 10.1007/s00382-011-1056-7 Google Scholar
  33. Mariotti A, Pan Y, Zeng N, Alessandri A (2015) Long-term climate change in the Mediterranean region in the midst of decadal variability. Clim Dyn. doi: 10.1007/s00382-015-2487-3 Google Scholar
  34. Reichler T, Kim J (2008) How well do coupled models simulate today’s climate? Bull Am Meteorol Soc 89:303–311. doi: 10.1175/BAMS-89-3-303 CrossRefGoogle Scholar
  35. Ruti PM, Somot S, Giorgi F, Dubois C, Flaounas E, Obermann A, Dell’Aquila A, Pisacane G, Harzallah A, Lombardi E, Ahrens B, Akhtar N, Alias A, Arsouze T, Aznar R, Bastin S, Bartholy J, Béranger K, Beuvier J, Bouffies-Cloché S, Brauch J, Cabos W, Calmanti S, Calvet JC, Carillo A, Conte D, Coppola E, Djurdjevic V, Drobinski P, Elizalde-Arellano A, Gaertner M, Galàn P, Gallardo C, Gualdi S, Goncalves M, Jorba O, Jordà G, L’Heveder B, Lebeaupin-Brossier C, Li L, Liguori G, Lionello P, Maciàs D, Nabat P, Onol B, Raikovic B, Ramage K, Sevault F, Sannino G, Struglia M, Sanna A, Torma C, Vervatis V (2015) MEDCORDEX initiative for Mediterranean climate studies. Bull Am Meteorol Soc. doi: 10.1175/BAMS-D-14-00176.1 Google Scholar
  36. Seneviratne SI et al (2006) Land-atmosphere coupling and climate change in Europe. Nature 443:205–209CrossRefGoogle Scholar
  37. Sevault F, Somot S, Alias A, Dubois C, Lebeaupin-Brossier C, Nabat P, Adloff F, Déqué M, Decharme B (2014) A fully coupled Mediterranean regional climate system model: design and evaluation of the ocean component for the 1980–2012 period. Tellus A 66:23967. doi: 10.3402/tellusa.v66.23967 CrossRefGoogle Scholar
  38. Somot S, Sevault F, Déqué M, Crépon M (2008) 21st century climate change scenario for the Mediterranean using a coupled atmosphere ocean regional climate model. Glob Planet Change 63:112–126CrossRefGoogle Scholar
  39. Stefanon M, Drobinski P, D’Andrea F, Lebeaupin-Brossier C, Bastin S (2014) Soil moisture-temperature feedbacks at meso-scale during summer heat waves over western Europe. Clim Dyn 42(5–6):1309–1324. doi: 10.1007/s00382-013-1794-9 CrossRefGoogle Scholar
  40. Uppala SM, Kallberg PW, Simmons AJ et al (2005) The era-40 re-analysis. Q J R Meteorol Soc 131:2961–3012. doi: 10.1256/qj.04.176 CrossRefGoogle Scholar
  41. van der Linden P, Mitchell JFB (2009) ENSEMBLES: climate change and its impacts: summary of research and results from the ENSEMBLES project. Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3 PB, UKGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Alessandro Dell’Aquila
    • 1
    Email author
  • Annarita Mariotti
    • 2
  • Sophie Bastin
    • 3
  • Sandro Calmanti
    • 1
  • Leone Cavicchia
    • 4
  • Michel Deque
    • 5
  • Vladimir Djurdjevic
    • 6
  • Marta Dominguez
    • 7
  • Miguel Gaertner
    • 7
  • Silvio Gualdi
    • 4
  1. 1.ENEARomeItaly
  2. 2.NOAASilver SpringUSA
  4. 4.CMCCBolognaItaly
  5. 5.CNRMToulouseFrance
  6. 6.University of BelgradeBelgradeSerbia
  7. 7.UCLMToledoSpain

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