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Seasonal to yearly assessment of temperature and precipitation trends in the North Western Mediterranean Basin by dynamical downscaling of climate scenarios at high resolution (1971–2050)

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Abstract

The complex topography and high climatic variability of the North Western Mediterranean Basin (NWMB) require a detailed assessment of climate change projections at high resolution. ECHAM5/MPIOM global climate projections for mid-21st century and three different emission scenarios are downscaled at 10 km resolution over the NWMB, using the WRF-ARW regional model. High resolution improves the spatial distribution of temperature and precipitation climatologies, with Pearson's correlation against observation being higher for WRF-ARW (0.98 for temperature and 0.81 for precipitation) when compared to the ERA40 reanalysis (0.69 and 0.53, respectively). However, downscaled results slightly underestimate mean temperature (≈1.3 K) and overestimate the precipitation field (≈400 mm/year). Temperature is expected to raise in the NWMB in all considered scenarios (up to 1.4 K for the annual mean), and particularly during summertime and at high altitude areas. Annual mean precipitation is likely to decrease (around −5 % to −13 % for the most extreme scenarios). The climate signal for seasonal precipitation is not so clear, as it is highly influenced by the driving GCM simulation. All scenarios suggest statistically significant decreases of precipitation for mountain ranges in winter and autumn. High resolution simulations of regional climate are potentially useful to decision makers. Nevertheless, uncertainties related to seasonal precipitation projections still persist and have to be addressed.

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References

  • Argüeso D et al (2012a) Evaluation of WRF mean and extreme precipitation over Spain: present climate (1970–1999). J Clim 25:4883–4897. doi:10.1175/JCLI-D-11-00276.1

    Article  Google Scholar 

  • Argüeso D et al (2012b) High-resolution projections of mean and extreme precipitation over Spain using the WRF model (2070–2099 versus 1970–1999). J Geophys Res 117, D12108. doi:10.1029/2011JD017399

    Google Scholar 

  • Barrera-Escoda A, Cunillera J (2011) Climate change projections for Catalonia (NE Iberian Peninsula). Part I: Regional climate modeling. Tethys 8:75–87. doi:10.3369/tethys.2011.8.08

    Google Scholar 

  • Beninston M (2003) Climatic change in mountain regions: a review of possible impacts. Clim Chang 59:5–31

    Article  Google Scholar 

  • Cardoso RM, Soares PMM, Miranda PMA, Belo-Pereira M (2012) WRF high resolution simulation of Iberian Mean and extreme precipitation climate. Int J Climatol. doi:10.1002/joc.3616

    Google Scholar 

  • Christensen JH et al (2007a) Regional climate projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the IPCC. Cambridge University Press, Cambridge

    Google Scholar 

  • Christensen JH, Carter TR, Rummukainen M, Amanatidis G (2007b) Evaluating the performance and utility of regional climate models: the PRUDENCE project. Clim Chang 81:1–6. doi:10.1007/s10584-006-9211-6

    Article  Google Scholar 

  • Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46:3077–3107

    Article  Google Scholar 

  • Gao X, Pal JS, Giorgi F (2006) Projected changes in mean and extreme precipitation over the Mediterranean Region from a high resolution double nested RCM simulation. Geophys Res Lett 33, L03706. doi:10.1029/2005GL024954

    Google Scholar 

  • Gao L, Bernhardt M, Schulz K (2012) Elevation correction of ERA-Interim temperature data in complex terrain. Hydrol Earth Syst Sci 16:4661–4673. doi:10.5194/hess-16-4661-2012

    Article  Google Scholar 

  • Giorgi F (2006) Climate change hot spots. Geophys Res Lett 33, L08707. doi:10.1029/2006GL025734

    Google Scholar 

  • Giorgi F, Mearns LO (1991) Approaches to the simulation of regional climate change: a review. Rev Geophys 29:191–216

    Article  Google Scholar 

  • Giorgi F, Hurrell J, Marinucci M, Beniston M (1997) Elevation dependency of the surface climate change signal: a model study. J Clim 10:288–296

    Article  Google Scholar 

  • Gómez-Navarro JJ et al (2012) What is the role of the observational dataset in the evaluation and scoring of climate models? Geophys Res Lett 39, L24701. doi:10.1029/2012GL054206

    Google Scholar 

  • Heikkilä U, Sandvick A, Sorteberg A (2010) Dynamical downscaling of ERA-40 in complex terrain using the WRF regional climate model. Clim Dyn 37:1551–1564. doi:10.1007/s00382-010-0928-6

    Article  Google Scholar 

  • Herrera S et al (2012) Development and analysis of a 50 year high-resolution daily gridded precipitation dataset over Spain (Spain02). Int J Climatol 32:74–85. doi:10.1002/joc.2256

    Article  Google Scholar 

  • Hong S, Dudhia J, Chen S (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Weather Rev 132:103–132

    Article  Google Scholar 

  • Hong S, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134:2318–2341

    Article  Google Scholar 

  • Iacono MJ et al (2009) Radiative forcing by long-lived greenhouse gases: calculations with the AER radiative transfer models. J Geophys Res 113, D13103. doi:10.1029/2008JD009944

    Article  Google Scholar 

  • Jiménez-Guerrero P et al (2013) Mean fields and interannual variability in RCM simulations over Spain: the ESCENA project. Clim Res 57:201–220. doi:10.3354/cr01165

    Google Scholar 

  • Jorba O, Loridan T, Jiménez-Guerrero P, Baldasano JM (2008) Annual evaluation of WRF-ARW and WRF-NMM meteorological simulations over Europe. 9th Annual WRF Users’ Workshop. 23–27 June, 2008. Boulder, CO. USA

  • Kain JS (2004) The Kain-Fritsch convective parameterization: an update. J Appl Meteorol 43:170–181

    Article  Google Scholar 

  • Livezey RE, Chen WY (1983) Statistical field significance and its determination by Monte Carlo techniques. Mon Weather Rev 111:46–59

    Article  Google Scholar 

  • Marsland SJ et al (2003) The Max-Planck-Institute global ocean/sea-ice model with orthogonal curvilinear coordinates. Ocean Model 5:91–127. doi:10.1016/S1463-5003(02)00015-X

    Article  Google Scholar 

  • Martin A et al (2007) Sensitivities of a flash flood over Catalonia: a numerical analysis. Mon Weather Rev 135:651–669. doi:10.1175/MWR3316.1

    Article  Google Scholar 

  • Martín-Vide J (1992) El Clima. Geografia General dels Països Catalans. Enciclopèdia Catalana 1:1–110, Barcelona

    Google Scholar 

  • Mercader J, Codina B, Sairouni A, Cunillera J (2010) Results of the meteorological model WRF-ARW over Catalonia using diferent parametrizations of convection and cloud microphysics. Tethys 7:75–86. doi:10.3369/tethys.2010.7.07

    Google Scholar 

  • Nakićenović et al (2000) Emissions scenarios 2000–Special Report of the Intergovernmental Panel on Climate Change (SRES-IEEE). Cambridge University Press, Cambridge, RU, 570pp. Available at: http://www.ipcc.ch/ipccreports/sres/emission/index.php?idp=0

  • Nieto S, Rodríguez-Puebla C (2006) Comparison of precipitation from observed data and general circulation models over the Iberian Peninsula. J Clim 19:4254–4275

    Article  Google Scholar 

  • Niu GY et al (2011) The community Noah land surface model with multiparameterization options (Noah‐MP): 1.Model description and evaluation with local‐scale measurements. J Geophys Res 116, D12109

    Article  Google Scholar 

  • Randall DA et al (2007) Climate models and their evaluation. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the IPCC. Cambridge University Press, Cambridge

    Google Scholar 

  • Roeckner E (2005a) IPCC MPI-ECHAM5_T63L31 MPI-OM_GR1.5L40 20C3M_all run no.1: atmosphere 6 HOUR values MPImet/MaDGermany. World Data Center for Climate, Hamburg, Germany. CERA-DB “EH5-T63L31_OM_20C3M_1_6H”

  • Roeckner E (2005b) IPCC MPI-ECHAM5_T63L31 MPI-OM_GR1.5L40 20C3M_all run no.3: atmosphere 6 HOUR values MPImet/MaDGermany. World Data Center for Climate. Hamburg, Germany. CERA-DB “EH5-T63L31_OM_20C3M_3_6H”

  • Roeckner E et al (2003) The atmospheric general circulation model ECHAM5. Part I. Max-Planck Institut für Meteorologie. Report No. 349, Hamburg, Germany, 127pp

  • Roeckner E, Lautenschlager M, Schneider H (2006a) IPCC-AR4 MPI-ECHAM5_T63L31 MPI-OM_GR1.5L40 SRESA2 run no.1: atmosphere 6 HOUR values MPImet/MaDGermany. World Data Center for Climate, Hamburg, Germany. doi:10.1594/WDCC/EH5-T63L31_OM-GR1.5L40_A2_1_6H

  • Roeckner E et al (2006b) IPCC-AR4 MPI-ECHAM5_T63L31 MPI-OM_GR1.5L40 SRESA2 run no.3: atmosphere 6 HOUR values MPImet/MaDGermany. World Data Center for Climate, Hamburg. Germany. doi:10.1594/WDCC/EH5-T63L31_OM-GR1.5L40_A2_3_6H

  • Roeckner E et al (2006c) IPCC-AR4 MPI-ECHAM5_T63L31 MPI-OM_GR1.5L40 SRESA1B run no.1: atmosphere 6 HOUR values MPImet/MaDGermany. World Data Center for Climate, Hamburg, Germany. doi:10.1594/WDCC/EH5-T63L31_OM-GR1.5L40_A1B_1_6H

  • Roeckner E et al (2006d) IPCC-AR4 MPI-ECHAM5_T63L31 MPI-OM_GR1.5L40 SRESA1B run no.3: atmosphere 6 HOUR values MPImet/MaDGermany. World Data Center for Climate, Hamburg, Germany. doi:10.1594/WDCC/EH5-T63L31_OM-GR1.5L40_A1B_3_6H

  • Roeckner E et al (2006e) IPCC-AR4 MPI-ECHAM5_T63L31 MPI-OM_GR1.5L40 SRESB1 run no.1: atmosphere 6 HOUR values MPImet/MaDGermany. World Data Center for Climate, Hamburg, Germany. doi:10.1594/WDCC/EH5-T63L31_OM-GR1.5L40_B1_1_6H

  • Roeckner E et al (2006f) IPCC-AR4 MPI-ECHAM5_T63L31 MPI-OM_GR1.5L40 SRESB1 run no.3: atmosphere 6 HOUR values MPImet/MaDGermany. World Data Center for Climate, Hamburg, Germany. doi:10.1594/WDCC/EH5-T63L31_OM-GR1.5L40_B1_3_6H

  • Romero R, Guijarro JA, Ramis C, Alonso S (1998a) A 30-year (1964–1993) daily rainfall data base for the Spanish mediterranean regions: first exploratory study. Int J Climatol 18:541–560

    Article  Google Scholar 

  • Romero R, Ramis C, Alsonso S (1998b) Performance of two cumulus convection parameterizations for two heavy precipitation events in the Western Mediterranean. Meteorol Atmos Phys 66:197–214

    Article  Google Scholar 

  • Rummukainen M (2010) State-of-the-art with regional climate models. WIREs Clim Chang 1:82–96

    Article  Google Scholar 

  • Skamarock WC, Klemp JB (2008) A time-split non hydrostatic atmospheric model for weather research and forecasting applications. J Comput Phys 227:3465–3485

    Article  Google Scholar 

  • SMC (2012) Butlletí Anual d’Indicadors Climàtics 2011. Servei Meteorològic de Catalunya, Barcelona, Spain, 77pp. Available at: http://bit.ly/196Zl4j

  • Soares PMM et al (2012) WRF high resolution dynamical downscaling of ERA-Interim for Portugal. Clim Dyn 39:2497–2522. doi:10.1007/s00382-012-1315-2

    Article  Google Scholar 

  • Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res 106(D7):7183–7192. doi:10.1029/2000JD900719

    Article  Google Scholar 

  • Uppala SM et al (2005) The ERA-40 re-analysis. Q J R Meteorol Soc 131:2961–3012. doi:10.1256/qj.04.176

    Article  Google Scholar 

  • 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, Exeter. Available at: http://ensembles-eu.metoffice.com/docs/Ensembles_final_report_Nov09.pdf

  • van Ulden AP, van Oldenborgh GJ (2006) Large-scale atmospheric circulation biases and changes in global climate model simulations and their importance for climate change in Central Europe. Atmos Chem Phys 6:863–881. doi:10.5194/acp-6-863-2006

    Article  Google Scholar 

  • von Storch H, Langenberg H, Feser F (2000) A spectral nudging technique for dynamical downscaling purposes. Mon Weather Rev 128:3664–3673

    Article  Google Scholar 

  • Wilks DS (2006) Statistical methods in the atmospheric sciences. International geophysics series 91. Elsevier Academic Press Publications, USA, 627pp

    Google Scholar 

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Acknowledgments

The authors gratefully acknowledge AEMET and UC for the data provided for this work (Spain02 dataset, http://www.meteo.unican.es/datasets/spain02). Data from the RCM used in the ENSEMBLES project have been retrieved from the ENSEMBLES website: http://www.ensembles-eu.org/. We also thank the ECMWF for the ERA40 reanalysis and the World Data Center for Climate in Hamburg for the ECHAM5/MPIOM simulations.

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Correspondence to M. Gonçalves.

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Gonçalves, M., Barrera-Escoda, A., Guerreiro, D. et al. Seasonal to yearly assessment of temperature and precipitation trends in the North Western Mediterranean Basin by dynamical downscaling of climate scenarios at high resolution (1971–2050). Climatic Change 122, 243–256 (2014). https://doi.org/10.1007/s10584-013-0994-y

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