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.
Similar content being viewed by others
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
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
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
Beninston M (2003) Climatic change in mountain regions: a review of possible impacts. Clim Chang 59:5–31
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
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
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
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
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
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
Giorgi F (2006) Climate change hot spots. Geophys Res Lett 33, L08707. doi:10.1029/2006GL025734
Giorgi F, Mearns LO (1991) Approaches to the simulation of regional climate change: a review. Rev Geophys 29:191–216
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
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
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
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
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
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
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
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
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
Livezey RE, Chen WY (1983) Statistical field significance and its determination by Monte Carlo techniques. Mon Weather Rev 111:46–59
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
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
Martín-Vide J (1992) El Clima. Geografia General dels Països Catalans. Enciclopèdia Catalana 1:1–110, Barcelona
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
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
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
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
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
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
Rummukainen M (2010) State-of-the-art with regional climate models. WIREs Clim Chang 1:82–96
Skamarock WC, Klemp JB (2008) A time-split non hydrostatic atmospheric model for weather research and forecasting applications. J Comput Phys 227:3465–3485
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
Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res 106(D7):7183–7192. doi:10.1029/2000JD900719
Uppala SM et al (2005) The ERA-40 re-analysis. Q J R Meteorol Soc 131:2961–3012. doi:10.1256/qj.04.176
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
von Storch H, Langenberg H, Feser F (2000) A spectral nudging technique for dynamical downscaling purposes. Mon Weather Rev 128:3664–3673
Wilks DS (2006) Statistical methods in the atmospheric sciences. International geophysics series 91. Elsevier Academic Press Publications, USA, 627pp
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.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Online Resource 1
(PDF 3910 kb)
Online Resource 2
(PDF 37 kb)
Online Resource 3
(PDF 1360 kb)
Online Resource 4
(PDF 3118 kb)
Online Resource 5
(PDF 7252 kb)
Online Resource 6
(PDF 2918 kb)
Online Resource 7
(PDF 13564 kb)
Rights and permissions
About this article
Cite this article
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
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10584-013-0994-y