Skip to main content

Advertisement

SpringerLink
Log in

Climate change scenarios for precipitation extremes in Portugal

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

Precipitation indices are commonly used as climate change indicators. Considering four Climate Variability and Predictability-recommended indices, this study assesses possible changes in their spatial patterns over Portugal under future climatic conditions. Precipitation data from the regional climate model Consortium for Small-Scale Modelling–Climate version of the Local Model (CCLM) ensemble simulations with ECHAM5/MPI-OM1 boundary conditions are used for this purpose. For recent–past, medians and probability density functions of the CCLM-based indices are validated against station-based and gridded observational dataset from ENSEMBLES-based (gridded daily precipitation data provided by the European Climate Assessment & Dataset project) indices. It is demonstrated that the model is able to realistically reproduce not only precipitation but also the corresponding extreme indices. Climate change projections for 2071–2100 (A1B and B1 SRES scenarios) reveal significant decreases in total precipitation, particularly in autumn over northwestern and southern Portugal, though changes exhibit distinct local and seasonal patterns and are typically stronger for A1B than for B1. The increase in winter precipitation over northeastern Portugal in A1B is the most important exception to the overall drying trend. Contributions of extreme precipitation events to total precipitation are also expected to increase, mainly in winter and spring over northeastern Portugal. Strong projected increases in the dry spell lengths in autumn and spring are also noteworthy, giving evidence for an extension of the dry season from summer to spring and autumn. Although no coupling analysis is undertaken, these changes are qualitatively related to modifications in the large-scale circulation over the Euro-Atlantic area, more specifically to shifts in the position of the Azores High and associated changes in the large-scale pressure gradient over the area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Abbreviations

CCLM COSMO-CLM:

Consortium for Small-Scale Modelling–Climate version of the Local Model

GCM:

Global climate model

GHG:

Greenhouse gas

IPCC:

International Panel on Climate Change

MSLP:

Mean sea level pressure

NAO:

North Atlantic Oscillation

RCM:

Regional climate model

SRES:

Synthesis Report on Emission Scenarios

WMW:

Wilcoxon–Mann–Whitney

References

  • Agresti A, Wackerly D, Boyett JM (1979) Exact conditional tests for cross-classifications: approximation of attained significance levels. Psychometrika 44:75–83

    Article  Google Scholar 

  • Alexander LV, Zhang X, Peterson TC, Caesar J et al (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109. doi:10.1029/2005JD006290

    Article  Google Scholar 

  • Andrade C, Santos JA, Pinto JG, Corte-Real J (2011) Large-scale atmospheric dynamics of the wet winter 2009–2010 and its impact on hydrology in Portugal. Clim Res 46:29–41. doi:10.3354/cr00945

    Article  Google Scholar 

  • Bachner S, Kapala A, Simmer C (2008) Evaluation of daily precipitation characteristics in the CLM and their sensitivity to parameterizations. Meteorol Z 17:407–419. doi:10.1127/0941-2948/2008/0300

    Article  Google Scholar 

  • Bengtsson L, Hodges KI, Roeckner E (2006) Storm tracks and climate change. J Climate 19:3518–3543. doi:10.1175/JCLI3815.1

    Article  Google Scholar 

  • Beniston M, Stephenson D, Christensen O, Ferro C et al (2007) Future extreme events in European climate: an exploration of regional climate model projections. Clim Chang 81:71–95. doi:10.1007/s10584-006-9226-z

    Article  Google Scholar 

  • Böhm U, Kücken M, Ahrens W, Block A, Hauffe D, Keuler K, Rockel B, Will A (2006) CLM—the climate version of LM: brief description and long-term applications. COSMO Newsletter 6:225–235

    Google Scholar 

  • Carvalho A, Flannigan MD, Logan KA, Gowman LM, Miranda AI, Borrego C (2010) The impact of spatial resolution on area burned and fire occurrence projections in Portugal under climate change. Clim Chang 98:177–197. doi:10.1007/s10584-009-9667-2

    Article  Google Scholar 

  • Christensen JH, Hewitson B, Busuioc A, Chen A, Gao X et al (2007) Regional climate projections. In: Solomon S, Qin D, Manning M, Chen Z et al (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 847–940

    Google Scholar 

  • Costa AC, Soares A (2009a) Trends in extreme precipitation indices derived from a daily rainfall database for the south of Portugal. Int J Climatol 29:1956–1975. doi:10.1002/joc.1834

    Article  Google Scholar 

  • Costa AC, Soares A (2009b) Homogenization of climate data: review and new perspectives using geostatistics. Math Geosci 41:291–305. doi:10.1007/s11004-008-9203-3

    Article  Google Scholar 

  • de Lima MIP, Carvalho SCP, de Lima JLMP (2010) Investigating annual and monthly trends in precipitation structure: an overview across Portugal. Nat Hazards Earth Syst Sci 10:2429–2440. doi:10.5194/nhess-10-2429-2010

    Article  Google Scholar 

  • Demuzere M, Werner M, van Lipzig NPM, Roeckner E (2009) An analysis of present and future ECHAM5 pressure fields using a classification of circulation patterns. Int J Climatol 29:1796–1810. doi:10.1002/joc.1821

    Article  Google Scholar 

  • Donat MG, Leckebusch GC, Pinto JG, Ulbrich U (2010) European storminess and associated circulation weather types: future changes deduced from a multi-model ensemble of GCM simulations. Clim Res 42:27–43. doi:10.3354/cr00853

    Article  Google Scholar 

  • Frei C, Schöll R, Fukutome S, Schmidli J, Vidale PL (2006) Future change of precipitation extremes in Europe: intercomparison of scenarios from regional climate models. J Geophys Res 111:D06105. doi:10.1029/2005JD005965

    Article  Google Scholar 

  • Frich P, Alexander LV, Della-Marta P, Gleason B, Haylock M, Klein Tank AMG, Peterson T (2002) Observed coherent changes in climatic extremes during the second half of the twentieth century. Clim Res 19:193–212. doi:10.3354/cr019193

    Article  Google Scholar 

  • Früh B, Becker P, Deutschländer T, Hessel J-D et al (2011) Estimation of climate change impacts on the urban heat load using an urban climate model and regional climate projections. J Appl Meteor Climatol 50:167–184. doi:10.1175/2010JAMC2377.1

    Article  Google Scholar 

  • Gallego MC, Trigo RM, Vaquero JM, Brunet M et al (2011) Trends in frequency indices of daily precipitation over the Iberian Peninsula during the last century. J Geophys Res 116:D02109. doi:10.1029/2010JD014255

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Goodess CM, Jones PD (2002) Links between circulation and changes in the characteristics of Iberian rainfall. Int J Climatol 22:1593–1615. doi:10.1002/joc.810

    Article  Google Scholar 

  • Haugen JE, Iversen T (2008) Response in extremes of daily precipitation and wind from a downscaled multimodel ensemble of anthropogenic global climate change scenarios. Tellus A 60:411–426. doi:10.1111/j.1600-0870.2008.00315.x

    Article  Google Scholar 

  • Haylock MR, Goodess CM (2004) Interannual variability of European extreme winter rainfall and links with mean large-scale circulation. Int J Climatol 24:759–776. doi:10.1002/joc.1033

    Article  Google Scholar 

  • Haylock MR, Hofstra N, Klein Tank AMG, Klok EJ, Jones PD, New M (2008) A European daily high-resolution gridded data set of surface temperature and precipitation. J Geophys Res 113:D20119. doi:10.1029/2008JD010201

    Article  Google Scholar 

  • Hewitt CD, Griggs DJ (2004) Ensembles-based predictions of climate changes and their impacts. EOS, Trans Am Geophys Union 85:566. doi:10.1029/2004EO520005

    Article  Google Scholar 

  • Hollweg HD, Böhm U, Fast I, Hennemuth B et al (2008) Ensemble simulations over Europe with the regional climate model CLM forced with IPCC AR4 global scenarios. M & D Technical Report 3. http://www.mad.zmaw.de/service-support/documents/reports/. Accessed 15 Nov 2010. doi:10.2312/WDCC/MaD_TeReport_No03

  • Karl TR, Nicholls N, Ghazi A (1999) CLIVAR/GCOS/WMO workshop on indices and indicators for climate extremes: workshop summary. Clim Chang 42:3–7. doi:10.1023/A:1005491526870

    Article  Google Scholar 

  • Kilsby CG, Tellier SS, Fowler HJ, Howels TR (2007) Hydrological impacts of climate change on the Tejo and Guadiana Rivers. Hydrol Earth Syst Sc 11:1175–1189. doi:10.5194/hess-11-1175-2007

    Article  Google Scholar 

  • Kjellström E, Nikulin G, Hansson U, Strandberg G, Ullerstig A (2011) 21st century changes in the European climate: uncertainties derived from an ensemble of regional climate model simulations. Tellus A 63:24–40. doi:10.1111/j.1600-0870.2010.00475.x

    Article  Google Scholar 

  • Klein Tank AMG et al (2002) Daily dataset of 20th-century surface air temperature and precipitation series for the European climate assessment. Int J Climatol 22:1441–1453. doi:10.1002/joc.773

    Article  Google Scholar 

  • Kostopoulou E, Jones PD (2005) Assessment of climate extremes in the Eastern Mediterranean. Meteorol Atmos Phys 89:69–85. doi:10.1007/s00703-005-0122-2

    Article  Google Scholar 

  • Kyselý J, Domonkos P (2006) Recent increase in persistence of atmospheric circulation over Europe: comparison with long-term variations since 1881. Int J Climatol 26:461–483. doi:10.1002/joc.1265

    Article  Google Scholar 

  • Lautenschlager M, Keuler K, Wunram C, Keup-Thiel E et al (2009a) Climate simulation with CLM, climate of the 20th century run no. 1, data stream 3: European region MPI-M/MaD. World Data Center for Climate. doi:10.1594/WDCC/CLM_C20_1_D3

  • Lautenschlager M, Keuler K, Wunram C, Keup-Thiel E et al (2009b) Climate simulation with CLM, climate of the 20th century run no. 2, data stream 3: European region MPI-M/MaD. World Data Center for Climate. doi:10.1594/WDCC/CLM_C20_2_D3

  • Lautenschlager M, Keuler K, Wunram C, Keup-Thiel E et al (2009c) Climate simulation with CLM, scenario A1B run no. 1, data stream 3: European region MPI-M/MaD. World Data Center for Climate. doi:10.1594/WDCC/CLM_A1B_1_D3

  • Lautenschlager M, Keuler K, Wunram C, Keup-Thiel E et al (2009d) Climate simulation with CLM, scenario A1B run no. 2, data stream 3: European region MPI-M/MaD. World Data Center for Climate. doi:10.1594/WDCC/CLM_A1B_2_D3

  • Lautenschlager M, Keuler K, Wunram C, Keup-Thiel E et al (2009e) Climate simulation with CLM, scenario B1 run no. 1, data stream 3: European region MPI-M/MaD. World Data Center for Climate. doi:10.1594/WDCC/CLM_B1_1_D3

  • Lautenschlager M, Keuler K, Wunram C, Keup-Thiel E et al (2009f) Climate simulation with CLM, scenario B1 run no. 2, data stream 3: European region MPI-M/MaD. World Data Center for Climate. doi:10.1594/WDCC/CLM_B1_2_D3

  • Lehner B, Czisch G, Vassolo S (2005) The impact of global change on the hydropower potential of Europe: a model-based analysis. Energy Policy 33:839–855. doi:10.1016/j.enpol.2003.10.018

    Article  Google Scholar 

  • Malheiro AC, Santos JA, Fraga H, Pinto JG (2010) Climate change scenarios for viticultural zoning in Europe. Clim Res 43:163–177. doi:10.3354/cr00918

    Article  Google Scholar 

  • Mann HB, Whitney DR (1947) On a test of whether one of two random variables is stochastically larger than the other. Ann Math Stat 18:50–60

    Article  Google Scholar 

  • Maraun D, Wetterhall F, Ireson AM, Chandler RE et al (2010) Precipitation downscaling under climate change: recent developments to bridge the gap between dynamical models and the end user. Rev Geophys 48:RG3003. doi:10.1029/2009RG000314

    Article  Google Scholar 

  • Meehl GA, Stocker TF, Collins WD, Friedlingstein P, Gaye AT et al (2007) Global climate projections. In: Solomon S, Qin D, Manning M, Chen Z et al (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Moriondo M, Good P, Durão R, Bindi M, Giannakopoulos C, Corte-Real J (2006) Potential impact of climate change on fire risk in the Mediterranean area. Clim Res 31:85–95. doi:10.3354/cr031085

    Article  Google Scholar 

  • Nakićenović N, Swart R (eds) (2000) IPCC special report on emissions scenarios. Cambridge University Press, Cambridge

    Google Scholar 

  • Panferov O, Doering C, Rauch E, Sogachev A, Ahrends B (2009) Feedbacks of windthrow for Norway spruce and Scots pine stands under changing climate. Environ Res Lett 4:045019. doi:10.1088/1748-9326/4/4/045019

    Article  Google Scholar 

  • Pauling A, Luterbacher J, Casty C, Wanner H (2006) Five hundred years of gridded high-resolution precipitation reconstructions over Europe and the connection to large-scale circulation. Clim Dynam 26:387–405. doi:10.1007/s00382-005-0090-8

    Article  Google Scholar 

  • Pereira MG, Trigo RM, da Camara CC, Pereira JMC, Leite SM (2005) Synoptic patterns associated with large summer forest fires in Portugal. Agr Forest Meteorol 129:11–25. doi:10.1016/j.agrformet.2004.12.007

    Article  Google Scholar 

  • Peterson TC (2005) Climate change indices. WMO Bulletin 54:83–86

    Google Scholar 

  • Peterson TC, Folland C, Gruza G, Hogg W, Mokssit A, Plummer N (2001) Report on the activities of the Working Group on Climate Change Detection and Related Rapporteurs 1998–2001. World Meteorological Organization, WCDMP—no. 47/WMO—TD No. 1071. World Meteorological Organization, Geneva, p 143

    Google Scholar 

  • Pinto JG, Spangehl T, Ulbrich U, Speth P (2006) Assessment of winter cyclone activity in a transient ECHAM4-OPYC3 GHG experiment. Meteorol Z 15:279–291. doi:10.1127/0941-2948/2006/0128

    Article  Google Scholar 

  • Pinto JG, Ulbrich U, Leckebusch GC, Spangehl T, Reyers M, Zacharias S (2007) Changes in storm track and cyclone activity in three SRES ensemble experiments with the ECHAM5/MPI-OM1 GCM. Clim Dynam 29:195–210. doi:10.1007/s00382-007-0230-4

    Article  Google Scholar 

  • Ramos AM, Trigo RM, Santo FE (2011) Evolution of extreme temperatures over Portugal: recent changes and future scenarios. Clim Res 48:177–192. doi:10.3354/cr00934

    Article  Google Scholar 

  • Randall DA, Wood RA, Bony S, Colman R, Fichefet T et al (2007) Climate models and their evaluation. In: Solomon S, Qin D, Manning M, Chen Z et al (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Rockel B, Will A, Hense A (2008) The regional climate model COSMO-CLM. Meteorol Z (Berl) 17:347–348. doi:10.1127/0941-2948/2008/0309

    Article  Google Scholar 

  • Roeckner E, Brokopf R, Esch M, Giorgetta M, Hagemann S, Kornblueh L (2006) Sensitivity of simulated climate to horizontal and vertical resolution in the ECHAM5 atmosphere model. J Climate 19:3771–3791. doi:10.1175/JCLI3824.1

    Article  Google Scholar 

  • Roesch A, Jaeger EB, Lüthi D, Seneviratne SI (2008) Analysis of CCLM model biases in relation to intra-ensemble model variability. Meteorol Z 17:369–382. doi:10.1127/0941-2948/2008/0307

    Article  Google Scholar 

  • Rosário L (2004) Indicadores de desertificação para Portugal Continental. Direcção-Geral dos Recursos Florestais (ed), Lisboa, May 2004, pp 56

  • Santos JA, Corte-Real J, Leite SM (2005) Weather regimes and their connection to the winter rainfall in Portugal. Int J Climatol 25:33–50. doi:10.1002/joc.1101

    Article  Google Scholar 

  • Santos JA, Corte-Real J, Ulbrich U, Palutikof J (2007a) European winter precipitation extremes and surface large-scale circulation: a coupled model and its scenarios. Theor Appl Climatol 87:85–102. doi:10.1007/s00704-005-0224-2

    Article  Google Scholar 

  • Santos JA, Corte-Real J, Leite SM (2007b) Atmospheric large-scale dynamics during the 2004/2005 winter drought in Portugal. Int J Climatol 27:571–586. doi:10.1002/joc.1425

    Article  Google Scholar 

  • Santos JA, Andrade C, Corte-Real J, Leite SM (2009a) The role of large-scale eddies in the occurrence of precipitation deficits in Portugal. Int J Climatol 29:1493–1507. doi:10.1002/joc.1818

    Article  Google Scholar 

  • Santos JA, Pinto JG, Ulbrich U (2009b) On the development of strong ridge episodes over the eastern North Atlantic. Geophys Res Lett 36:L17804. doi:10.1029/2009GL039086

    Article  Google Scholar 

  • Scaife AA, Folland CK, Alexander LV, Moberg A, Knight JR (2008) European climate extremes and the North Atlantic Oscillation. J Climate 21:72–83. doi:10.1175/2007JCLI1631.1

    Article  Google Scholar 

  • Shapiro SS, Wilk MB (1965) An analysis of variance test for normality (complete samples). Biometrika 52:591–611. doi:10.1093/biomet/52.3-4.591

    Google Scholar 

  • Sillmann J, Roeckner E (2008) Indices for extreme events in projections of anthropogenic climate change. Clim Chang 86:83–104. doi:10.1007/s10584-007-9308-6

    Article  Google Scholar 

  • Stephenson DB, Pavan V, Collins M, Junge MM, Quadrelli R, participating CMIP2 modelling groups (2006) North Atlantic Oscillation response to transient greenhouse gas forcing and the impact on European winter climate: a CMIP2 multi-model assessment. Clim Dynam 27:401–420. doi:10.1007/s00382-006-0140-x

    Article  Google Scholar 

  • Tebaldi C, Hayhoe K, Arblaster JM, Meehl GA (2006) Going to extremes: an intercomparison of model-simulated historical and future changes in extreme events. Clim Chang 79:185–211. doi:10.1007/s10584-006-9051-4

    Article  Google Scholar 

  • Trenberth KE, Jones PD, Ambenje P, Bojariu R et al (2007) Observations: surface and atmospheric climate change. In: Solomon S, Qin D, Manning M, Chen Z et al (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Trigo RM, DaCamara C (2000) Circulation weather types and their impact on the precipitation regime in Portugal. Int J Climatol 20:1559–1581. doi:10.1002/1097-0088(20001115)20:13<1559::AID-JOC555>3.0.CO;2-5

    Article  Google Scholar 

  • Trigo RM, Osborn TJ, Corte-Real JM (2002) The North Atlantic Oscillation influence on Europe climate impacts and associated physical mechanisms. Clim Res 20:9–17. doi:10.3354/cr020009

    Article  Google Scholar 

  • Ulbrich U, Christoph M, Pinto JG, Corte-Real J (1999) Dependence of winter precipitation over Portugal on NAO and baroclinic wave activity. Int J Climatol 19:379–390. doi:10.1002/(SICI)1097-0088(19990330)19:4<379::AID-JOC357>3.0.CO;2-8

    Article  Google Scholar 

  • Ulbrich U, Leckebusch GC, Pinto JG (2009) Extra-tropical cyclones in the present and future climate: a review. Theor Appl Climatol 96:117–131. doi:10.1007/s00704-008-0083-8

    Article  Google Scholar 

  • Verde JC, Zêzere JL (2010) Assessment and validation of wildfire susceptibility and hazard in Portugal. Nat Hazards Earth Syst Sci 10:485–497. doi:10.5194/nhess-10-485-2010

    Article  Google Scholar 

  • Vicente-Serrano SM, Cuadrat-Prats JM (2007) Trends in drought intensity and variability in the middle Ebro valley (NE of the Iberian peninsula) during the second half of the twentieth century. Theor Appl Climatol 88:247–258. doi:10.1007/s00704-006-0236-6

    Article  Google Scholar 

  • Vicente-Serrano SM, Trigo RM, López-Moreno JI, Liberato MLR, Lorenzo-Lacruz J, Beguería S, Morán-Tejeda E, Kenawy AE (2011) Extreme winter precipitation in the Iberian Península in 2010: anomalies, driving mechanisms and future projections. Clim Res 46:51–65. doi:10.3354/cr00977

    Article  Google Scholar 

  • van der Linden P, Mitchell JFB (eds) (2009) ENSEMBLES: climate change and its impacts: summary of research and results from the ENSEMBLES project. Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK, p 160

  • Wijngaard J, Klein Tank AMG, Können GP (2003) Homogeneity of 20th century European daily temperature and precipitation series. Int J Climatol 23:679–692. doi:10.1002/joc.906

    Article  Google Scholar 

  • Wilcoxon F (1945) Individual comparison by ranking methods. Biometrics 1:80–83

    Article  Google Scholar 

Download references

Acknowledgements

We thank the MPI for Meteorology (Hamburg, Germany), the WDCC/CERA database and the COSMO-CLM community for providing the COSMO-CLM data. We acknowledge the E-OBS dataset from the EU-FP6 project ENSEMBLES (http://ensembles-eu.metoffice.com) and the data providers in the ECA&D project (http://eca.knmi.nl).

Author information

Authors and Affiliations

  1. ISEGI, Universidade Nova de Lisboa, 1070-312, Lisbon, Portugal

    Ana C. Costa

  2. Centre for the Research and Technology of Agro-Environmental and Biological Sciences, Physics Department, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal

    João A. Santos

  3. Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany

    Joaquim G. Pinto

Authors
  1. Ana C. Costa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. João A. Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Joaquim G. Pinto
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ana C. Costa.

Electronic supplementary material

This Appendix presents a set of additional figures addressing the results obtained for the B1 SRES scenario and for the two ensemble members of the A1B SRES scenario.

Fig. A1

Results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the ensemble member 1 medians of PRCPTOT between future climate conditions under the A1B SRES scenario (2071–2100) and recent–past climate conditions (1961–2000) in a autumn, b winter, c spring and d annual values (JPEG 95 kb)

High resolution image (TIFF 12035 kb)

Fig. A2

Results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the autumn ensemble member 1 medians of each index for future climate conditions under the A1B SRES scenario (2071–2100) and recent–past climate conditions (1961–2000): a Rx5day, b R95T, c R95pTOT and d CDD (JPEG 86 kb)

High resolution image (TIFF 12035 kb)

Fig. A3

Results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the winter ensemble member 1 medians of each index for future climate conditions under the A1B SRES scenario (2071–2100) and recent–past climate conditions (1961–2000): a Rx5day, b R95T, c R95pTOT and d CDD (JPEG 94 kb)

High resolution image (TIFF 12035 kb)

Fig. A4

Results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the spring ensemble member 1 medians of each index for future climate conditions under the A1B SRES scenario (2071–2100) and recent–past climate conditions (1961–2000): a Rx5day, b R95T, c R95pTOT and d CDD (JPEG 82 kb)

High resolution image (TIFF 12035 kb)

Fig. A5

Results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the ensemble member 2 medians of PRCPTOT between future climate conditions under the A1B SRES scenario (2071–2100) and recent–past climate conditions (1961–2000) in a autumn, b winter, c spring and d annual values (JPEG 90 kb)

High resolution image (TIFF 12035 kb)

Fig. A6

Results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the autumn ensemble member 2 medians of each index for future climate conditions under the A1B SRES scenario (2071–2100) and recent–past climate conditions (1961–2000): a Rx5day, b R95T, c R95pTOT and d CDD (JPEG 91 kb)

High resolution image (TIFF 12035 kb)

Fig. A7

Results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the winter ensemble member 2 medians of each index for future climate conditions under the A1B SRES scenario (2071–2100) and recent–past climate conditions (1961–2000): a Rx5day, b R95T, c R95pTOT and d CDD (JPEG 92 kb)

High resolution image (TIFF 12035 kb)

Fig. A8

Results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the spring ensemble member 2 medians of each index for future climate conditions under the A1B SRES scenario (2071–2100) and recent–past climate conditions (1961–2000): a Rx5day, b R95T, c R95pTOT and d CDD (JPEG 94 kb)

High resolution image (TIFF 12035 kb)

Fig. A9

As Fig. 3 but for the B1 SRES scenario: results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the two-member ensemble medians of PRCPTOT between future climate conditions under the B1 SRES scenario (2071–2100) and recent–past climate conditions (1961–2000) in a autumn, b winter, c spring and d annual values (JPEG 90 kb)

High resolution image (TIFF 12035 kb)

Fig. A10

As Fig. 4 but for the B1 SRES scenario: results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the autumn two-member ensemble medians of each index for future climate conditions under the B1 SRES scenario (2071–2100) and recent–past climate conditions (1961–2000): a Rx5day, b R95T, c R95pTOT and d CDD (JPEG 91 kb)

High resolution image (TIFF 12035 kb)

Fig. A11

As Fig. 5 but for the B1 SRES scenario: results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the winter two-member ensemble medians of each index for future climate conditions under the B1 SRES scenario (2071–2100) and recent–past climate conditions (1961–2000): a Rx5day, b R95T, c R95pTOT and d CDD (JPEG 90 kb)

High resolution image (TIFF 12035 kb)

Fig. A12

As Fig. 6 but for the B1 SRES scenario: results of the one-sided Wilcoxon–Mann–Whitney tests for the differences in the spring two-member ensemble medians of each index for future climate conditions under the B1 SRES scenario (2071–2100) and recent–past climate conditions (1961–2000): a Rx5day, b R95T, c R95pTOT and d CDD (JPEG 92 kb)

High resolution image (TIFF 12035 kb)

Fig. A13

As Fig. 7 (right panels) but for the B1 SRES scenario: anomalies between future (2071–2100) and recent–past (1961–2000) fields in the composites of the mean sea level pressure (in hectopascals) within the Euro-Atlantic sector simulated by the ECHAM5 under the B1 SRES scenario in a autumn, b winter and c spring. Only differences with a statistical significance level of 5% are depicted (JPEG 340 kb)

High resolution image (TIFF 102 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Costa, A.C., Santos, J.A. & Pinto, J.G. Climate change scenarios for precipitation extremes in Portugal. Theor Appl Climatol 108, 217–234 (2012). https://doi.org/10.1007/s00704-011-0528-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-011-0528-3

Keywords

Search

Navigation