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Evaluation of different downscaling techniques for hydrological climate-change impact studies at the catchment scale

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Abstract

Hydrological modeling for climate-change impact assessment implies using meteorological variables simulated by global climate models (GCMs). Due to mismatching scales, coarse-resolution GCM output cannot be used directly for hydrological impact studies but rather needs to be downscaled. In this study, we investigated the variability of seasonal streamflow and flood-peak projections caused by the use of three statistical approaches to downscale precipitation from two GCMs for a meso-scale catchment in southeastern Sweden: (1) an analog method (AM), (2) a multi-objective fuzzy-rule-based classification (MOFRBC) and (3) the Statistical DownScaling Model (SDSM). The obtained higher-resolution precipitation values were then used to simulate daily streamflow for a control period (1961–1990) and for two future emission scenarios (2071–2100) with the precipitation-streamflow model HBV. The choice of downscaled precipitation time series had a major impact on the streamflow simulations, which was directly related to the ability of the downscaling approaches to reproduce observed precipitation. Although SDSM was considered to be most suitable for downscaling precipitation in the studied river basin, we highlighted the importance of an ensemble approach. The climate and streamflow change signals indicated that the current flow regime with a snowmelt-driven spring flood in April will likely change to a flow regime that is rather dominated by large winter streamflows. Spring flood events are expected to decrease considerably and occur earlier, whereas autumn flood peaks are projected to increase slightly. The simulations demonstrated that projections of future streamflow regimes are highly variable and can even partly point towards different directions.

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References

  • Bardossy A, Plate EJ (1992) Space-time model for daily rainfall using atmospheric circulation patterns. Water Resour Res 28(5):1247–1259. doi:10.1029/91WR02589

    Article  Google Scholar 

  • Bardossy A, Duckstein L, Bogardi I (1995) Fuzzy rule-based classification of atmospheric circulation patterns. Int J Climatol 15(10):1087–1097. doi:10.1002/joc.3370151003

    Article  Google Scholar 

  • Bardossy A, Bogardi I, Matyasovszky I (2005) Fuzzy rule-based downscaling of precipitation. Theor Appl Climatol 82(1):119–129. doi:10.1007/s00704-004-0121-0

    Article  Google Scholar 

  • Beldring S, Engen-Skaugen T, Førland EJ, Roald LA (2008) Climate change impacts on hydrological processes in Norway based on two methods for transferring regional climate model results to meteorological station sites. Tellus A 60(3):439–450. doi:10.1111/j.1600-0870.2008.00306.x

    Article  Google Scholar 

  • Bergström S (1976) Development and application of a conceptual runoff model for Scandinavian catchments. SMHI, Report RHO 7. Norrköping

  • Bergström S (1992) The HBV model—its structure and applications. SMHI, Hydrologi Report RH 4. Norrköping

  • Bergström S, Carlsson B, Gardelin M, Lindström G, Pettersson A, Rummukainen M (2001) Climate change impacts on runoff in Sweden—assessments by global climate models, dynamical downscaling and hydrological modelling. Clim Res 16:101–112. doi:10.3354/cr016101

    Article  Google Scholar 

  • Beven KJ (2002) Rainfall—runoff modelling: the primer. Wiley, Chinchester, England

    Google Scholar 

  • Busuioc A, Giorgi F, Bi X, Ionita M (2006) Comparison of regional climate model and statistical downscaling simulations of different winter precipitation change scenarios over Romania. Theor Appl Climatol 86(1):101–123. doi:10.1007/s00704-005-0210-8

    Article  Google Scholar 

  • Casanova S, Ahrens B (2009) On the weighting of multimodel ensembles in seasonal and short-range weather forecasting. Mon Weather Rev 137(11):3811–3822. doi:10.1175/2009MWR2893.1

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Chu J, Xia J, Xu CY, Singh V (2010) Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China. Theor Appl Climatol 99(1):149–161. doi:10.1007/s00704-009-0129-6

    Article  Google Scholar 

  • Fowler HJ, Ekström M (2009) Multi-model ensemble estimates of climate change impacts on UK seasonal precipitation extremes. Int J Climatol 29(3):385–416. doi:10.1002/joc.1827

    Article  Google Scholar 

  • Fowler H, Kilsby C (2007) Using regional climate model data to simulate historical and future river flows in northwest England. Clim Change 80(3):337–367. doi:10.1007/s10584-006-9117-3

    Article  Google Scholar 

  • Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 27(12):1547–1578. doi:10.1002/joc.1556

    Article  Google Scholar 

  • Frei C, Alberghi S, Amici M, Anagnostopoulou C, Bardossy A, Cacciamani C, Goodess C, Haylock M, Hundecha Y, Maheras P, Marchesi S, Morgillo A, Pavan V, Plaut G, Schmidli J, Smith T, Simonnet E, Tolika K, Tomozeiu R, Tosi E, Wilby R (2005) STARDEX—Recommendations on the most reliable predictor variables and evaluation of inter-relationships (Deliverable D13) (No. EVK2-CT-2001-00115). online: http://www.cru.uea.ac.uk/projects/stardex/deliverables/D13/. Accessed 24 Sept 2010

  • Goodess CM, Anagnostopoulou C, Bardossy A, Frei C, Harpham C, Haylock MR, Hundecha Y, Maheras P, Ribalaygua J, Schmidli J, Schmith T, Tolika K, Tomozeiu R, Wilby RL (2010) An intercomparison of statistical downscaling methods for Europe and European regions—assessing their performance with respect to extreme weather events and the implications for climate change applications. Clim Change (submitted)

  • Hanssen-Bauer I, Achberger C, Benestad R, Chen D, Førland E (2005) Statistical downscaling of climate scenarios over Scandinavia. Clim Res 29(3):255–268. doi:10.3354/cr029255

    Article  Google Scholar 

  • Harlin J, Kung C (1992) Parameter uncertainty and simulation of design floods in Sweden. J Hydrol 137(1–4):209–230. doi:10.1016/0022-1694(92)90057-3

    Article  Google Scholar 

  • Haylock MR, Cawley GC, Harpham C, Wilby RL, Goodess CM (2006) Downscaling heavy precipitation over the United Kingdom: a comparison of dynamical and statistical methods and their future scenarios. Int J Climatol 26(10):1397–1415. doi:10.1002/joc.1318

    Article  Google Scholar 

  • Hellström C, Chen D, Achberger C, Räisänen J (2001) Comparison of climate change scenarios for Sweden based on statistical and dynamical downscaling of monthly precipitation. Clim Res 19:45–55. doi:10.3354/cr019045

    Article  Google Scholar 

  • Hersbach H (2000) Decomposition of the continuous ranked probability score for ensemble prediction systems. Weather Forecast 15(5):559–570. doi:10.1175/1520-0434(2000)015<0559:DOTCRP>2.0.CO;2

    Article  Google Scholar 

  • Hewitson BC, Crane R (1996) Climate downscaling: techniques and application. Clim Res 7(2):85–95. doi:10.3354/cr0007085

    Article  Google Scholar 

  • IPCC (2007) 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, UK, and New York, USA

  • Johansson B (2002) Estimation of areal precipitation for hydrological modelling in Sweden. Dissertation, Göteborg University

  • Johns TC, Gregory JM, Ingram WJ, Johnson CE, Jones A, Lowe JA, Mitchell JFB, Roberts DL, Sexton DMH, Stevenson DS, Tett SFB, Woodage MJ (2003) Anthropogenic climate change for 1860 to 2100 simulated with the HadCM3 model under updated emissions scenarios. Clim Dynam 20(6):583–612. doi:10.1007/s00382-002-0296-y

    Google Scholar 

  • Kalnay EC, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J (1996) The NCEP/NCAR 40-year reanalysis project. B Am Meteorol Soc 77(3):437–471. doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2

    Article  Google Scholar 

  • Kay AL, Davies HN, Bell VA, Jones RG (2009) Comparison of uncertainty sources for climate change impacts: flood frequency in England. Clim Change 92(1):41–63. doi:10.1007/s10584-008-9471-4

    Article  Google Scholar 

  • Kug JS, Lee JY, Kang IS, Wang B, Park CK (2008) Optimal multimodel ensemble method in seasonal climate prediction. Asia-Pac J Atmos Sci 44(3):259–267

    Google Scholar 

  • Lindström G, Bergström S (1992) Improving the HBV and PULSE-models by use of temperature anomalies. Vannet i Norden 1:16–23

    Google Scholar 

  • Lindström G, Johansson B, Persson M, Gardelin M, Bergström S (1997) Development and test of the distributed HBV-96 hydrological model. J Hydrol 201(1–4):272–288. doi:10.1016/S0022-1694(97)00041-3

    Article  Google Scholar 

  • Maraun D, Wetterhall F, Ireson AM, Chandler RE, Kendon EJ, Widmann M, Brienen S, Rust HW, Sauter T, Themeßl M, Venema VKC, Chun KP, Goodess CM, Jones RG, Onof C, Vrac M, Thiele-Eich I (2010) Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user. Rev Geophys 48(3):RG3003. doi:10.1029/2009RG000314

    Article  Google Scholar 

  • Moore K, Pierson D, Pettersson K, Schneiderman E, Samuelsson P (2008) Effects of warmer world scenarios on hydrologic inputs to Lake Mälaren, Sweden and implications for nutrient loads. Hydrobiologia 599(1):191–199. doi:10.1007/s10750-007-9197-8

    Article  Google Scholar 

  • Murphy J (1999) An evaluation of statistical and dynamical techniques for downscaling local climate. J Clim 12(8):2256–2284. doi:10.1175/1520-0442(1999)012<2256:AEOSAD>2.0.CO;2UR

    Article  Google Scholar 

  • Murphy J (2000) Predictions of climate change over Europe using statistical and dynamical downscaling techniques. Int J Climatol 20(5):489–501. doi:10.1002/(SICI)1097-0088(200004)20:5<489:AID-JOC484>3.0.CO;2-6

    Article  Google Scholar 

  • Nakicenovic N, Swart R (2000) Special report on emissions scenarios: a special report of working group III of the intergovernmental panel on climate change, 1st edn. Cambridge University Press, Cambridge, UK

    Google Scholar 

  • Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part I—A discussion of principles. J Hydrol 10(3):282–290. doi:10.1016/0022-1694(70)90255-6

    Article  Google Scholar 

  • Obled C, Bontron G, Garçon R (2002) Quantitative precipitation forecasts: a statistical adaptation of model outputs through an analogues sorting approach. Atmos Res 63(3–4):303–324. doi:10.1016/S0169-8095(02)00038-8

    Article  Google Scholar 

  • Roeckner E, Arpe K, Bengtsson L, Christoph M, Dümenil L, Esch M, Giorgetta M, Schulzweida U, Claussen M, Schlese U (1996) The atmospheric general circulation model ECHAM-4: model description and simulation of present-day climate (No. 218). Max-Plank-Institut für Meteorologie, Hamburg

    Google Scholar 

  • Schmidli J, Frei C, Vidale PL (2006) Downscaling from GCM precipitation: a benchmark for dynamical and statistical downscaling methods. Int J Climatol 26(5):679–689. doi:10.1002/joc.1287

    Article  Google Scholar 

  • Seibert J (1999) Regionalisation of parameters for a conceptual rainfall-runoff model. Agr Forest Meteorol 98–99:279–293. doi:10.1016/S0168-1923(99)00105-7

    Article  Google Scholar 

  • Seibert J (2000) Multi-criteria calibration of a conceptual runoff model using a genetic algorithm. Hydrol Earth Syst Sci 4(2):215–224. doi:10.5194/hess-4-215-2000

    Article  Google Scholar 

  • Seibert J (2003) Reliability of model predictions outside calibration conditions. Nord Hydrol 34(5):477–492. doi:10.2166/nh.2003.028

    Google Scholar 

  • Teutschbein C, Seibert J (2010) Regional climate models for hydrological impact studies at the catchment scale: a review of recent modeling strategies. Geography Compass 4(7):834–860. doi:10.1111/j.1749-8198.2010.00357.x

    Article  Google Scholar 

  • Teweles S, Wobus H (1954) Verification of prognostic charts. B Am Meteorol Soc 35:455–463

    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, FitzRoy Road, Exeter EX1 3PB, UK

  • Wetterhall F, Halldin S, Xu CY (2005) Statistical precipitation downscaling in central Sweden with the analogue method. J Hydrol 306(1–4):174–190. doi:10.1016/j,jhydrol.2004.09.008

    Article  Google Scholar 

  • Wetterhall F, Bardossy A, Chen D, Halldin S, Xu CY (2006) Daily precipitation-downscaling techniques in three Chinese regions. Water Resour Res 42. doi:10.1029/2005WR004573

  • Wetterhall F, Halldin S, Xu CY (2007) Seasonality properties of four statistical-downscaling methods in central Sweden. Theor Appl Climatol 87(1–4):123–137. doi:10.1007/s00704-005-0223-3

    Article  Google Scholar 

  • Wetterhall F, Bardossy A, Chen DL, Halldin S, Xu CY (2009) Statistical downscaling of daily precipitation over Sweden using GCM output. Theor Appl Climatol 96(1–2):95–103. doi:10.1007/s00704-008-0038-0

    Article  Google Scholar 

  • Wilby RL, Dawson CW (2007) SDSM 4.2—A decision support tool for the assessment of regional climate change impacts: User Manual. Online: https://co-public.lboro.ac.uk/cocwd/SDSM/main.html. Accessed 24 Sept 2010

  • Wilby RL, Wigley TML (1997) Downscaling general circulation model output: a review of methods and limitations. Prog Phys Geog 21(4):530–548. doi:10.1177/030913339702100403

    Article  Google Scholar 

  • Wilby RL, Hay L, Leavesley G (1999) A comparison of downscaled and raw GCM output: implications for climate change scenarios in the San Juan River basin, Colorado. J Hydrol 225(1–2):67–91. doi:10.1016/S0022-1694(99)00136-5

    Article  Google Scholar 

  • Wilby RL, Hay LE, Gutowski WJ Jr, Arritt RW, Takle ES, Pan Z, Leavesley GH, Clark MP (2000) Hydrological responses to dynamically and statistically downscaled climate model output. Geophys Res Lett 27(8):1199–1202. doi:200010.1029/1999GL006078

    Article  Google Scholar 

  • Wilby RL, Dawson CW, Barrow EM (2002) SDSM—a decision support tool for the assessment of regional climate change impacts. Environ Modell Softw 17(2):145–157. doi:10.1016/S1364-8152(01)00060-3

    Article  Google Scholar 

  • Wilby RL, Tomlinson OL, Dawson CW (2003) Multi-site simulation of precipitation by conditional resampling. Clim Res 23(3):183–194. doi:10.3354/cr023183

    Article  Google Scholar 

  • Wilby RL, Charles SP, Zorita E, Timbal B, Whetton P, Mearns LO (2004) Guidelines for use of climate scenarios developed from statistical downscaling methods. Supporting material to the Intergovernmental Panel on Climate Change 27

  • Wilks DS (2005) Statistical methods in the atmospheric sciences, 2nd edn. Academic Press, London

    Google Scholar 

  • Xu CY (2000) Modelling the effects of climate change on water resources in Central Sweden. Water Resour Manag 14(3):177–189. doi:10.1023/A:1026502114663

    Article  Google Scholar 

  • Yang W, Bardossy A, Caspary HJ (2010) Downscaling daily precipitation time series using a combined circulation- and regression-based approach. Theor Appl Climatol 102:439–454. doi:10.1007/s00704-010-0272-0

    Article  Google Scholar 

  • Zorita E, von Storch H (1999) The analog method as a simple statistical downscaling technique: comparison with more complicated methods. J Clim 12(8):2474. doi:10.1175/1520-0442(1999)012<2474:TAMAAS>2.0.CO;2

    Article  Google Scholar 

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Acknowledgments

We thank the Swedish Meteorological and Hydrological Institute (SMHI) for providing meteorological and hydrological observation data. The ENSEMBLES data used in this work was funded by the EU FP6 Integrated Project ENSEMBLES (Contract number 505539) whose support is gratefully acknowledged. SDSM 4.2.2 was supplied by Drs. R. L. Wilby and C. W. Dawson supported by the Environmental Agency of England and Wales as part of the Thames Estuary 2100 project. Furthermore, we acknowledge financial support from FORMAS, the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning, (Grant No. 2007-1433) and the National Environmental Research Council FREE project (Grant No. NE/E002242/1).

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Authors and Affiliations

  1. Department of Physical Geography and Quaternary Geology, Stockholm University, 10691, Stockholm, Sweden

    Claudia Teutschbein & Jan Seibert

  2. Department of Geography, King’s College London, Strand, London, WC2R2LS, UK

    Fredrik Wetterhall

  3. Department of Earth Sciences, Uppsala University, 75236, Uppsala, Sweden

    Jan Seibert

  4. Swedish Meteorological and Hydrological Institute, 60176, Norrköping, Sweden

    Fredrik Wetterhall & Jan Seibert

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  1. Claudia Teutschbein
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Correspondence to Claudia Teutschbein.

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Teutschbein, C., Wetterhall, F. & Seibert, J. Evaluation of different downscaling techniques for hydrological climate-change impact studies at the catchment scale. Clim Dyn 37, 2087–2105 (2011). https://doi.org/10.1007/s00382-010-0979-8

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