Abstract
In the current study, two regional climate models (MM5 and REMO) driven by different global boundary conditions (the ERA40 reanalysis and the ECHAM5 model) are one-way coupled to the uncalibrated hydrological process model PROMET to analyze the impact of global boundary conditions, dynamical regionalization and subsequent statistical downscaling (bilinear interpolation, correction of subgrid-scale variability and combined correction of subgrid-scale variability and bias) on river discharge simulation. The results of 12 one-way coupled model runs, set up for the catchment of the Upper Danube (Central Europe) over the historical period 1971–2000, prove the expectation that the global boundaries applied to force the RCMs strongly influence the accuracy of simulated river discharge. It is, however, noteworthy that all efficiency criteria in case of bias corrected MM5 simulations indicate better performance under ERA40 boundaries, whereas REMO-driven hydrological simulations better correspond to measured discharge under ECHAM5 boundaries. Comparing the hydrological results achievable with MM5 and REMO, the application of bias-corrected MM5 simulations turned out to allow for a more accurate simulation of discharge, while the variance in simulated discharge in most cases was better reflected in case of REMO forcings. The correction of subgrid-scale variability within the downscaling of RCM simulations compared to a bilinear interpolation allows for a more accurate simulation of discharge for all model configurations and all discharge criteria considered (mean monthly discharge, mean monthly low-flow and peak-flow discharge). Further improvements in the hydrological simulations could be achieved by eliminating the biases (in terms of deviations from observed meteorological conditions) inherent in the driving RCM simulations, regardless of the global boundary conditions or the RCM applied. In spite of all downscaling and bias correction efforts described, the RCM-driven hydrological simulations remain less accurate than those achievable with spatially distributed meteorological observations.
References
Bach H, Braun M, Lampart G, Mauser W (2003) The use of remote sensing for hydrological parameterisation of Alpine catchments. Hydrol Earth Syst Sci 7(6):862–876
Bach H, Mauser W, Schneider K (2003) The use of radiative transfer models for remote sensing data assimilation in crop growth models. In: Stafford J, Werner A (eds) Precision Agriculture. Wageningen Academic Publishers, The Netherlands
Bach H, Verhoef W, Schneider K (2000) Coupling remote sensing observation models and a growth model for improved retrieval of (geo)biophysical information from optical remote sensing data. Remote Sens Agric Ecosyst Hydrol 4171:1–11
Bengtsson L, Hodges KI, Roeckner E (2006) Storm tracks and climate change. J Clim 19:3518–3543
Chen F, Dudhia J (2001) Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Mon Weather Rev 129:569–585
Chen F, Dudhia J (2001) Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part II: preliminary model validation. Mon Weather Rev 129:587–604
Christensen JH, Carter TR, Rummukainen M, Amanatidis G (2007) Evaluating the performance and utility of regional climate models: the PRUDENCE project. Clim Change 81:1–6
Cosgrove BA, Lohmann D, Mitchell KE, Houser PR, Wood EF, Schaake JC, Robock A, Marshall C, Sheffield J, Duan Q, Luo L, Higgins RW, Pinker RT, Tarpley JD, Meng J (2003) Real-time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project. J Geophys Res 108:1–12
Cubasch U (2001) Simulations of regional climate change. In: Lozan JL, Grassl H, Hupfer P (eds) Climate of the 21st century: changes and risks. Wissenschaftliche Auswertungen, Hamburg
Daly C, Neilson RP, Phillips DL (1994) A statisticaltopographic model for mapping climatological precipitation over mountainous terrain. J Appl Meteorol 33:140–158
Dudhia J (1993) A nonhydrostatic version of the Penn State/NCAR mesoscale model: validation tests and simulation of an Atlantic cyclone and cold front. Mon Weather Rev 121:1493–1513
Früh B, Schipper JW, Pfeiffer A, Wirth V (2006) A pragmatic approach for downscaling precipitation in alpine-scale complex terrain. Meteorol Z 15(6):631–646
Giorgi F, Mearns LO (1991) Introduction to special section: regional climate modelling revisited. J Geophys Res 104:6335–6352
Grasso LD (2000) The differentiation between grid spacing and resolution and their application to numerical modeling. Bull Am Meteorol Soc 81(3):579–580
Grell GA, Dudhia J, Stauffer DR (1994) A description of the fifth-generation Penn State/NCAR mesoscale model (MM5), NCAR/TN-398+STR. Technical report, National Centre for Atmospheric Research, Boulder, Colorado, USA
Haddeland I, Heinke J, Vo F, Eisner S, Chen C, Hagemann S, Ludwig F (2012) Effects of climate model radiation, humidity and wind estimates on hydrological simulations. Hydrol Earth Syst Sci 16:305–318
Hagemann S, Botzet M, Machenhauer B (2001) The summer drying problem over south-eastern Europe: sensitivity of the limited area model HIRHAM4 to improvements in physical parameterization and resolution. Phys Chem Earth 26:391–396
Hagemann S, Gttel H, Jacob D, Lorenz P, Roeckner E (2009) Improved regional scale processes reflected in projected hydrological changes over large european catchments. Clim Dyn 32:767–781
Hank T (2008) A biophysically based coupled model approach for the assessment of canopy processes under climate change conditions. PhD thesis, Ludwig-Maximilians-University, Munich (Germany)
IPCC (2007) Contribution of working group I to the fourth 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) Climate change 2007: the physical science basis. Cambridge University Press, Cambridge
Jacob D (2001) A note to the simulation of the annual and interannual variability of the water budget over the baltic sea drainage basin. Meteorol Atmos Phys 77(1-4):61–74
Jacob D, Brring L, Christensen OB, Christensen JH, de Castro M, Dqu M, Giorgi F, Hagemann S, Hirschi M, Jones R, Kjellstrm E, Lenderink G, Rockel B, Snchez E, Schr C, Seneviratne SI, Somot S, van Ulden A, van den Hurk B (2007) An inter-comparison of regional climate models for Europe: model performance in present-day climate. Clim Change 81:31–52
Janjic ZI (1994) The step-mountain eta coordinate model: further development of the convection, viscous sublayer, and turbulent closure schemes. Mon Weather Rev 122:927–945
Kain JS (2004) The Kain–Fritsch convective parameterization: an update. J Appl Meteorol 43:170–181
Kain JS, Fritsch JM (1990) A one-dimensional entraining/detraining plume model and its application in convective parameterization. J Atmos Sci 47:2784–2802
Kain JS, Fritsch JM (1993) Convective parameterization for mesoscale models: Tthe Kain–Fritsch scheme. In: Emanuel KA, Raymond DJ (eds) The representation of cumulus convection in numerical models. Meteorological monograph series, vol 24, no 46
Kidson JW, Thompson CS (1998) A comparison of statistical and model-based downscaling techniques for estimating local climate variations. J Clim 11:735–753
Kotlarski S, Block A, Böhm U, Jacob D, Keuler K, Knoche R, Rechid D, Walter A (2005) Regional climate model simulations as input for hydrological applications: evaluation of uncertainties. Adv Geosci 5:119–125
Krause P, Boyle DP, Bäse F (2005) Comparison of different efficiency criteria for hydrological model assessment. Adv Geosci 5:89–97
Kunstmann H, Schneider K, Forkel R, Knoche R (2004) Impact analysis of climate change for an Alpine catchment using high resolution dynamic downscaling of ECHAM4 time slices. Hydrol Earth Syst Sci 8(6):1030–1044
Laux P, Vogl S, Qiu W, Knoche HR, Kunstmann H (2011) Copula-based statistical refinement of precipitation in RCM simulations over complex terrain. Hydrol Earth Syst Sci Discuss 8:3001–3045
Leavesley GH, Stannard LG (1995) The precipitation-runoff modeling system—PRMS. In: Singh VP (ed) Computer models of watershed hydrology. Water Resources Publications, Highlands Ranch, pp 281–310
Leung LR, Qian Y, Bian X, Washington WM, Han J, Roads JO (2004) Mid-century ensemble regional climate change scenarios for the Western United States. Clim Change 62:75–113
Liang X, Lettenmaier DP, Wood EF, Burges SJ (1994) A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J Geophys Res 99:14415–14428
Louis JF (1979) A parametric model of vertical eddy fluxes in the atmosphere. Bound Layer Meteorol 17:187–202
Ludwig R, Mauser W (2000) Modelling catchment hydrology within a GIS based SVAT-model framework. Hydrol Earth Syst Sci 4(2):239–249
Ludwig R, Mauser W, Niemeyer S, Colgan A, Stolz R, Escher-Vetter H, Kuhn M, Reichstein M, Tenhunen J, Kraus A, Ludwig M, Barth M, Hennicker R (2003) Web-based modelling of energy, water and matter fluxes to support decision making in mesoscale catchments the integrative perspective of GLOWA-Danube. Phys Chem Earth 28:621–634
Ludwig R, May I, Turcotte R, Vescovi L, Braun M, Cyr J, Fortin LG, Chaumont D, Biner S, Chartier I, Caya D, Mauser W (2009) The role of hydrological model complexity and uncertainty in climate change impact assessment. Adv Geosci 21:63–71
Ludwig R, Probeck M, Mauser W (2003) Mesoscale water balance modelling in the upper Danube watershed using sub-scale land cover information derived from NOAA-AVHRR imagery and GIS-techniques. Phys Chem Earth 28:1351–1364
Majewski D (1991) The Europa-Modell of the Deutscher Wetterdienst. In: ECMWF seminar on numerical methods in atmospheric models, vol 2, pp 147–191
Marke T (2008) Development and application of a model interface to couple land surface models with regional climate models for climate change risk assessment in the upper Danube watershed. PhD thesis, Ludwig-Maximilians-University, Munich
Marke T, Mauser W, Pfeiffer A, Zängl G (2011) A pragmatic approach for the downscaling and bias correction of regional climate simulations: evaluation in hydrological modeling. Geosci Model Dev 4:759–770
Marke T, Strasser U, Kraller G, Warscher M, Kunstmann H, Franz H, Vogel M (2013) The Berchtesgaden National Park (Bavaria, Germany)—a platform for interdisciplinary catchment research. Environ Earth Sci 69(2):679–694
Mauser W, Bach H (2009) PROMET Large scale distributed hydrological modelling to study the impact of climate change on the water flows of mountain watersheds. J Hydrol 376:362–377
Mauser W, Marke T (2009) Climate change and water resources: scenarios of low-flow conditions in the upper danube river basin. IAHS Publ 327:225–236
Mauser W, Schädlich S (1998) Modeling the spatial distribution of evapotranspiration on different scale using remote sensing data. J Hydrol (Special BAHC Issue):212–213
Mearns LO, Bogardi I, Giorgi F, Matyasovszky I, Palecki M (1999) Comparison of climate change scenarios generated from regional climate model experiments and statistical downscaling. J Geophys Res 104:6603–6621
Morcrette JJ, Smith L, Fourquart Y (1986) Pressure and temperature dependance of the absorption in longwave radiation parameterizations. Beitraege zur Physik der Atmosphaere 59:455–469
MPI (2013) REMO UBA: climate simulations for Germany, Austria and Switzerland, https://remo-rcm.de/?id=1189. Accessed March 2013
Muerth MJ (2008) A soil temperature and energy balance model for integrated assessment of global change impacts at the regional scale. PhD thesis, Ludwig-Maximilians-University, Munich
Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models. Part I: a discussion of principles. J Hydrol 10:282–290
Nasonova ON, Gusev YM, Kovalev YE (2011) Impact of uncertainties in meteorological forcing data and land surface parameters on global estimates of terrestrial water balance components. Hydrol Process 25:1074–1090
Nordeng TE (1994) Extended versions of the convective parametrization scheme at ECMWF and their impact on the mean and transient activity of the model in the tropics. Technical Report 206, ECMWF Research Department
Pfeifer S (2006) Modeling cold cloud processes with the regional climate model REMO. Reports on Earth System Science. Technical report, Max Planck Institute for Meteorology
Pfeiffer A, Zängl G (2010) Validation of climate-mode MM5- simulations for the European Alpine Region. Theor Appl Climatol 101:93–108
Pfeiffer A, Zängl G (2011) Regional climate simulations for the European Alpine Region—sensitivity of precipitation to large scale flow conditions of driving input data. Theor Appl Climatol 105:325–340
Pielke RA (2002) Mesoscale meteorological modeling. International Geophysics Series, vol 78, 2nd edn. Academic Press, London
Redler R, Valcke S, Ritzdorf H (2010) OASIS4—a coupling software for next generation earth system modelling. Geosci Model Dev 3:87–104
Reisner J, Rasmussen RM, Bruintjes RT (1998) Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model. Q J R Meteorol Soc 124:1071–1107
Roeckner E, Arpe K, Bentsson L, Christoph M, Claussen M, Dümenil L, Esch M, Giorgetta M, Schlese U, Schulzweida U (1996) The atmospheric genaral circulation model ECHAM-4: model description and simulation of present day climate. Technical Report 218, Max-Planck Institute for Meteorology
Roeckner E, Bäuml G, Bonaventura L, Brokopf R, Esch M, Giorgetta M, Hagemann S, Kirchner I, Kornblueh L, Manzini E, Rhodin A, Schlese U, Schulzweida U, Tompkins A (2003) The atmospheric general circulation model ECHAM5. Part I: model description. Technical Report 349, Max-Planck Institute for Meteorology
Semmler T, Jacob D, Schlünzen KH, Podzun R (2004) Influence of sea ice treatment in a regional climate model on boundary layer values in the fram strait region. Mon Weather Rev 132:985–999
Sevruk B (1985) Systematischer Niederschlagsmessfehler in der Schweiz. In: Sevruk B (ed.) Der Niederschlag in der Schweiz, Beiträge zur Geologie der Schweiz -Hydrologie, no 31, pp 65–75
Shi XG, Wild M, Lettenmaier DP (2010) Surface radiative fluxes over the span-arctic land region: variability and trends. J Geophys Res 115. doi:10.1029/2010JD014402
Strasser U, Marke T, Sass O, Birk S, Winkler G (2013) Johns Creek Valley—a mountainous catchment for long-term interdisciplinary human-environment system research in upper Styria (Austria). Environ Earth Sci (accepted) 69(2):973–983
Strasser U, Mauser W (2001) Modelling the spatial and temporal variations of the water balance for the Weser catchment 1965-1994. J Hydrol 254(1-4):199–214
Sundquist H (1978) A parameterization scheme for non-convective condensation including precipitation including prediction of cloud water content. Q J R Meteorol Soc 104:677–690
Themessl M, Gobiet A, Leuprecht A (2011) Empirical-statistical downscaling and error correction of daily precipitation from regional climate models. Int J Climatol 31:1530–1544
Tiedtke M (1989) A comprehensive mass flux scheme for cumulus parameterization in large scale models. Mon Weather Rev 117:1779–1800
Uppala SM, Kallberg PW, Simmons AJ, Andrae U, da Costa Bechtold V, Fiorino M, Gibson JK, Haseler J, Hernandez A, Kelly GA, Li X, Onogi K, Saarinen S, Sokka N, Allan RP, Andersson E, Arpe K, Balmaseda MA, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Caires S, Chevallier F, Dethof A, Dragosavac M, Fisher M, Fuentes M, Hagemann S, Holm E, Hoskins BJ, Isaksen V, Janssen PAEM, Jenne R, McNally AP, Mahfouf JF, Morcrette JJ, Rayner NA, Saunders RW, Simon P, Sterl A, Trenberth KE, Untch A, Vasiljevic D, Viterbo P, Woollen J (2005) The ERA-40 reanalysis. Q J R Meteorol Soc 131:2961–3012
Van Loan CF (1997) Introduction to scientific computing. Prentice Hall, New York
Wilby RL, Hay LE, Gutowski WJ, 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
Wilby RL, Hay LE, Leavesley GH (1999) A comparison of downscaled and raw GCM output: implications for climate change scenarios in the San Juan River Basin. J Hydrol 225:67–91
Wilks DS (1995) Statistical methods in the atmospheric sciences: an introduction. Academic Press, New York
Wood AW, Leung LR, Sridhar V, Lettenmaier DP (2004) Hydrological implications of dynamical and statistical approaches to downscaling climate model outputs. Clim Change 62:189–216
Yarnal B, Lakhtakia MN, Yu Z, White RA, Pollard D, Miller DA, Lapenta WM (2000) A linked meteorological and hydrological model system: the Susquehanna River Basin Experiment (SRBEX). Global Planet Change 25:149–161
Zabel F, Mauser W, Marke T, Pfeiffer A, Zängl G, Wastl C (2012) Inter-comparison of two land-surface schemes applied on different scales and their feedbacks while coupled with a regional climate model. Hydrol Earth Syst Sci 16:1017–1031
Zängl G (2002) An improved method for computing horizontal diffusion in a sigma-coordinate model and its application to simulations over mountainous topography. Mon Weather Rev 130:1423–1432
Acknowledgments
The authors thank the German Ministry for Education and Research (BMBF), the Free State of Bavaria and the Ludwig-Maximilians-University Munich (LMU) for funding the GLOWA-Danube project. Thanks also go to the German and Austrian Weather Services for the provision of the station data used in this study as well as to all partners of the GLOWA-Danube project for the fruitful cooperations in the last years.
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Marke, T., Mauser, W., Pfeiffer, A. et al. Application of a hydrometeorological model chain to investigate the effect of global boundaries and downscaling on simulated river discharge. Environ Earth Sci 71, 4849–4868 (2014). https://doi.org/10.1007/s12665-013-2876-z
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DOI: https://doi.org/10.1007/s12665-013-2876-z