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Philippe Lucas-Picher, Jens H. Christensen, Fahad Saeed, Pankaj Kumar, Shakeel Asharaf, Bodo Ahrens, Andrew J. Wiltshire, Daniela Jacob, and Stefan Hagemann

, the north Bay of Bengal, and northeast India are poorly simulated by most GCMs ( Christensen et al. 2007 ; Kripalani et al. 2007 ). This is likely caused by the coarse resolutions of the GCMs, which are not able to correctly represent the regional forcings such as the steep topography of the Himalayas and the Western Ghats ( Rupa Kumar et al. 2006 ). The computer power currently available constrains GCMs to perform long global climate simulations on a regular grid at a horizontal resolution of

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Stefan Hagemann, Cui Chen, Jan O. Haerter, Jens Heinke, Dieter Gerten, and Claudio Piani

least for precipitation, an impact of the bias correction on the climate change signal may be reasonable. For temperature, the assumption of relating current-day model and observed variability differences to future scenario sensitivity to changes in GHG boundary conditions has yet to be verified. For precipitation, this is a similar problem but the situation becomes even more complicated because additional current-day model and observational variabilities affect the signal, and deriving the transfer

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Ingjerd Haddeland, Douglas B. Clark, Wietse Franssen, Fulco Ludwig, Frank Voß, Nigel W. Arnell, Nathalie Bertrand, Martin Best, Sonja Folwell, Dieter Gerten, Sandra Gomes, Simon N. Gosling, Stefan Hagemann, Naota Hanasaki, Richard Harding, Jens Heinke, Pavel Kabat, Sujan Koirala, Taikan Oki, Jan Polcher, Tobias Stacke, Pedro Viterbo, Graham P. Weedon, and Pat Yeh

1. Introduction The global water balance has been the subject of modeling studies for decades, both from a climate perspective where the main interest is the influence of the water balance on surface heat fluxes and from a hydrological perspective focusing on water availability and use. However, there are still many uncertainties in our understanding of the current water cycle, and to date the results of land surface models (LSMs) and global hydrology models (GHMs) have not been compared in a

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Lukas Gudmundsson, Lena M. Tallaksen, Kerstin Stahl, Douglas B. Clark, Egon Dumont, Stefan Hagemann, Nathalie Bertrand, Dieter Gerten, Jens Heinke, Naota Hanasaki, Frank Voss, and Sujan Koirala

hydrology models (GHMs), focusing on closing the water balance for the purpose of water resource assessment, and land surface models (LSMs) that were historically developed to provide lower boundary conditions for atmospheric circulation models with a focus on the surface water and energy balances. However, many models (both GHMs and LSMs) share essentially the same conceptualization of the water fluxes ( Haddeland et al. 2011 ). Thus, all models that resolve the terrestrial part of the water cycle at

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D. Gerten, J. Heinke, H. Hoff, H. Biemans, M. Fader, and K. Waha

Intercomparison Project (WaterMIP) simulation protocol ( Haddeland et al. 2011 ). See below for details on the modeling of GW and BW availability. Seasonal phenology (sowing and harvest dates) of CFTs was simulated based on CFT-specific parameters, past climate and current meteorological conditions, allowing for adaptation of varieties and growing periods to climate change ( Bondeau et al. 2007 ; Waha et al. 2011 ). To ensure sound estimates of CFT yields and water productivities, yields were calibrated for

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Pete Falloon, Richard Betts, Andrew Wiltshire, Rutger Dankers, Camilla Mathison, Doug McNeall, Paul Bates, and Mark Trigg

, although simulations using the previous version HadCM3 were also included in Solomon et al. (2007) . HadGEM1 and HadCM3 are described in detail by Johns et al. (2003 , 2006) and Martin et al. (2006) . HadGEM1 has many improvements over HadCM3, including improved horizontal latitude–longitude resolution (atmosphere: 1.25° × 1.875° versus 2.5° × 3.75°; ocean: 1.0° × 1.0° versus 1.25° × 1.25°) and substantially improved representations of physical processes including advection, boundary layer

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Kerstin Stahl, Lena M. Tallaksen, Lukas Gudmundsson, and Jens H. Christensen

control. In addition, all series were visually checked for detectable inhomogeneities or quality problems during low flows ( Stahl et al. 2010 ). For this study, only records covering the period from 1961 to 2004 without gaps of more than a few days were chosen. Basin boundary estimates were available from CCM2, the second version of the Catchment Characterisation and Modelling (CCM) River and Catchment database for Europe ( Vogt et al. 2007 ). While catchment area was provided by the national

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G. P. Weedon, S. Gomes, P. Viterbo, W. J. Shuttleworth, E. Blyth, H. Österle, J. C. Adam, N. Bellouin, O. Boucher, and M. Best

responsible for an observed drop in pan evaporation, although decreases–increases in radiation (global dimming–brightening) are perhaps responsible for changes elsewhere. Shuttleworth et al. (2009) demonstrated that it is not always possible to use pan evaporation to diagnose large-scale change in external drivers of actual evaporation. This is because some changes in the drivers of pan evaporation are caused by feedbacks in the atmospheric planetary boundary layer caused by altered actual evaporation

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Christel Prudhomme, Simon Parry, Jamie Hannaford, Douglas B. Clark, Stefan Hagemann, and Frank Voss

large-scale hydrological models, all driven by the same meteorological forcing data, with observed regional high and low flow catalogues over the period 1963–2000, in an attempt to assess the validity of their reproduction of regional runoff “extremes” in Europe. These global models are part of the Water Model Intercomparison Project (WaterMIP) ( Haddeland et al. 2011 ). The current study uses the European RDI and RFI historical catalogues as a benchmark to assess and compare how well large

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