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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

evaporation need an accurate assessment of the external drivers of the evaporation process. However, because of nonlinearity in the relationships between the drivers of evaporation (particularly temperature) it is not possible to make such an assessment using daily average meteorological data. Instead, accurate assessment requires data that resolve the full diurnal cycle. This paper describes the creation of the Water and Global Change (WATCH) Forcing Data (WFD), a dataset that is available for the whole

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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

) ( Henderson-Sellers et al. 1995 ), the Global Soil Wetness Project (GSWP) ( Oki et al. 1999 ; Dirmeyer et al. 2006 ; Dirmeyer 2011 ), and the Water Model Intercomparison Project (WaterMIP) ( Haddeland et al. 2011 ). In general, these studies conclude that there are large differences between the models, which may be caused by incomplete process understanding, different parameter estimates, and imperfect atmospheric forcing data. Several multimodel evaluation studies not only compare individual models to

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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

of model simulations including human influences and the impacts of climate change on global water resources. 2. Simulation setup and model descriptions In this first stage of WaterMIP, we assess the components of the contemporary global terrestrial water balance under naturalized conditions: that is, human impacts such as storage in man-made reservoirs and agricultural water withdrawal are not included in the model runs. The spatial resolution of the forcing data and the model simulations is 0

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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

more than any other changes (e.g., with regard to flood risks and changes in water availability and water quality). Consequently, the quantification of these implications is also a major objective of the EU project Water and Global Change (WATCH; ). Simulations of projected components of the hydrological cycle, under a range of GHG forcing scenarios ( Gutowski et al. 2007 ; Boberg et al. 2007 ), are essential tools for strategic freshwater resource management, particularly

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

( Falloon and Betts 2006 ). Comparison of annual and monthly TRIP river flow outputs with observed river flow-gauge data has shown good agreement both using an independent runoff dataset ( Oki 1997 ; Oki et al. 1999 ), and the land surface scheme used to produce runoff as input to TRIP in HadGEM1 has been shown to reproduce observed changes in continental-scale (but not basin scale) runoff during the twentieth century ( Gedney et al. 2006 ), driven by climate, CO 2 , aerosol, and land use forcings. In

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

products from 20% to 10% (meaning that more food and thereby water is consumed from cropland and less from grassland). For all future projections, the country-specific share of the water resource from grazing land was held constant at the present level. 3. Climate data and scenarios LPJmL was forced for the period 1901–2000 by monthly values of air temperature, precipitation amounts, number of wet days, and cloud cover, taken from the Climate Research Unit time series (CRU TS) 3.0 climate database

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