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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

1. Introduction As the earth’s whole climate system slowly changes there are likely to be greater and faster regional changes. Studies of the impacts of these changes on essential services such as fresh water supply are being made by many researchers (e.g., Harding et al. 2011 ) with the change in evaporation being a key aspect. Observations of large-scale evaporation over the last half century (the most studied period) are, however, not available. Consequently, models of evaporation are

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Manuel Punzet, Frank Voß, Anja Voß, Ellen Kynast, and Ilona Bärlund

assessment of the potential impacts of global change on the state of surface water resources is required. Impacts of climate change on freshwater biota can already be observed today. Effects on community structure, food web dynamics, and life cycle of different freshwater organisms have been found ( Schindler 1997 ; Poff et al. 2002 ; Wrona et al. 2006 ). Durance and Ormerod (2007) published a decline in macroinvertebrate abundance at a small catchment in Wales with increasing stream temperatures

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Richard Harding, Martin Best, Eleanor Blyth, Stefan Hagemann, Pavel Kabat, Lena M. Tallaksen, Tanya Warnaars, David Wiberg, Graham P. Weedon, Henny van Lanen, Fulco Ludwig, and Ingjerd Haddeland

). There is already evidence that rainfall, runoff, and evaporation have increased, and will continue to do so ( Wentz et al. 2007 ; Huntington 2006 ). However, rising CO 2 concentrations may also reduce evaporation because of stomatal closing under elevated CO 2 concentrations. Superimposed on the effects of climate change will be the other impacts of human activities, such as land cover change and exploitation of water resources. In the short term at least, these latter influences will have an

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Aristeidis G. Koutroulis, Aggeliki-Eleni K. Vrohidou, and Ioannis K. Tsanis

because of the regional atmospheric patterns that dominantly derive from the northwest and head toward the southeast. Another important factor is the morphological variability that presents higher elevation and steepest slopes in the west part of the island ( Fig. 5 ), where orographic effects tend to increase both frequency and intensity of precipitation ( Naoum and Tsanis 2004 ; Koutroulis and Tsanis 2010 ). The uneven spatial and temporal precipitation distributions of Crete, although common in

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

meteorological events and catchment properties that are not necessarily representative of the whole region) are smoothed out, while large-scale generating mechanisms are captured—furthermore, the spatial scale of the regional time series is consistent with that of the global models; and (iii) RDI and RFI are derived from time series anomalies: when applied to global models, the anomalies are based on the internal variability of each model-simulated flow, hence eliminating the effects of systematic biases in

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Wai Kwok Wong, Stein Beldring, Torill Engen-Skaugen, Ingjerd Haddeland, and Hege Hisdal

RegCM output is a topic for further research. The control period used here (1961–90) is the latest normal period and is commonly used in regional climate modeling studies [e.g., Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects (PRUDENCE); Christensen and Christensen 2007 ]. However, if another control period had been used in this study, it might give slightly different results, and hence represents another source of uncertainty. The

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

decrease in both scenarios—for instance, in southern Europe, the Near East (by >40% in some countries), northern and southern Africa, and Central America and Mexico, mostly in response to higher temperatures and regional precipitation decreases [data not shown, but see Bates et al. (2008) ]. GW availability is simulated to decrease in most countries but Canada and central and northern Asia. Fig . 4. Percent changes (medians across all climate scenarios, including CO 2 effects) in blue, green, and

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

the representation of extremes from future climate scenarios effectively is filtered out in the transfer process (e.g., Graham et al. 2007 ), which is not desirable in studies of future changes in extreme events. Themeßl et al. (2011) compared several empirical–statistical downscaling and error correction methods applied to daily precipitation simulated by regional climate models over the Alps. These methods include indirect methods such as multiple linear regression (e.g., von Storch 1999

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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

://ftp.dwd.de/pub/data/gpcc/PDF/GPCC_intro_products_2008.pdf .] Shorthouse, C. , and Arnell N. , 1997 : Spatial and temporal variability in European river flows and the North Atlantic oscillation. FRIEND’97—Regional Hydrology: Concepts and Models for Sustainable Water Resource Management, A. Gustard et al., Eds., IAHS, 77–85 . Shorthouse, C. , and Arnell N. , 1999 : The effects of climatic variability on spatial characteristics of European river flows . Phys. Chem. Earth , 24B ( 1–2 ), 7 – 13 , doi:10.1016/S1464

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