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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

use of satellite data. At the global scale the precipitation datasets do differ in their totals, although their interannual variability and trends are largely similar. The mean annual land precipitation estimates vary from 96 286 to 118 006 km 3 yr −1 (743–926 mm yr −1 ) for the years 1979–99 ( Biemans et al. 2009 ). The overall trend is an increase in the early part of twentieth century, a decrease between 1950 and 1990, and an increase since then. Regionally, there have been decreases in the

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

application of the SPI covers a significant part of many studies that have been carried out over the last decades ( Bonaccorso et al. 2003 ; Loukas and Vasiliades 2004 ; Wu et al. 2007 ). Bacanli et al. (2009) assumed that when the analysis period (time scale) increases, drought is observed less but lasts longer. According to their study, the SPI showed short-term conditions with seasonal variation for 3- and 6-month periods, while 9- and 12-month periods used showed drought with average duration

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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

the period 1958–2001. For the period 1901–57 the WFD can therefore be used to characterize early twentieth-century subdaily to seasonal hydrological statistics, but they do not represent particular historical events. There is a lack of interannual–decadal variability in PET rc for 1901–57 despite the trends in 2-m temperature introduced by bias correction as a result of 1) the randomization of the ERA-40 data used in construction and 2) lack of bias correction of wind speed, surface pressure

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

, only annual values or long-term averages can be compared unless naturalized series are employed. In the case of soil moisture anomalies, the high spatial variability of soil properties restricts conclusions on model errors. Notable differences between modeled and observed streamflow dynamics, on the other hand, may be difficult to attribute to separate hydrological processes in the model—for example, either runoff generation or channel routing ( Balsamo et al. 2009 ). Hence, additional high

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

than only one aspect (e.g., mean or variability) of a specific variable in order to capture future changes in the whole distribution. For example, most studies of hydrological change in the past have used the delta change approach ( Hay et al. 2000 ), where the projected changes derived from climate modeling studies are added to observational data before these data are used to force hydrology models. However, this approach considers only the changes in the mean but not in the variability so that

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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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