Access the full text.
Sign up today, get DeepDyve free for 14 days.
M. Bosilovich, Junye Chen, F. Robertson, R. Adler (2008)
Evaluation of Global Precipitation in ReanalysesJournal of Applied Meteorology and Climatology, 47
P. Seguí, P. Moigne, Y. Durand, E. Martin, Florence, Habets, Martine Baillon, Claire Canellas, L. Franchistéguy, S. Morel (2008)
Analysis of Near-Surface Atmospheric Variables: Validation of the SAFRAN Analysis over FranceJournal of Applied Meteorology and Climatology, 47
2014: hydroGOF: Goodness-of-fit functions for comparison of simulated and observed hydrological time series. R package
J. Vidal, E. Martin, L. Franchistéguy, Martine Baillon, J. Soubeyroux (2010)
A 50‐year high‐resolution atmospheric reanalysis over France with the Safran systemInternational Journal of Climatology, 30
F. Isotta, R. Vogel, C. Frei (2015)
Evaluation of European regional reanalyses and downscalings for precipitation in the Alpine regionMeteorologische Zeitschrift, 24
H. Gupta, H. Kling, K. Yilmaz, G. Martinez (2009)
Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modellingJournal of Hydrology, 377
Lars Häggmark, Karl-Ivar Ivarsson, S. Gollvik, Per Olofsson (2000)
Mesan, an operational mesoscale analysis systemTellus A: Dynamic Meteorology and Oceanography, 52
S. Schiavon, R. Zecchin (2007)
Climate change 2007 : the physical science basis : contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change
M. Coustau, Fabienne Rousset-Regimbeau, G. Thirel, F. Habets, B. Janet, E. Martin, C. Saint-Aubin, J. Soubeyroux (2015)
Impact of improved meteorological forcing, profile of soil hydraulic conductivity and data assimilation on an operational Hydrological Ensemble Forecast System over FranceJournal of Hydrology, 525
P. Poli, H. Hersbach, D. Dee, P. Berrisford, A. Simmons, F. Vitart, P. Laloyaux, D. Tan, C. Peubey, J. Thepaut, Y. Trémolet, E. Holm, M. Bonavita, L. Isaksen, M. Fisher (2016)
ERA-20C: An Atmospheric Reanalysis of the Twentieth CenturyJournal of Climate, 29
R. Vautard, Thomas Noël, Laurent Li, M. Vrac, E. Martin, P. Dandin, J. Cattiaux, S. Joussaume (2013)
Climate variability and trends in downscaled high-resolution simulations and projections over Metropolitan FranceClimate Dynamics, 41
T. Landelius, P. Dahlgren, S. Gollvik, A. Jansson, Esbjörn Olsson (2016)
A high‐resolution regional reanalysis for Europe. Part 2: 2D analysis of surface temperature, precipitation and windQuarterly Journal of the Royal Meteorological Society, 142
C. Soci, E. Bazile, F. Besson, T. Landelius (2016)
High-resolution precipitation re-analysis system for climatological purposesTellus A: Dynamic Meteorology and Oceanography, 68
Qinglong You, J. Min, Wei Zhang, N. Pepin, Shi-chang Kang (2015)
Comparison of multiple datasets with gridded precipitation observations over the Tibetan PlateauClimate Dynamics, 45
V. Klemeš (1986)
Operational testing of hydrological simulation modelsHydrological Sciences Journal-journal Des Sciences Hydrologiques, 31
(2014)
Comparison of the regional reanalyses products with newly developed and existing state-of-the art systems
C. Piani, G. Weedon, M. Best, S. Gomes, P. Viterbo, S. Hagemann, J. Haerter (2010)
Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological modelsJournal of Hydrology, 395
Matthew Garcia, C. Peters-Lidard, D. Goodrich (2008)
Spatial interpolation of precipitation in a dense gauge network for monsoon storm events in the southwestern United StatesWater Resources Research, 44
C. Perrin, C. Michel, V. Andréassian (2003)
Improvement of a parsimonious model for streamflow simulationJournal of Hydrology, 279
(2010)
The WATCH forcing data 1958–2001: A meteorological forcing dataset for land surface and hydrological models
A. Lorenc (1981)
A Global Three-Dimensional Multivariate Statistical Interpolation SchemeMonthly Weather Review, 109
S. Bastola, V. Misra (2014)
Evaluation of dynamically downscaled reanalysis precipitation data for hydrological applicationHydrological Processes, 28
(2007)
Climate models and their evaluation.Climate
(2014)
hydroGOF: Goodness-of-fit functions for comparison of simulated and observed hydrological time series
D. Dee, S. Uppala, A. Simmons, P. Berrisford, P. Poli, S. Kobayashi, U. Andrae, M. Balmaseda, G. Balsamo, P. Bauer, P. Bechtold, A. Beljaars, L. Berg, J. Bidlot, N. Bormann, C. Delsol, R. Dragani, M. Fuentes, A. Geer, L. Haimberger, S. Healy, H. Hersbach, E. Holm, L. Isaksen, P. Kållberg, M. Köhler, M. Matricardi, A. Mcnally, B. Monge-Sanz, J. Morcrette, B. Park, C. Peubey, P. Rosnay, Christina Tavolato, J. Thepaut, F. Vitart (2011)
The ERA‐Interim reanalysis: configuration and performance of the data assimilation systemQuarterly Journal of the Royal Meteorological Society, 137
P. Loikith, D. Waliser, Jinwon Kim, R. Ferraro (2018)
Evaluation of cool season precipitation event characteristics over the Northeast US in a suite of downscaled climate model hindcastsClimate Dynamics, 50
G. Weedon, S. Gomes, P. Viterbo, W. Shuttleworth, E. Blyth, H. Osterle, J. Adam, N. Bellouin, O. Boucher, M. Best (2011)
Creation of the WATCH Forcing Data and Its Use to Assess Global and Regional Reference Crop Evaporation over Land during the Twentieth CenturyJournal of Hydrometeorology, 12
A. Prein, A. Gobiet (2016)
Impacts of uncertainties in European gridded precipitation observations on regional climate analysisInternational Journal of Climatology, 37
G. Dayon, J. Boé, E. Martin (2015)
Transferability in the future climate of a statistical downscaling method for precipitation in FranceJournal of Geophysical Research: Atmospheres, 120
L. Oudin, C. Perrin, T. Mathevet, V. Andréassian, C. Michel (2006)
Impact of biased and randomly corrupted inputs on the efficiency and the parameters of watershed modelsJournal of Hydrology, 320
M. Bourqui, T. Mathevet, J. Gailhard, F. Hendrickx (2011)
Hydrological validation of statistical downscaling methods applied to climate model projectionsIAHS-AISH publication
Gilles Essou, R. Arsenault, F. Brissette (2016)
Comparison of climate datasets for lumped hydrological modeling over the continental United StatesJournal of Hydrology, 537
G. Weedon, G. Balsamo, N. Bellouin, S. Gomes, M. Best, P. Viterbo (2014)
The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA‐Interim reanalysis dataWater Resources Research, 50
E. Martin, S. Gascoin, Youen Grusson, C. Murgue, Mélanie Bardeau, F. Anctil, S. Ferrant, R. Lardy, P. Moigne, D. Leenhardt, V. Rivalland, José Pérez, S. Sauvage, O. Thérond (2016)
On the Use of Hydrological Models and Satellite Data to Study the Water Budget of River Basins Affected by Human Activities: Examples from the Garonne Basin of FranceSurveys in Geophysics, 37
Gilles Essou, Florent Sabarly, P. Lucas‐Picher, F. Brissette, Annie Poulin (2016)
Can Precipitation and Temperature from Meteorological Reanalyses Be Used for Hydrological ModelingJournal of Hydrometeorology, 17
A. Valéry, V. Andréassian, C. Perrin (2014)
‘As simple as possible but not simpler’: What is useful in a temperature-based snow-accounting routine? Part 1 – Comparison of six snow accounting routines on 380 catchmentsJournal of Hydrology, 517
Y. Durand, E. Brun, L. Mérindol, G. Guyomarc'h, B. Lesaffre, Eric Martin (1993)
A meteorological estimation of relevant parameters for snow modelsAnnals of Glaciology, 18
F. Weiland, J. Vrugt, R. Beek, A. Weerts, M. Bierkens (2015)
Significant uncertainty in global scale hydrological modeling from precipitation data errorsJournal of Hydrology, 529
R. Jones, I. Renfrew, A. Orr, B. Webber, D. Holland, M. Lazzara (2016)
Evaluation of four global reanalysis products using in situ observations in the Amundsen Sea Embayment, AntarcticaJournal of Geophysical Research: Atmospheres, 121
M. Haylock, N. Hofstra, A. Tank, E. Klok, P. Jones, M. New (2008)
A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006Journal of Geophysical Research, 113
F. Habets, A. Boone, J. Champeaux, P. Etchevers, L. Franchistéguy, É. Leblois, E. Ledoux, P. Moigne, E. Martin, S. Morel, J. Noilhan, P. Seguí, Fabienne Rousset-Regimbeau, P. Viennot (2008)
The SAFRAN‐ISBA‐MODCOU hydrometeorological model applied over FranceJournal of Geophysical Research, 113
L. Oudin, F. Hervieu, C. Michel, C. Perrin, V. Andréassian, F. Anctil, C. Loumagne (2005)
Which potential evapotranspiration input for a lumped rainfall-runoff model?. Part 2: Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modellingJournal of Hydrology, 303
D. Dawdy, James Bergmann (1969)
Effect of rainfall variability on streamflow simulationWater Resources Research, 5
Edijatno, N. Nascimento, Xiaoliu Yang, Z. Makhlouf, C. Michel (1999)
GR3J: a daily watershed model with three free parametersHydrological Sciences Journal-journal Des Sciences Hydrologiques, 44
AbstractThe number and refinement of gridded meteorological datasets are on the rise at the global and regional scales. Although these datasets are now commonly used for hydrological modeling, the representation of precipitation amount and timing is crucial to correctly model streamflow. The GR4J conceptual hydrological model combined with the CEMANEIGE snow routine was calibrated using four temperature and precipitation datasets (SAFRAN, MESAN, E-OBS, WFDEI) on 931 French gauged catchments ranging in size from 10 to 10,000 km2. The efficiency of the calibrated hydrological model in simulating streamflow was higher for the models calibrated on high-resolution meteorological datasets (SAFRAN, MESAN) compared to coarseresolution datasets (E-OBS, WFDEI), as well as for reanalysis (SAFRAN, MESAN, WFDEI) compared to datasets based on interpolation only (E-OBS). The systematic decrease in efficiency associated with precipitation bias or temporality highlights that the use of a hydrological model calibrated on meteorological datasets can assess these datasets, most particularly precipitation. It appears essential that datasets account for high-resolution topography to accurately represent elevation gradient and assimilate dense ground-based observation networks. This is particularly emphasized for hydrological applications in mountainous areas and areas subject to fine-scale events. For hydrological applications on non-mountainous regions, not subject to fine-scale events, both regional and global datasets give satisfactory results. It is crucial to continue improving precipitation datasets, especially in mountainous areas, and to assess their sensitivity to eventual corrupted observations. These datasets are essential to correct the bias of climate model outputs and to investigate the impact of climate change on hydrological regimes.
Journal of Hydrometeorology – American Meteorological Society
Published: Sep 22, 2017
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.