A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset

Schellekens, Jaap; Dutra, Emanuel; Martinez-de la Torre, Alberto; Balsamo, Gianpaolo; van Dijk, Albert; Sperna Weiland, Frederiek; Minvielle, Marie; Calvet, Jean-Christophe; Decharme, Bertrand; Eisner, Stephanie; Fink, Gabriel; Flörke, Martina; Peßenteiner, Stefanie; van Beek, Rens; Polcher, Jan; Beck, Hylke; Orth, René; Calton, Ben; Burke, Sophia; Dorigo, Wouter; Weedon, Graham P.. 2017 A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset. Earth System Science Data, 9 (2). 389-413. https://doi.org/10.5194/essd-9-389-2017

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Official URL: https://doi.org/10.5194/essd-9-389-2017

Abstract/Summary

The dataset presented here consists of an ensemble of 10 global hydrological and land surface models for the period 1979–2012 using a reanalysis-based meteorological forcing dataset (0.5° resolution). The current dataset serves as a state of the art in current global hydrological modelling and as a benchmark for further improvements in the coming years. A signal-to-noise ratio analysis revealed low inter-model agreement over (i) snow-dominated regions and (ii) tropical rainforest and monsoon areas. The large uncertainty of precipitation in the tropics is not reflected in the ensemble runoff. Verification of the results against benchmark datasets for evapotranspiration, snow cover, snow water equivalent, soil moisture anomaly and total water storage anomaly using the tools from The International Land Model Benchmarking Project (ILAMB) showed overall useful model performance, while the ensemble mean generally outperformed the single model estimates. The results also show that there is currently no single best model for all variables and that model performance is spatially variable. In our unconstrained model runs the ensemble mean of total runoff into the ocean was 46 268 km3 yr−1 (334 kg m−2 yr−1), while the ensemble mean of total evaporation was 537 kg m−2 yr−1. All data are made available openly through a Water Cycle Integrator portal (WCI, wci.earth2observe.eu), and via a direct http and ftp download. The portal follows the protocols of the open geospatial consortium such as OPeNDAP, WCS and WMS. The DOI for the data is https://doi.org/10.1016/10.5281/zenodo.167070.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.5194/essd-9-389-2017
UKCEH and CEH Sections/Science Areas:	Reynard
ISSN:	1866-3508
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
NORA Subject Terms:	Hydrology Data and Information
Date made live:	20 Jul 2017 13:26 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/517350

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.5194/essd-9-389-2017

UKCEH and CEH Sections/Science Areas:

Reynard

ISSN:

1866-3508

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

NORA Subject Terms:

Hydrology
Data and Information