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

Schellekens, Jaap; Dutra, Emanuel; la Torrej, Alberto Martinez-de; Balsamo, Gianpaolo; Van Dijk, Albert; Sperna Weiland, F.C.; Minvielle, Marie; Calvet, J C; Decharme, B; Eisner, Stephanie L; Fink, Gabriel; Flörke, Martina


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...[Show more]

CollectionsANU Research Publications
Date published: 2017
Type: Journal article
Source: Earth System Science Data
DOI: 10.5194/essd-9-389-2017
Access Rights: Open Access


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