A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset
J Schellekens, E Dutra… - Earth System …, 2017 - essd.copernicus.org
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 …
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 …
[引用][C] A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset, Earth Syst. Sci. Data, 9, 389–413
J Schellekens, E Dutra, A Martínez-De La Torre… - 2017
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