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. Knowledge of how uncertainty propagates through a hydrological land surface modelling sequence is of crucial importance in the identification and characterisation of system weaknesses in the prediction of droughts and floods at global scale. We evaluated the performance of five state-of-the-art global hydrological and land surface models in the contextof modelling extreme conditions (drought and flood). Uncertainty wasapportioned between the model used (model skill) and also the satellite-basedprecipitation products used to drive the simulations (forcing datavariability) for extreme values of precipitation, surface runoff andevaporation. We found in general that model simulations acted to augmentuncertainty rather than reduce it. In percentage terms, the increase inuncertainty was most often less than the magnitude of the input datauncertainty, but of comparable magnitude in many environments. Uncertaintyin predictions of evapotranspiration lows (drought) in dry environments wasespecially high, indicating that these circumstances are a weak point incurrent modelling system approaches. We also found that high data and modeluncertainty points for both ET lows and runoff lows were disproportionatelyconcentrated in the equatorial and southern tropics. Our results areimportant for highlighting the relative robustness of satellite products inthe context of land surface simulations of extreme events and identifyingareas where improvements may be made in the consistency of simulationmodels.

A global-scale evaluation of extreme event uncertainty in the &lt;i&gt;eartH2Observe&lt;/i&gt; project

A global-scale evaluation of extreme event uncertainty in the <i>eartH2Observe</i> project