Generating spatial precipitation ensembles: impact of temporal correlation structures

Synthetic and real world experiments are carried out within the hilly region of the Belgian Ardennes. Precipitation fields are simulated for pixels of 10 × 10 km2 resolution. Uncertainty analyses in the simulated fields focus on (1) the number of previous simulation hours on which the new simulation is conditioned, (2) the advection speed of the rainfall event, (3) the size of the catchment considered, and (4) the rain gauge density within the catchment. The results for a synthetic experiment show for typical advection speeds of >20 km h-1, no uncertainty is added in terms of across ensemble spread when conditioned on more than one or two previous simulations. However, for the real world experiment, additional uncertainty can be still added when conditioning on a higher number of previous simulations. This is, because for actual precipitation fields, the dynamics exhibit a larger spatial and temporal variability. Moreover, by thinning the observation network with 50%, the added uncertainty increases only slightly. Finally, the first order autocorrelation coefficients show clear temporal coherence in the time series of the areal precipitation using the time-dependent multivariate conditional simulations, which was not the case using the time-independent univariate conditional simulations