Uncertainty assessment for climate change impact on intense precipitation: how many model runs do we need?

Precipitation projections are typically obtained from general circulation model (GCM) outputs under different future scenarios, then downscaled for hydrological applications to a watershed or site-specific scale. However, uncertainties in projections are known to be present and need to be quantified. Although GCMs are commonly considered the major contributor of uncertainty for hydrological impact assessment of climate change, other uncertainty sources must be taken into account for a thorough understanding of the hydrological impact. This study investigates uncertainties related to GCMs, GCM initial conditions and representative concentration pathways (RCPs) and their sensitivity to the selection of GCM runs in order to quantify the impact of climate change on extreme precipitation and intensity/duration/frequency statistics. The results from a large ensemble of 140 CMIP5 GCM runs including 15 GCMs, 3-10 GCM initial conditions and 4 RCPs are analysed. Albeit the choice of GCM is the major contributor (up to 65% for some cases) to intense precipitation change uncertainty for all return periods (1 year, 10 years) and aggregation levels (1-, 5-, 10-, 15-and 30-day), uncertainties related to the GCM initial conditions and RCPs of up to 38 and 23%, respectively, are found in some cases. The sensitivity analysis reveals that the GCM, RCP and GCM initial condition uncertainties are greatly influenced by the set of climate model runs considered, especially for more extreme precipitation at finer time scales.