In the framework of the CORDEX FPS on Convective phenomena at high resolution over Europe and the Mediterranean (FPS-CEM, Coppola et al., 2018), a convection-permitting multi-model ensemble was used to simulate high-impact weather events over the Alps. This experiment resulted in noticeable discrepancies between models in representing selected heavy precipitation events. The groups using the Weather and Research Forecasting (WRF) model organized a multi-physics ensemble, suited to identify the processes behind those discrepancies. In this work we analyze the uncertainty arising from internal variability in this multi-physics ensemble at one-month and one-year timescales. To distinguish the uncertainty due to the use of different parameterizations from that of the internal variability, a set of simulations with perturbed initial conditions was performed. We measured quantitatively the uncertainty arising from both sources using inter-member variances. For circulation variables, the results suggest that uncertainties from multi-physics and internal variability have comparable magnitude, exhibiting an annual cycle with higher values in summer than in winter. The spatial distribution of the uncertainties show similar patterns, with higher values over the northeastern part of the domain. These patterns are in agreement with previous studies which conclude that internal variability increases where the inflow of the boundary information is less dominant: that is, in summer when the boundary forcing is not able to overcome the local-scale processes, and far from the westerly flow coming from the north Atlantic. The behaviour of uncertainty also depends on the variable. Surface variables are more affected by parameterized processes (soil physics, boundary layer, clouds, etc.), hence the uncertainty associated to the parameterizations has more decisive role for these variables than for circulation variables.
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