The impact of horizontal resolution and ensemble size for convective‐scale probabilistic forecasts

The relative benefits of ensemble size and model resolution are investigated within the AROME–France convective‐scale ensemble prediction system (EPS), which operationally runs 12 perturbed members at 2.5 km horizontal resolution. This baseline configuration is compared with two auxiliary ensemble experiments, which are run at resolutions of 2.5 and 1.3 km, with 34 and 12 members respectively. In addition, post‐processing techniques including neighbourhood approaches and time‐lagging are examined as potential alternatives to increase the sample size at a lower computational cost. Probabilistic verification of the raw EPS outputs indicates that increasing model resolution is more beneficial at very short ranges, whereas increasing the ensemble size has a larger impact at longer forecast ranges, as predictability decreases and more members are required to sample the larger uncertainty better. The neighbourhood processing confirms these conclusions and is shown to improve precipitation forecasts of all EPS configurations significantly, especially the smaller‐size ensembles. Hence, it can be considered as a viable substitute to running additional AROME members for the first 24 h of forecasts. Time‐lagging of three successive ensemble productions also appears to be a competitive approach to improve the ensemble forecast skill, particularly at very short ranges, where AROME‐EPS is known to be underdispersive. The performance of the time‐lagged 36 member ensemble is generally close to or even better than the performance of the single 34 member ensemble for the whole forecast range and for different surface weather variables. Overall, given the relative costs and skills of the different EPS configurations, we suggest that resources should primarily be spent on increasing ensemble size, by combining both additional members and post‐processing methods. In addition, the performance of the 1.3 km ensemble should be examined further for explicit high‐impact weather and with an appropriate tuning of physics and surface perturbations.