The scale- and case- dependence of the predictability of precipitation by a storm scale ensemble forecasting system

This presentation discusses the scale- and case- dependence of the predictability of precipitation by the CAPS SSEF run during NOAA's Hazardous Weather Testbed (HWT) Spring Experiments of 2008-2013. The effect of different types of ensemble perturbation methodologies is quantified as a function of spatial scale. It is found that uncertainties in the large-scale initial and boundary conditions (IC/LBC) and in the model microphysical parameterization scheme can result in the loss of predictability at scales smaller than 200 km after 24 h. Also, these uncertainties account for most of the forecast error. Other types on ensemble perturbation methodologies, such as small-scale initial condition perturbations and physics only perturbations, were not found to be as important for the quantitative precipitation forecasts (QPF). The case-dependence of predictability and of the sensitivity to the ensemble perturbation methodology are also analyzed. Events characterized by large precipitation coverage and convective equilibrium are generally more predictable than weakly-forced events in terms of ensemble spread and QPF skill. However, the loss of predictability at small scales occurs just as rapidly for the two types of events. Also, in agreement with previous studies, accounting for the uncertainty in the model microphysical parameterization is more important for weakly-forced cases than for strongly-forced cases. Finally, properly accounting for small-scale errors in the ICs is desirable, especially for events in which convection is not in equilibrium with the large-scale forcing.