Characteristics of analysis increments from a convective-scale ensemble data assimilation system
The operational kilometre-scale ensemble data assimilation (KENDA) system of MeteoSwiss is based on the numerical weather prediction model COSMO and an LETKF. The model domain covers the entire Alpine region. Since the ensemble spread is too small in the forecast step of the analysis cycle in the boundary layer, stochastic perturbations of physical tendencies (SPPT) are used to account for model errors, which mitigates but does not solve the overconfidence. Piccolo et al. (2018) found that using analysis increments to represent model errors improves the spread and the reliability of ensemble forecasts. Analysis increments can take into account more possible sources of model errors than SPPT since they are not limited to the physical tendencies.
In order to gain a deeper knowledge of the analysis increments of KENDA, the increments of temperature, horizontal wind, and humidity are examined. The analysed time period covers an entire year. The statistical analysis includes seasonal mean and variance for each grid point of the model domain as well as diurnal variations of the analysis increments. The aim of the study is to estimate to what extend these analysis increments can be considered as a proxy for model errors to generate additional ensemble perturbations.
Dr. Claire Merker MeteoSwiss