Blocking prediction in an ensemble forecasting system

The predictability of the atmospheric blocking phenomenon is investigated using the output of the high-resolution ensemble prediction system of the European Centre for Medium-Range Weather Forecasts.
The output from the model is analysed using an objective blocking index. This is compared with the theory of Charney and DeVore that blocking is a large-scale non-linear phenomenon. A consequence of the non-linearity is that in some cases multiple quasi-stationary atmospheric states can exist for the same set of boundary conditions.
It is found that the model in general produces too few blocks. Good agreement is found between the models lacking ability to predict blocking frequency and the systematic errors of 500-hPa geopotential height. It is found that there exists a limit, in the middle of the medium range, beyond which forecasts of blocking onset should be considered as probabilistic rather than dynamical. Inspection of individual blocking events adds new support to the idea that atmospheric blocking can be explained using the Charney–DeVore model.     

Flow-dependent versus flow-independent initial perturbations for ensemble prediction

Ensemble prediction relies on a faithful representation of initial uncertainties in a forecasting system. Early research on initial perturbation methods tested random perturbations by adding 'white noise' to the analysis. Here, an alternative kind of random perturbations is introduced by using the difference between two randomly chosen atmospheric states (i.e. analyses). It yields perturbations (random field, RF, perturbations) in approximate flow balance.
The RF method is compared with the operational singular vector based ensemble at European Centre for Medium Range Weather Forecasts (ECMWF) and the ensemble transform (ET) method. All three methods have been implemented on the ECMWF IFS-model with resolution T _L 255L40. The properties of the different perturbation methods have been investigated both by comparing the dynamical properties and the quality of the ensembles in terms of different skill scores. The results show that the RF perturbations initially have the same dynamical properties as the natural variability of the atmosphere. After a day of integration, the perturbations from all three methods converge. The skill scores indicate a statistically significant advantage for the RF method for the first 2–3 d for the most of the evaluated parameters. For the medium range (3–8 d), the differences are very small.