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A blending method for generating initial condition (IC) perturbations in a regional ensemble prediction system is proposed. The blending is to combine the large-scale IC perturbations from a global ensemble prediction system (EPS) with the small-scale IC perturbations from a regional EPS by using a digital filter and the spectral analysis technique. The IC perturbations generated by blending can well represent both largescale and small-scale uncertainties in the analysis, and are more consistent with the lateral boundary condition (LBC) perturbations provided by global EPS. The blending method is implemented in the regional ensemble system Aire Limit ee Adaptation Dynamique D eveloppement International-Limited Area Ensemble Forecasting (ALADIN-LAEF), in which the large-scale IC perturbations are provided by the European Centre for Medium-Range Weather Forecasts (ECMWF-EPS), and the small-scale IC perturbations are generated by breeding in ALADIN-LAEF. Blending is compared with dynamical downscaling and breeding over a 2-month period in summer 2007. The comparison clearly shows impact on the growth of forecast spread if the regional IC perturbations are not consistent with the perturbations coming through LBC provided by the global EPS. Blending can cure the problem largely, and it performs better than dynamical downscaling and breeding.

The lack or inadequate representation of uncertainties in the surface initial conditions (ICs) affects the quality of ensemble forecast, in particular the near surface temperature and precipitation. In this paper, a strategy for perturbing surface ICs in limited area model ensemble prediction system, noncycling surface breeding (NCSB) is proposed. The strategy combines short-range surface forecasts driven by perturbed atmospheric forcing and the breeding method for generating the perturbation to surface ICs. NCSB is implemented and tested in Aire Limitée Adaptation dynamique Développement InterNational-limited area ensemble forecasting (ALADIN-LAEF). Statistical verification demonstrates that the application of NCSB improves the ALADIN-LAEF 2m temperature and precipitation forecast. Positive impacts are also obtained for temperature and specific humidity in the lower atmosphere.

Two techniques for perturbing surface initial conditions in the regional ensemble system Aire Limitée Adaptation Dynamique Développement International-Limited Area Ensemble Forecasting (ALADIN-LAEF) are presented and investigated in this paper. The first technique is the noncycling surface breeding (NCSB), which combines short-range surface forecasts driven by perturbed atmospheric forcing and the breeding method for generating the perturbations on surface initial conditions. The second technique, which is currently used in the ALADIN-LAEF operational version, applies an ensemble of surface data assimilations (ESDA) in which the observations are randomly perturbed. Both techniques are evaluated over a two-month period from late spring to summer. The results show that the evaluation is more favorable to ESDA. In general, the ensemble forecasts of the observed near-surface meteorological variables (screen-level variables) of ESDA are more skillful than NCSB, in particular for 2-m temperature they are statistically more consistent and reliable. A slightly better statistical reliability for 2-m relative humidity and 10-m wind has been found as well. This could be attributed to the introduction of surface data assimilation in ESDA, which provides more accurate surface initial conditions. Moreover, the observation perturbation in ESDA helps to better estimate the initial condition uncertainties. For the forecast of precipitation and the upper-air variables in the lower troposphere, both ESDA and NCSB perform very similarly, having neutral impact.

This paper describes 27 years of scientific and operational achievement of Regional Cooperation for Limited Area Modelling in Central Europe (RC LACE), which is supported by the national (hydro-) meteorological services of Austria, Croatia, the Czech Republic, Hungary, Romania, Slovakia, and Slovenia. The principal objectives of RC LACE are to 1) develop and operate the state-of-the-art limited-area model and data assimilation system in the member states and 2) conduct joint scientific and technical research to improve the quality of the forecasts. In the last 27 years, RC LACE has contributed to the limited-area Aire Limitée Adaptation Dynamique Développement International (ALADIN) system in the areas of preprocessing of observations, data assimilation, model dynamics, physical parameterizations, mesoscale and convection-permitting ensemble forecasting, and verification. It has developed strong collaborations with numerical weather prediction (NWP) consortia ALADIN, the High Resolution Limited Area Model (HIRLAM) group, and the European Centre for Medium-Range Weather Forecasts (ECMWF). RC LACE member states exchange their national observations in real time and operate a common system that provides member states with the preprocessed observations for data assimilation and verification. RC LACE runs operationally a common mesoscale ensemble system, ALADIN–Limited Area Ensemble Forecasting (ALADIN-LAEF), over all of Europe for early warning of severe weather. RC LACE has established an extensive regional scientific and technical collaboration in the field of operational NWP for weather research, forecasting, and applications. Its 27 years of experience have demonstrated the value of regional cooperation among small- and medium-sized countries for success in the development of a modern forecasting system, knowledge transfer, and capacity building.