Results
Title

On the Impact of the Choice of Global Ensemble in Forcing a Regional Ensemble System.

Authors

Weidle, Florian; Wang, Yong; Smet, Geert

Abstract

It is quite common that in a regional ensemble system the large-scale initial condition (IC) perturbations and the lateral boundary condition (LBC) perturbations are taken from a global ensemble prediction system (EPS). The choice of global EPS as a driving model can have a significant impact on the performance of the regional EPS. This study investigates the impact of large-scale IC/LBC perturbations obtained from different global EPSs on the forecast quality of a regional EPS. For this purpose several experiments are conducted where the Aire Limitée Adaption dynamique Développement International-Limited Area Ensemble Forecasting (ALADIN-LAEF) regional ensemble is forced by two of the world's leading global ensembles, the European Centre for Medium-Range Weather Forecasts' Ensemble Prediction System (ECMWF-EPS) and the Global Ensemble Forecasting System (GEFS) from the National Centers for Environmental Prediction (NCEP), which provide the IC and LBC perturbations. The investigation is carried out for a 51-day period during summer 2010 over central Europe. The results indicate that forcing of the regional ensemble with GEFS performs better for surface parameters, whereas at upper levels forcing with ECMWF-EPS is superior. Using perturbations from GEFS lead to a considerably higher spread in ALADIN-LAEF, which is beneficial near the surface where regional EPSs are usually underdispersive. At upper levels, forcing with GEFS leads to an overdispersion of ALADIN-LAEF as a result of the large spread of some parameters, where forcing ALADIN-LAEF with ECMWF-EPS provides statistically more reliable forecasts. The results indicate that the best global EPS might not always provide the best ICs and LBCs for a regional ensemble.

Subjects

WEATHER forecasting; BOUNDARY value problems; NATIONAL Centers for Environmental Prediction (U.S.); ATMOSPHERIC models; DISTRIBUTION (Probability theory)

Publication

Weather & Forecasting, 2016, Vol 31, Issue 2, p515

ISSN

0882-8156

Publication type

Academic Journal

DOI

10.1175/WAF-D-15-0102.1