Weather forecasts obtained with a Multimodel SuperEnsemble technique in a complex orography region

Abstract

The Multimodel SuperEnsemble technique (KRISHNAMURTI et al., 2000a) is a new powerful post-processing method for the estimation of weather forecast parameters. Several model outputs are combined, using weights calculated during a training period. Piedmont region is characterised by complex mountainous orography and direct model outputs, even from high-resolution limited area models, show many strong systematic and random errors in the forecast, compared to the values observed by our high-density non-GTS network. This is one of the first applications of this technique in a narrow mountain area and combines both global and limited-area models. Our results show a good improvement of meteorological parameter forecasts such as temperature, humidity, wind speed and precipitation.