Ana Morata

Weather pattern classification and relationships with observational wind speed over Iberia

The present study is focused on the analysis of the relationships between weather patterns and wind speeds over Iberia. A weather pattern classification is made by applying a multivariate methodology based on principal components to the Atlantic geopotential height field. From such classification, a set of composite plots are illustrated, showing how the different obtained atmospheric patterns have influence over the wind speed behaviour and the wind speed values. Moreover, the relationships between the obtained principal components and the observational local wind speeds are also provided in terms of the wind speed cumulated probability values and the associated curve area values related to the highest and lowest scores of the components time series.

A short-range ensemble precipitation prediction system over the Iberian Peninsula and Balearics

A short-range ensemble precipitation forecast system has been constructed over the Iberian Peninsula and Balearics by means of the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Model (MM5). The ensemble system consists of ten members, each run with a different combination of two different initial conditions from global models, IFS-ECMWF and GFS-NCEP, and five different subgrid-scale physics configurations for one month period, October 2006. The mesoscale verification is made by using observational precipitation data of the Spanish Climatic Network. The created short-range ensemble shows high spread-skill correlation values for daily precipitation. However, the asymmetric shape of the rank histogram indicates some underdispersion, suggesting a biased behaviour. The Talagrand shows as well the underdispersive effect because of its asymmetric distribution. The Relative Operating Characteristic curve shows a very outstanding area indicating the good discrimination capacity. The reliability diagrams are also indicative of the good reliability of the forecasting system, depicting in general good agreement between forecast probability and the mean observed frequency. Because of that, the verification proves the usefulness of the forecasting system over the study area.