Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/20.500.11765/1382
Predictability of short-range forecasting: a multimodel approach
Título : Predictability of short-range forecasting: a multimodel approach
Autor : García-Moya, José AntonioAutor AEMETCallado Pallarés, AlfonsAutor AEMETEscribà, PauAutor AEMETSantos Burguete, Carlos ORCID RESEARCHERID Autor AEMETSantos Muñoz, DanielAutor AEMETSimarro Grande, Juan Pablo ORCID SCOPUSID Autor AEMET
Palabras clave : Short-range forecasting; Numerical weather prediction; Ensemble Prediction System; Mesoscale model
Fecha de publicación : 2011
Editor: Taylor & Francis
Citación : Tellus A. 2011, 63(3), p. 550-563
Versión del editor: https://dx.doi.org/10.1111/j.1600-0870.2010.00506.x
Resumen : Numerical weather prediction (NWP) models (including mesoscale) have limitations when it comes to dealing with severe weather events because extreme weather is highly unpredictable, even in the short range. A probabilistic forecast based on an ensemble of slightly differentmodel runs may help to address this issue. Among other ensemble techniques, Multimodel ensemble prediction systems (EPSs) are proving to be useful for adding probabilistic value to mesoscale deterministic models. A Multimodel Short Range Ensemble Prediction System (SREPS) focused on forecasting the weather up to 72 h has been developed at the panishMeteorological Service (AEMET). The system uses five different limited area models (LAMs), namely HIRLAM (HIRLAM Consortium), HRM (DWD), the UM (UKMO), MM5 (PSU/NCAR) and COSMO (COSMO Consortium). These models run with initial and boundary conditions provided by five different global deterministic models, namely IFS (ECMWF), UM (UKMO), GME (DWD), GFS (NCEP) and CMC (MSC). AEMET-SREPS (AE) validation on the large-scale flow, using ECMWF analysis, shows a consistent and slightly underdispersive system. For surface parameters, the system shows high skill forecasting binary events. 24-h precipitation probabilistic forecasts are verified using an up-scaling grid of observations from European high-resolution precipitation networks, and compared with ECMWF-EPS (EC).
URI : http://hdl.handle.net/20.500.11765/1382
ISSN : 0280-6495
1600-0870
Colecciones: Artículos científicos 2010-2014


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