Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11765/1382
Predictability of short-range forecasting: a multimodel approach
Title: Predictability of short-range forecasting: a multimodel approach
Authors: García-Moya, José AntonioAutor AEMETCallado, AlfonsAutor AEMETEscribá, PauAutor AEMETSantos Burguete, Carlos ORCID RESEARCHERID Autor AEMETSantos Muñoz, DanielSimarro, Juan Pablo ORCID SCOPUSID Autor AEMET
Keywords: Short-range forecasting; Numerical weather prediction; Ensemble Prediction System; Mesoscale model
Issue Date: 2011
Publisher: Taylor & Francis
Citation: Tellus A. 2011, 63(3), p. 550-563
Publisher version: https://dx.doi.org/10.1111/j.1600-0870.2010.00506.x
Abstract: 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
Appears in Collections:Artículos científicos 2010-2014


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