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Original Research Papers

Predictability of short-range forecasting: a multimodel approach

Authors:

Jose-Antonio García-Moya,

AEMET, C/Leonardo Prieto Castro 8, Ciudad Universitaria, 28071 Madrid, ES
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Alfons Callado,

AEMET, Delegación Territorial en Cataluña, C/Arquitecto Sert 1, 08071 Barcelona, ES
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Pau Escribá,

AEMET, Delegación Territorial en Cataluña, C/Arquitecto Sert 1, 08071 Barcelona, ES
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Carlos Santos,

AEMET, C/Leonardo Prieto Castro 8, Ciudad Universitaria, 28071 Madrid, ES
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Daniel Santos-Muñoz,

AEMET, C/Leonardo Prieto Castro 8, Ciudad Universitaria, 28071 Madrid, ES
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Juan Simarro

AEMET, Delegación Territorial en la Comunidad Valenciana, C/Botánico Cavanilles 3, 46010 Valencia, ES
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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 SpanishMeteorological 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).

How to Cite: García-Moya, J.-A., Callado, A., Escribá, P., Santos, C., Santos-Muñoz, D. and Simarro, J., 2011. Predictability of short-range forecasting: a multimodel approach. Tellus A: Dynamic Meteorology and Oceanography, 63(3), pp.550–563. DOI: http://doi.org/10.1111/j.1600-0870.2010.00506.x
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  Published on 01 Jan 2011
 Accepted on 19 Nov 2010            Submitted on 11 Apr 2010

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