| Metadato | Etiqueta | Valor | Idioma |
|---|---|---|---|
| dc.contributor.author | Autor | Silini, Riccardo | - |
| dc.contributor.author | Autor | Lerch, Sebastian | - |
| dc.contributor.author | Autor | Mastrantonas, Nikolaos | - |
| dc.contributor.author | Autor | Kantz, Holger | - |
| dc.contributor.author | Autor | Barreiro, Marcelo | - |
| dc.contributor.author | Autor | Masoller, Cristina | - |
| dc.contributor.filiacion | Filiación | Silini Riccardo | - |
| dc.contributor.filiacion | Filiación | Lerch Sebastian | - |
| dc.contributor.filiacion | Filiación | Mastrantonas Nikolaos | - |
| dc.contributor.filiacion | Filiación | Kantz Holger | - |
| dc.contributor.filiacion | Filiación | Barreiro Marcelo, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Física. | - |
| dc.contributor.filiacion | Filiación | Masoller Cristina | - |
| dc.date.accessioned | Fecha ingreso | 2023-11-20T13:18:50Z | - |
| dc.date.available | Fecha disponible | 2023-11-20T13:18:50Z | - |
| dc.date.issued | Año de publicación | 2022 | - |
| dc.description.abstract | Resumen | The Madden–Julian Oscillation (MJO) is a major source of predictability on the sub-seasonal (10 to 90 d) timescale. An improved forecast of the MJO may have important socioeconomic impacts due to the influence of MJO on both tropical and extratropical weather extremes. Although in the last decades state-of-the-art climate models have proved their capability for forecasting the MJO exceeding the 5-week prediction skill, there is still room for improving the prediction. In this study we use multiple linear regression (MLR) and a machine learning (ML) algorithm as post-processing methods to improve the forecast of the model that currently holds the best MJO forecasting performance, the European Centre for Medium-Range Weather Forecasts (ECMWF) model. We find that both MLR and ML improve the MJO prediction and that ML outperforms MLR. The largest improvement is in the prediction of the MJO geographical location and intensity. | es |
| dc.format.extent | Extensión | 9 h. | es |
| dc.format.mimetype | Formato | application/pdf | es |
| dc.identifier.citation | Citación | Silini, R, Lerch, S, Mastrantonas, N, [y otros autores]. "Improving the prediction of the Madden–Julian Oscillation of the ECMWF model by post-processing". Earth System Dynamics. [en línea] 2022, 13: 1157–1165. 9 h. DOI: 10.5194/esd-13-1157-2022 | es |
| dc.identifier.doi | DOI | 10.5194/esd-13-1157-2022 | - |
| dc.identifier.issn | ISSN | 2190-4979 | - |
| dc.identifier.uri | URI | https://hdl.handle.net/20.500.12008/41312 | - |
| dc.language.iso | Idioma | en | es |
| dc.publisher | Editorial | European Geosciences Union | es |
| dc.relation.ispartof | EN | Earth System Dynamics, 2022, 13: 1157–1165 | es |
| dc.rights | Derechos | Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014) | es |
| dc.rights.licence | Licencia | Licencia Creative Commons Atribución (CC - By 4.0) | es |
| dc.subject | Palabras clave | Madden–Julian Oscillation | es |
| dc.subject | Palabras clave | Weather forecast | es |
| dc.subject | Palabras clave | Climate models | es |
| dc.title | Título | Improving the prediction of the Madden–Julian Oscillation of the ECMWF model by post-processing | es |
| dc.type | Tipo de documento | Artículo | es |
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| 10.5194esd-13-1157-2022.pdf | — | 2.58 MB | Adobe PDF |