The Niño3.4 region predictability beyond the persistence barrier
The predictability of the Niño3.4 region, especially the skill loss for lead times longer than two seasons, is the target of this study. We use an equatorial version of a seasonal statistical model to identify a seasonal predictability barrier, the skill loss of the predictions which target the summ...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Stockholm University Press
2015-09-01
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| Series: | Tellus: Series A, Dynamic Meteorology and Oceanography |
| Subjects: | |
| Online Access: | http://www.tellusa.net/index.php/tellusa/article/view/27457/pdf_54 |
| _version_ | 1818572378287898624 |
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| author | Miguel Tasambay-Salazar María José Ortizbeviá Francisco J. Alvarez-GarcÍa Antonio M. Ruiz De Elvira |
| author_facet | Miguel Tasambay-Salazar María José Ortizbeviá Francisco J. Alvarez-GarcÍa Antonio M. Ruiz De Elvira |
| author_sort | Miguel Tasambay-Salazar |
| collection | DOAJ |
| description | The predictability of the Niño3.4 region, especially the skill loss for lead times longer than two seasons, is the target of this study. We use an equatorial version of a seasonal statistical model to identify a seasonal predictability barrier, the skill loss of the predictions which target the summer or autumn Niño3.4 Index value, relative to those which target the winter or spring values. The variables of the basic model include an index for the subsurface anomalous state and another for the atmospheric variability. We develop different versions of the model, substituting some of its variables with others that contain tropical or extratropical information, produce a number of hindcasts with these models using two different prediction schemes, and crossvalidate them. The analysis shows that in winter and spring some skill improvements can be gained with the introduction of a particular variable or the other. However, these improvements are similar to the ones obtained using a forecast scheme that incorporates the complete solution of the stochastic model. Moreover, useful summer and autumn hindcast skill values are scored only with the model versions that include a representation of the extratropical feedbacks among its variables. Higher scores correspond to models that incorporate an index built from atmospheric temperature anomalies integrated from the surface up to the mid-troposphere, south of 20°S. |
| first_indexed | 2024-12-14T18:56:17Z |
| format | Article |
| id | doaj.art-206cac199a31471b84b98a3b618897c2 |
| institution | Directory Open Access Journal |
| issn | 1600-0870 |
| language | English |
| last_indexed | 2024-12-14T18:56:17Z |
| publishDate | 2015-09-01 |
| publisher | Stockholm University Press |
| record_format | Article |
| series | Tellus: Series A, Dynamic Meteorology and Oceanography |
| spelling | doaj.art-206cac199a31471b84b98a3b618897c22022-12-21T22:51:04ZengStockholm University PressTellus: Series A, Dynamic Meteorology and Oceanography1600-08702015-09-0167011710.3402/tellusa.v67.2745727457The Niño3.4 region predictability beyond the persistence barrierMiguel Tasambay-Salazar0María José Ortizbeviá1Francisco J. Alvarez-GarcÍa2Antonio M. Ruiz De Elvira3Departamento de Física y Matemática, Universidad de Alcalá, Madrid, SpainDepartamento de Física y Matemática, Universidad de Alcalá, Madrid, SpainDepartamento de Física y Matemática, Universidad de Alcalá, Madrid, SpainDepartamento de Física y Matemática, Universidad de Alcalá, Madrid, SpainThe predictability of the Niño3.4 region, especially the skill loss for lead times longer than two seasons, is the target of this study. We use an equatorial version of a seasonal statistical model to identify a seasonal predictability barrier, the skill loss of the predictions which target the summer or autumn Niño3.4 Index value, relative to those which target the winter or spring values. The variables of the basic model include an index for the subsurface anomalous state and another for the atmospheric variability. We develop different versions of the model, substituting some of its variables with others that contain tropical or extratropical information, produce a number of hindcasts with these models using two different prediction schemes, and crossvalidate them. The analysis shows that in winter and spring some skill improvements can be gained with the introduction of a particular variable or the other. However, these improvements are similar to the ones obtained using a forecast scheme that incorporates the complete solution of the stochastic model. Moreover, useful summer and autumn hindcast skill values are scored only with the model versions that include a representation of the extratropical feedbacks among its variables. Higher scores correspond to models that incorporate an index built from atmospheric temperature anomalies integrated from the surface up to the mid-troposphere, south of 20°S.http://www.tellusa.net/index.php/tellusa/article/view/27457/pdf_54Niño3.4predictabilitybarrierpredictorstropicalextratropicalseasonalstochasticmodels |
| spellingShingle | Miguel Tasambay-Salazar María José Ortizbeviá Francisco J. Alvarez-GarcÍa Antonio M. Ruiz De Elvira The Niño3.4 region predictability beyond the persistence barrier Tellus: Series A, Dynamic Meteorology and Oceanography Niño3.4 predictability barrier predictors tropical extratropical seasonal stochastic models |
| title | The Niño3.4 region predictability beyond the persistence barrier |
| title_full | The Niño3.4 region predictability beyond the persistence barrier |
| title_fullStr | The Niño3.4 region predictability beyond the persistence barrier |
| title_full_unstemmed | The Niño3.4 region predictability beyond the persistence barrier |
| title_short | The Niño3.4 region predictability beyond the persistence barrier |
| title_sort | nino3 4 region predictability beyond the persistence barrier |
| topic | Niño3.4 predictability barrier predictors tropical extratropical seasonal stochastic models |
| url | http://www.tellusa.net/index.php/tellusa/article/view/27457/pdf_54 |
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