Prediction of interannual climate variations [Libro electrónico] / editor: J. Shukla
Shukla, J [editor].
Tipo de material: Libro en línea Series Editor: New York, New York, United States: Springer-Verlag, c1993Descripción: xv, 265 páginas : ilustraciones ; 25 centímetros.ISBN: 3540545913; 0387545913; 9783642769627 (Print); 9783642769603 (Online).Tema(s): Climatic changes -- Forecasting -- Congresses | Weather forecasting -- Congresses | Ocean-atmosphere interaction -- Congresses | Atmospheric circulation -- Forecasting -- CongressesNota de acceso: Disponible para usuarios de ECOSUR con su clave de acceso Nota de bibliografía: Incluye bibliografía Número de sistema: 56170Contenidos:Mostrar Resumen:Tipo de ítem | Biblioteca actual | Colección | Signatura | Estado | Fecha de vencimiento | Código de barras |
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Libros | Biblioteca Electrónica Recursos en línea (RE) | Acervo General | Recurso digital | ECO400561704902 |
Incluye bibliografía
Chapter 1. Reviews.. Chapter 2. Coupled models.. Chapter 3. Low-frequency variability.. Chapter 4. Present status of seasonal forecasting.. Chapter 5. Predictability.. Appendix
Disponible para usuarios de ECOSUR con su clave de acceso
It has been known for some time that the behavior of the short-term fluctuations of the earth's atmosphere resembles that of a chaotic non-linear dynamical system, and that the day-to-day weather cannot be predicted beyond a few weeks. However, it has also been found that the interactions of the atmosphere with the underlying oceans and the land surfaces can produce fluctuations whose time scales are much longer than the limits of deterministic prediction of weather. It is, therefore, natural to ask whether it is possible that the seasonal and longer time averages of climate fluctuations can be predicted with sufficient skill to be beneficial for social and economic applications, even though the details of the day-to-day weather cannot be predicted beyond a few weeks. The main objective of the workshop was to address this question by assessing the current state of knowledge on predictability of seasonal and interannual climate variability and to investigate various possibilities for its prediction. eng
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