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Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/20.500.12008/54432 Cómo citar
Título: The stochastic skeleton model for the Madden–Julian Oscillation with time-dependent observation-based forcing
Autor: Ehstand, Noémie
Donner, Reik V.
López, Cristóbal
Barreiro, Marcelo
Hernández-García, Emilio
Tipo: Artículo
Palabras clave: MJO, ENSO
Fecha de publicación: 2025
Resumen: We analyze solutions to the stochastic skeleton model, a minimal non-linear oscillator model for the Madden–Julian Oscillation (MJO). This model has been recognized for its ability to reproduce several large-scale features of the MJO. In previous studies, the model’s forcings were predominantly chosen to be mathematically simple and time-independent. Here, we present solutions to the model with time-dependent observation-based forcing functions. Our results show that the model, with these more realistic forcing functions, successfully replicates key characteristics of MJO events, such as their lifetime, extent, and amplitude, whose statistics agree well with observations. However, we find that the seasonality of MJO events and the spatial variations in the MJO properties are not well reproduced. Having implemented the model in the presence of time-dependent forcings, we can analyze the impact of temporal variability at different timescales. In particular, we study the model’s ability to reflect changes in MJO characteristics under the different phases of El Niño–Southern Oscillation (ENSO). We find that it does not capture significant differences in the studied characteristics of MJO events in response to differences in conditions during El Niño, La Niña, and neutral ENSO.
Editorial: European Geosciences Union
EN: Nonlinear Processes in Geophysics, 2025, 32: 367–382.
Citación: Ehstand, N, Donner, R, López, C [y otros autores]. "The stochastic skeleton model for the Madden–Julian Oscillation with time-dependent observation-based forcing". Nonlinear Processes in Geophysics. [en línea] 2025, 32: 367–382. 16 h. DOI: 10.5194/npg-32-367-2025
ISSN: 1607-7946
Licencia: Licencia Creative Commons Atribución (CC - By 4.0)
Aparece en las colecciones: Publicaciones académicas y científicas - Facultad de Ciencias

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