Sulian Thual

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12 The stochastic skeleton model is a simplied model for the Madden-Julian oscil-13 lation (MJO) and intraseasonal-planetary variability in general involving coupling of 14 planetary-scale dry dynamics, moisture, and a stochastic parametrization for the unre-15 solved details of synoptic-scale activity. The model captures the fundamental features 16 of the(More)
Atmospheric wind bursts in the tropics play a key role in the dynamics of the El Niño Southern Oscillation (ENSO). A simple modeling framework is proposed that summarizes this relationship and captures major features of the observational record while remaining physically consistent and amenable to detailed analysis. Within this simple framework, wind burst(More)
x An RMM-like index was created for the skeleton model that mimics observations 21 x Stochasticity helps improve MJO initiation and termination event statistics 22 x The skeleton model produces more realistic MJOs when forced with observed SSTs 23 24 3 Abstract 25 The Madden-Julian oscillation (MJO) skeleton model is a low-order dynamic model that 26 is(More)
Atmospheric wind bursts in the tropics plays a key role in the dynamics of the El Niño Southern Oscillation (ENSO). A simple mod-eling framework is proposed that summarizes this relationship and captures major features of the observational record while remaining physically consistent and amenable to detailed analysis. Within this simple framework, wind(More)
The Madden-Julian oscillation (MJO) is the dominant mode of variability in the tropical atmosphere on intraseasonal timescales and planetary spatial scales. The skeleton model is a minimal dynamical model that recovers robustly the most fundamental MJO features of (I) a slow eastward speed of roughly 5 ms −1 , (II) a peculiar dispersion relation with dω/dk(More)
The supplementary information is organized as follows. In Section 1 we detail the asymptotic expansion used to derive the ENSO model at the interannual timescale. In Section 2 we detail the model's meridional truncation. In Section 3 we provide additional theoretical details on the two-state Markov jump process. In Section 4 we detail the algorithm for(More)
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