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Abstract A subseasonal-to-seasonal (S2S) prediction system was recently developed using the GFDL Seamless System for Prediction and Earth System Research (SPEAR) global coupled model. Based on 20-yr hindcast results (2000–19), the boreal wintertime (November–April) Madden–Julian oscillation (MJO) prediction skill is revealed to reach 30 days measured before the anomaly correlation coefficient of the real-time multivariate (RMM) index drops to 0.5. However, when the MJO is partitioned into four distinct propagation patterns, the prediction range extends to 38, 31, and 31 days for the fast-propagating, slow-propagating, and jumping MJO patterns, respectively, but falls to 23 days for the standing MJO. A further improvement of MJO prediction requires attention to the standing MJO given its large gap with its potential predictability (38 days). The slow-propagating MJO detours southward when traversing the Maritime Continent (MC), and confronts the MC prediction barrier in the model, while the fast-propagating MJO moves across the central MC without this prediction barrier. The MJO diversity is modulated by stratospheric quasi-biennial oscillation (QBO): the standing (slow-propagating) MJO coincides with significant westerly (easterly) phases of QBO, partially explaining the contrasting MJO prediction skill between these two QBO phases. The SPEAR model shows its capability, beyond the propagation, in predicting their initiation for different types of MJO along with discrete precursory convection anomalies. The SPEAR model skillfully predicts the observed distinct teleconnections over the North Pacific and North America related to the standing, jumping, and fast-propagating MJO, but not the slow-propagating MJO. These findings highlight the complexities and challenges of incorporating MJO prediction into the operational prediction of meteorological variables. 

Observations and theory of convectively coupled equatorial waves suggest that they can be categorized into two distinct groups. Moisture modes are waves whose thermodynamics are governed by moisture fluctuations. The thermodynamics of the gravity wave group, on the other hand, are rooted in buoyancy (temperature) fluctuations. On the basis of scale analysis, it is found that a simple nondimensional parameter—akin to the Rossby number—can explain the processes that lead to the existence of these two groups. This parameter, defined as N mode , indicates that moisture modes arise when anomalous convection lasts sufficiently long so that dry gravity waves eliminate the temperature anomalies in the convective region, satisfying weak temperature gradient (WTG) balance. This process causes moisture anomalies to dominate the distribution of moist enthalpy (or moist static energy), and hence the evolution of the wave. Conversely, convectively coupled gravity waves arise when anomalous convection eliminates the moisture anomalies more rapidly than dry gravity waves can adjust the troposphere toward WTG balance, causing temperature to govern the moist enthalpy distribution and evolution. Spectral analysis of reanalysis data indicates that slowly propagating waves ( c p ~ 3 m s −1 ) are likely to be moisture modes while fast waves ( c p ~ 30 m s −1 ) exhibit gravity wave behavior, with “mixed moisture–gravity” waves existing in between. While these findings are obtained from a highly idealized framework, it is hypothesized that they can be extended to understand simulations of convectively coupled waves in GCMs and the thermodynamics of more complex phenomena. 

In this paper, it is shown that westward-propagating monsoon-low-pressure-system-like disturbances in the South Asian monsoon region can be simulated in an idealized moist general circulation model through the addition of a simplified parameterization of land. Land is parameterized as having one-tenth the heat capacity of the surrounding slab ocean, with evaporation limited by a bucket hydrology model. In this model, the prominent topography of the Tibetan Plateau does not appear to be necessary for these storm systems to form or propagate; therefore focus is placed on the simulation with land but no topography. The properties of the simulated storms are elucidated using regression analysis and compared to results from composites of storms from comprehensive GCMs in prior literature and reanalysis. The storms share a similar vertical profile in anomalous Ertel potential vorticity to those in reanalysis. Propagation, however, does not seem to be strongly dictated by beta-drift. Rather, it seems to be more closely consistent with linear moisture vortex instability theory, with the exception of the importance of the vertical advection term in the Ertel potential vorticity budget toward the growth and maintenance of disturbances. The results presented here suggest that a simplified GCM configuration might be able to be used to gain a clearer understanding of the sensitivity of monsoon low pressure systems to changes in the mean state climate.