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Few studies have utilized machine learning techniques to predict or understand the Madden‐Julian oscillation (MJO), a key source of subseasonal variability and predictability. Here, we present a simple framework for real‐time MJO prediction using shallow artificial neural networks (ANNs). We construct two ANN architectures, one deterministic and one probabilistic, that predict a real‐time MJO index using maps of tropical variables. These ANNs make skillful MJO predictions out to ∼18 days in October‐March and ∼11 days in April‐September, outperforming conventional linear models and efficiently capturing aspects of MJO predictability found in more complex, dynamical models. The flexibility and explainability of simple ANN frameworks are highlighted through varying model input and applying ANN explainability techniques that reveal sources and regions important for ANN prediction skill. The accessibility, performance, and efficiency of this simple machine learning framework is more broadly applicable to predict and understand other Earth system phenomena.

Midlatitude stationary waves are relatively persistent large‐scale longitudinal variations in atmospheric circulation. Although recent case studies have suggested a close connection between stationary waves and extreme weather events, little is known about the global‐scale linkage between stationary waves and wildfire activity, as well as the potential changes in this relationship in a warmer climate. Here, by analyzing the Community Earth System Model version 2 large ensemble, we show that a zonal wavenumber 5–6 stationary wave pattern tends to synchronize wildfire occurrences across the Northern Hemisphere midlatitudes. The alternation of upper‐troposphere ridges and troughs creates a hemispheric‐scale spatial pattern of alternating hot/dry and cold/wet conditions, which increases or decreases wildfire occurrence, respectively. More persistent high‐pressure conditions drastically increase wildfire probabilities. Even though the dynamics of these waves change little in response to anthropogenic global warming, the corresponding midlatitude wildfire variability is projected to intensify due to changes in climate background conditions.

With widespread influence on global climate and weather extremes, the Madden-Julian Oscillation (MJO) plays a crucial role in subseasonal prediction. Our latest global climate models (GCMs), however, have great difficulty in realistically simulating the MJO. This model inability is largely due to problems in representation of MJO’s cumulus organization. This study, based on a series of idealized aqua-planet model experiments using an atmospheric-only GCM, clearly demonstrates that MJO propagation is strongly modulated by the large-scale background state in which the lower-tropospheric mean moisture gradient and zonal winds are critical. Therefore, when tuning climate models to achieve improved MJO simulations, particular attention needs to be placed on the model large-scale mean state that is also significantly affected by cumulus parameterizations. This study indicates that model biases in representing MJO propagation may be related to the widely reported double-ITCZ (intertropical convergence zone) problem in climate models.

The impacts of rising carbon dioxide (CO₂) concentration and ocean feedbacks on the Madden‐Julian Oscillation (MJO) are investigated with the Community Atmospheric Model Version 5 (CAM5) in an idealized aquaplanet configuration. The climate response associated with quadrupled CO₂concentrations and sea surface temperature (SST) warming are examined in both the uncoupled CAM5 and a version coupled to a slab ocean model. Increasing CO₂concentrations while holding SST fixed produces only small impacts to MJO characteristics, while the SST change resulting from increased CO₂concentrations produces a significant increase in MJO precipitation anomaly amplitude but smaller increase in MJO circulation anomaly amplitude, consistent with previous studies. MJO propagation speed increases in both coupled simulations with quadrupling of CO₂and uncoupled simulations with the same climatological surface temperature warming imposed, although propagation speed is increased more with coupling. While climatological SST changes are identical between coupled and uncoupled runs, other aspects of the basic state such as zonal winds do not change identically. For example, climate warming produces stronger superrotation and weaker mean lower tropospheric easterlies in the coupled run, which contributes to greater increases in MJO eastward propagation speed with warming through its effect on moisture advection. The column process, representing the sum ofmore »vertical moist static energy (MSE) advection and radiative heating anomalies, also supports faster eastward propagation with warming in the coupled run. How differing basic states between coupled and uncoupled runs contribute to this behavior is discussed in more detail.

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Since its discovery in the early 1970s, the crucial role of the Madden‐Julian Oscillation (MJO) in the global hydrological cycle and its tremendous influence on high‐impact climate and weather extremes have been well recognized. The MJO also serves as a primary source of predictability for global Earth system variability on subseasonal time scales. The MJO remains poorly represented in our state‐of‐the‐art climate and weather forecasting models, however. Moreover, despite the advances made in recent decades, theories for the MJO still disagree at a fundamental level. The problems of understanding and modeling the MJO have attracted significant interest from the research community. As a part of the AGU's Centennial collection, this article provides a review of recent progress, particularly over the last decade, in observational, modeling, and theoretical study of the MJO. A brief outlook for near‐future MJO research directions is also provided.

Abstract The Madden-Julian oscillation (MJO) has profound impacts on weather and climate phenomena, and thus changes in its activity have important implications under human-induced global climate change. Here, the time at which the MJO change signal emerges from natural variability under anthropogenic warming is investigated. Using simulations of the Community Earth System Model version 2 large ensemble forced by the shared socioeconomic pathways SSP370 scenario, an increase in ensemble mean MJO precipitation amplitude and a smaller increase in MJO circulation amplitude occur by the end of the 21 st century, consistent with previous studies. Notably, the MJO precipitation amplitude change signal generally emerges more than a decade earlier than that of MJO wind amplitude. MJO amplitude changes also emerge earlier over the eastern Pacific than other parts of the tropics. Our findings provide valuable information on the potential changes of MJO variability with the aim of improving predictions of the MJO and its associated extreme events.

Abstract This study investigates why the major convective envelope of the Madden–Julian oscillation (MJO) detours to the south of the Maritime Continent (MC) only during boreal winter [December–March (DJFM)]. To examine processes affecting this MJO detour, the MJO-related variance of precipitation and column-integrated moisture anomalies in DJFM are compared with those in the seasons before [October–November (ON)] and after [April–May (AM)]. While MJO precipitation variance is much higher in the southern MC (SMC) during DJFM than in other seasons, the MJO moisture variance is comparable among the seasons, implying that the seasonal locking of the MJO’s southward detour cannot be explained by the magnitude of moisture anomalies alone. The higher precipitation variance in the SMC region is partly explained by the much higher moisture sensitivity of precipitation in DJFM than in other seasons, resulting in a more efficient conversion of anomalous moisture to anomalous precipitation. DJFM is also distinguishable from the other seasons by stronger positive wind–evaporation feedback onto MJO precipitation anomalies due to the background westerly wind in the lower troposphere. It is found that the seasonal cycle of moisture–precipitation coupling and wind–evaporation feedback in the SMC region closely follows that of the Australian monsoon, which is active exclusivelymore »in DJFM. Our results suggest that the MJO’s southward detour in the MC is seasonally locked because it occurs preferentially when the Australian monsoon system produces a background state that is favorable for MJO development in the SMC.« less

Abstract The impact of the environmental background wind on the diurnal cycle near tropical islands is examined in observations and an idealized model. Luzon Island in the northern Philippines is used as an observational test case. Composite diurnal cycles of CMORPH precipitation are constructed based on an index derived from the first empirical orthogonal function (EOF) of ERA5 zonal wind profiles. A strong precipitation diurnal cycle and pronounced offshore propagation in the leeward direction tends to occur on days with a weak, offshore prevailing wind. Strong background winds, particularly in the onshore direction, are associated with a suppressed diurnal cycle. Idealized high resolution 2-D Cloud Model 1 (CM1) simulations test the dependence of the diurnal cycle on environmental wind speed and direction by nudging the model base-state toward composite profiles derived from the reanalysis zonal wind index. These simulations can qualitatively replicate the observed development, strength, and offshore propagation of diurnally generated convection under varying wind regimes. Under strong background winds, the land-sea contrast is reduced, which leads to a substantial reduction in the strength of the sea-breeze circulation and precipitation diurnal cycle. Weak offshore prevailing winds favor a strong diurnal cycle and offshore leeward propagation, with the direction ofmore »propagation highly sensitive to the background wind in the lower free troposphere. Offshore propagation speed appears consistent with density current theory rather than a direct coupling to a single gravity wave mode, though gravity waves may contribute to a destabilization of the offshore environment.« less

Changes to the tropical eastern North Pacific Intraseasonal Oscillation (ISO) at the end of the 21st century and implications for tropical cyclone (TC) genesis are examined in the Shared Socioeconomic Pathways (SSP585) scenario of the Coupled Model Intercomparison Project phase 6 (CMIP6) data set. Multimodel mean composite low-level wind and precipitation anomalies associated with the leading intraseasonal mode indicate that precipitation amplitude increases while wind amplitude weakens under global warming, consistent with previous studies for the Indo-Pacific warm pool. The eastern North Pacific intraseasonal precipitation/wind pattern also tends to shift southwestward in a warmer climate, associated with weaker positive precipitation anomalies near the coast of Mexico and Central America during the enhanced convection/westerly wind phase. Implications for the modulation of TC genesis by the leading intraseasonal mode are then explored using an empirical genesis potential index (GPI). In the historical simulation, GPI shows positive anomalies in the eastern North Pacific in the convectively enhanced phase of the ISO. The ISO’s modulation of GPI weakens near the coast of Mexico and Central America with warming, associated with a southward shift of GPI anomalies. Further examination of the contribution from individual environmental variables that enter the GPI shows that relative humidity andmore »vorticity changes during ISO events weaken positive GPI anomalies near the Mexican coast with warming and make genesis more favorable to the southwest. The impact of vertical shear anomaly changes is also to favor genesis away from the coast. These results suggest a weaker modulation of TCs near the Mexican Coast by the ISO in a warmer climate.« less

Abstract The excitation of the Pacific–North American (PNA) teleconnection pattern by the Madden–Julian oscillation (MJO) has been considered one of the most important predictability sources on subseasonal time scales over the extratropical Pacific and North America. However, until recently, the interactions between tropical heating and other extratropical modes and their relationships to subseasonal prediction have received comparatively little attention. In this study, a linear inverse model (LIM) is applied to examine the tropical–extratropical interactions. The LIM provides a means of calculating the response of a dynamical system to a small forcing by constructing a linear operator from the observed covariability statistics of the system. Given the linear assumptions, it is shown that the PNA is one of a few leading modes over the extratropical Pacific that can be strongly driven by tropical convection while other extratropical modes present at most a weak interaction with tropical convection. In the second part of this study, a two-step linear regression is introduced that leverages a LIM and large-scale climate variability to the prediction of hydrological extremes (e.g., atmospheric rivers) on subseasonal time scales. Consistent with the findings of the first part, most of the predictable signals on subseasonal time scales are determined bymore »the dynamics of the MJO–PNA teleconnection while other extratropical modes are important only at the shortest forecast leads.« less