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Abstract The Madden‐Julian Oscillation (MJO) is often used for subseasonal forecasting of tropical cyclone (TC) activity. However, TC activity still has considerable variability even given the state of the MJO. This study evaluates the connection between MJO propagation speed with Atlantic TC activity and possible physical mechanisms guiding this relation. We find the Atlantic sees the highest accumulated cyclone energy (ACE) during MJO phase 2. However, the odds of above average ACE in the Atlantic is greatest during slow MJO propagation. We find that slow propagation of the MJO results in lower vertical wind shear anomalies over the Caribbean and main development region compared with typical MJO propagation. Typical MJO propagation produces an amplified height pattern and lower height anomalies along the region of the tropical upper tropospheric trough which is known to impede Atlantic TC activity. Slow MJO propagation sees weaker height anomalies over the Atlantic. 

Abstract Extreme weather events have devastating impacts on human health, economic activities, ecosystems, and infrastructure. It is therefore crucial to anticipate extremes and their impacts to allow for preparedness and emergency measures. There is indeed potential for probabilistic subseasonal prediction on time scales of several weeks for many extreme events. Here we provide an overview of subseasonal predictability for case studies of some of the most prominent extreme events across the globe using the ECMWF S2S prediction system: heatwaves, cold spells, heavy precipitation events, and tropical and extratropical cyclones. The considered heatwaves exhibit predictability on time scales of 3–4 weeks, while this time scale is 2–3 weeks for cold spells. Precipitation extremes are the least predictable among the considered case studies. ­Tropical cyclones, on the other hand, can exhibit probabilistic predictability on time scales of up to 3 weeks, which in the presented cases was aided by remote precursors such as the Madden–Julian oscillation. For extratropical cyclones, lead times are found to be shorter. These case studies clearly illustrate the potential for event-dependent advance warnings for a wide range of extreme events. The subseasonal predictability of extreme events demonstrated here allows for an extension of warning horizons, provides advance information to impact modelers, and informs communities and stakeholders affected by the impacts of extreme weather events. 

Abstract The Madden‐Julian oscillation (MJO) is the leading source of global subseasonal predictability; however, many dynamical forecasting systems struggle to predict MJO propagation through the Maritime Continent. Better understanding the biases in simulated physical processes associated with MJO propagation is the key to improve MJO prediction. In this study, MJO prediction skill, propagation processes, and mean state biases are evaluated in reforecasts from models participating in the Subseasonal Experiment (SubX) and Subseasonal to Seasonal (S2S) prediction projects. SubX and S2S reforecasts show MJO prediction skill out to 4.5 weeks based on the Real‐time Multivariate MJO index consistent with previous studies. However, a closer examination of these models' representation of MJO propagation through the Maritime Continent reveals that they fail to predict the MJO convection, associated circulations, and moisture advection processes beyond 10 days with most of models underestimating MJO amplitude. The biases in the MJO propagation can be partly associated with the following mean biases across the Indo‐Pacific: a drier low troposphere, excess surface precipitation, more frequent occurrence of light precipitation rates, and a transition to stronger precipitation rates at lower humidity than in observations. This indicates that deep convection occurs too frequently in models and is not sufficiently inhibited when tropospheric moisture is low, which is likely due to the representation of entrainment.