The El Niño-Southern Oscillation (ENSO) is a complex, interannual phenomenon that is characterized by fluctuations of oceanic and atmospheric conditions across the equatorial Pacific Ocean. While it is well understood that the irregular periodic oscillation has two dominant phases, El Niño (warm state) and La Niña (cool state), the mechanisms preceding their onset remain less understood. For an El Niño event, there are two main tropical precursors that aid in prediction, including anomalous build up of oceanic heat in the western Pacific and recurrence of westerly wind bursts (WWBs). While the ocean evolves slower and the associated oceanic memory offers a source of predictability, it can be difficult to predict when and where WWBs will occur, their strength, and how they will impact El Niño development. WWBs can be attributed to a wide variety of factors: the phase of ENSO itself, the Madden-Julian Oscillation (MJO), the East Asian monsoon, and circulation changes that occur outside of the tropic; all of which further complicate our ability to understand the contribution extent of WWBs to El Niño onset. Forecasting ENSO is of particular interest due to the high frequency of El Niño false alarms in the past couple decades. Many of these forecasts occurred during the springtime, which is associated with lower forecast skill when models are initialized during February-May. During this timeframe, it can be difficult to predict an upcoming ENSO event and its characteristics. This work will examine previous false alarms and skillful forecasts that occurred from 1999 through 2018 to better understand the precursors. We will examine SST gradients, sea level pressure gradients, characteristics of the thermocline, and WWBs. We also aim to more clearly discern the impacts that WWBs have on ENSO onset by examining the characteristics, if any, of the MJO during the boreal winter and springtime before model initialization took place. The Seasonal-to-Multiyear Large Ensemble (SMYLE), a set of initialized hindcasts created using the Community Earth System Model Version 2 (CESM2), is used for this analysis.