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We introduce a simple method to define the start and the end of the rainiest part of the year as the first and the last day of the year when the daily rain rate is more or less than the annual mean climatological rain rate for a region or at a given grid point of the rainfall analysis, respectively. A novelty of this work is the adoption of a perturbation technique to generate a total of 1001 ensemble members to account for observational and analysis uncertainties. This allows for a probabilistic estimate of the start and retreat dates of the rainy season at the granularity of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), version 6, rainfall analysis over Central America. The seasonal cycle of the IMERG rainfall analysis is also found to verify with in situ observations in the region. Many large-scale climate drivers affect regional rainfall, often with complex interactions that affect the onset date, retreat date, and magnitude of the seasonal rainfall cycle, making it difficult to predict the length or total quantity of seasonal rainfall using climate drivers alone. Once an onset date is established, however, this metric alone can be more indicative of both the length and total seasonal rainfall anomaly than predicting how the climate drivers will interact to affect the quantity and duration of upcoming seasonal rainfall. The local relationships of the start date with seasonal length and rainfall anomaly are leveraged to produce effective seasonal outlooks of the rainy season for the region by just monitoring the start date variations. Significance Statement: The start date and retreat date of the rainy season in Central America are defined every year, precisely to a specific date from our proposed definition of it. This is possible because the region exhibits a strong seasonality of the rainfall. As a result, the year-to-year (interannual) variation of the seasonal rainfall during the rainy season is also determined by the variations in the length of the season that are usually overlooked in fixed calendar seasons. We define the start or retreat date of the rainy season as the first or the last day of the year when the daily rain rate exceeds or falls below the average daily rainfall from 2001 to 2022, respectively. We also find that both start and retreat date variations independently influence the length and total seasonal rainfall of the rainy season. Consequently, these relationships are leveraged to provide an outlook of the forthcoming rainy season from the diagnosis of the variations of its onset date, which is shown to be an effective predictor with significant useful seasonal prediction skills. [ABSTRACT FROM AUTHOR]

This study reports on the analysis of the results from a 20 km grid spacing, Regional Coupled ocean–atmosphere Model (RCM) integration over the Western Pacific Warm Pool (WP2). The RCM was integrated over a 20‐year period (1986–2005) using reanalysis boundary conditions for the atmosphere and the ocean. This is a first‐of‐a‐kind study with an RCM at 20 km over the WP2. The RCM simulation shows reasonable fidelity of the mean state and of the Madden–Julian Oscillation (MJO). We utilize this successful integration of the RCM to understand a well‐known observed feature of MJOs in the WP2 to be of the strongest amplitude during the December–March period of the year. Our analysis of the model integration reveals that the recharge of moist static energy (MSE) prior to peak MJO convection and its discharge during and after the convection explains the MJO in the simulation. The recharge/discharge of the MSE is shown to be largely dictated by horizontal advection, which is stemmed to a small extent by column‐integrated radiative heating and surface evaporation. This balance of forces in the evolution of the MSE anomalies and their corresponding variations with sea‐surface temperature (SST) anomalies at MJO time‐scales in the WP2 is strongest in the December–March period in the RCM simulation. [ABSTRACT FROM AUTHOR]