Rainfall in the Caribbean is an important resource for numerous stakeholders in the region. Based on previous work, which identified several variables that could provide predictive skill of rainfall in the region, canonical correlation analysis is applied to assess forecast skill for station-averaged sub-regional frequency and intensity of the Early-Rainy Season (ERS) and Late-Rainy Season (LRS) wet days, and magnitude of the Mid-Summer Drought (MSD). Predictor fields are explored from the ERA-Interim and North American Multi-Model Ensemble (NMME). The use of sea-level pressure (SLP), 850 hPa zonal winds (u850), vertically integrated zonal (UQ), and meridional (VQ) moisture fluxes show comparable, if not better, forecast skill than sea-surface temperatures (SSTs), which is generally the commonly-used predictor in a given region's seasonal climate forecasts. Generally, the highest predictive skill is found for the frequency of wet days. Rainfall characteristics in the Central and Eastern Caribbean have significant predictive skill. Forecast skill of rainfall characteristics in the Northwestern and Western Caribbean are lower and less consistent. The sub-regional differences and consistently significant skill across lead times up to at least two months can be attributed to persistent SST/SLP anomalies during the ERS that resemble the North Atlantic Oscillation, and that resembles the summer-time onset of the El Niño-Southern Oscillation during the LRS. The anomalous spatial patterns during the MSD bear resemblance to both the ERS and LRS signals. The results provide additional variables that can be used to forecast rainfall characteristics in the Caribbean and a way to tailor seasonal forecasts for each sub-region.

Knowledge of subseasonal-to-seasonal (S2S) rainfall characteristics such as onset, duration, and demise of the rainfall cycle, and characteristics of dry periods that are between rainfall seasons, can provide important insight for the agriculture, health, disaster, and energy industries. Several methods have attempted to calculate temporal characteristics of rainfall and few have worked with intermittent dry periods and calculate intermittent dry period characteristics. Issues arise when applying these methods for complex rainfall regimes, or regions that have one or more of the following: (1) multiple rainfall seasons in a given year, (2) a relatively wet dry season, (3) unclear transitions between wet and dry seasons. This study develops a new and comprehensive method for calculating S2S rainfall characteristics, especially for regions that have complex annual rainfall cycles. The method consists of three steps: (1) create the annual cycle climatology of rainfall and classify its modality by the presence or absence of intermittent dry period(s), (2) identify seasonal windows of the rainfall cycle based on its climatological modality, (3) calculate yearly intermittent dry period characteristics and calculate temporal rainfall characteristics for each year using information on daily rainfall amount and the concurrent rate of change. Application and results of the method are given for the Caribbean, which exhibits the properties of a region with complex rainfall regimes. The method can be utilized under a meteorological or agronomical lens and is able to delineate false meteorological and agronomical onsets and demises. Meteorological onsets and demises that are calculated via each year’s Early-Rainy Season (ERS) and Late-Rainy Season (LRS) mean thresholds effectively characterize the seasonal evolution of mean onsets and demises in the Caribbean. The year-to-year variability of Mid-Summer Drought (MSD) characteristics, and onsets and demises that are calculated by climatological ERS and LRS mean thresholds resemble the variability of seasonal rainfall totals in the Caribbean and are statistically significantly correlated with the identified dynamical processes that impact each seasonal component of the rainfall cycle. The method has important implications for prediction, modeling capabilities, and understanding the variability of rainfall across timescales.

The Caribbean seasonal rainfall cycle and its characteristics are heavily relied upon by the region’s inhabitants for their socioeconomic needs; the prediction of its variability would be valuable to society. An important way to understand the predictability of the Caribbean rainfall cycle is to study its interannual variability. Previous studies vary as to how and what large-scale climate driver(s) affect the interannual variability of rainfall and its associated dynamical mechanisms in the Caribbean. To address this, this study investigates wet and dry Caribbean early-rainy seasons (ERS; mid-April to mid-June) and late-rainy seasons (LRS; late August to mid-November) by conducting the following: (1) a spatial composite of rainfall from 34 Caribbean rainfall stations using daily data; and, (2) spatial composites of sea-surface temperature, sea-level pressure, and mean flow moisture convergence and transports. The ERS and LRS are impacted in distinctly different ways by two different, and largely independent, dominant large-scale phenomena: the North Atlantic Oscillation (NAO) and the El Niño-Southern Oscillation (ENSO), respectively. Dry ERS years are associated with a persistent dipole of cold and warm SSTs over the Caribbean Sea and Gulf of Mexico, respectively, that were caused by a preceding positive NAO state. This setting involves a wind-evaporation-SST (WES) feedback expressed in enhanced trade winds and consequently, moisture transport divergence over all of the Caribbean, except in portions of the NW Caribbean in May. A contribution from the preceding winter cold ENSO event is also discernible during dry ERS years. Dry LRS years are due to the summertime onset of an El Niño event, developing an inter-basin SLP pattern that fluxes moisture out of the Caribbean, except in portions of the NW Caribbean in November. Both large-scale climate drivers would have the opposite effect during their opposite phases leading to wet years for both seasons. The two rainy seasons are independent because the main drivers of their variability are independent. This has implications for prediction.

The Caribbean is a complex region that heavily relies on its rainfall cycle for its economic and societal needs. This makes the Caribbean especially susceptible to hydro-meteorological disasters (i.e. droughts and floods). Previous studies have investigated the seasonal cycle of rainfall in the Caribbean with monthly or longer resolutions that often mask the seasonal transitions and regional differences of rainfall. This has resulted in inconsistent findings on the seasonal cycle. In addition, the mechanisms that shape the climatological rainfall cycle in the region are not fully understood. To address these problems, this study conducts: (i) a principal component analysis of the annual cycle of precipitation across 38 Caribbean stations using daily observed precipitation data; and, (ii) a moisture budget analysis for the Caribbean, using the ERA-Interim Reanalysis. This study finds that the seasonal cycle of rainfall in the Caribbean hinges on three main facilitators of moisture convergence: the Eastern Pacific ITCZ, the Atlantic ITCZ, and the western flank of the North Atlantic Subtropical High (NASH). The Atlantic Warm Pool and Caribbean Low-Level Jet modify the extent of moisture provided by these main facilitators. The expansion and contraction of the western flank of NASH generate the bimodal pattern of the precipitation annual cycle in the northwestern Caribbean, central Caribbean, and with the Eastern Pacific ITCZ the western Caribbean. This study identifies the Atlantic ITCZ as the major source of precipitation for the central and southern Lesser Antilles, which is responsible for their unimodal rainfall pattern. Convergence by sub-monthly transients contributes little to Caribbean rainfall.

The atmospheric jet and blocking distributions, especially in the North Atlantic sector, have been challenging features for a climate model to realistically reproduce. This study examines climatological distributions of winter (December–February) daily jet latitude and blocking in the North Atlantic from the 40-member Community Earth System Model version 1 Large Ensemble (CESM1LE) simulations. This analysis aims at examining whether a broad range of internal climate variability encompassed by a large ensemble of simulations results in an improved representation of the jet latitude distributions and blocking days in CESM1LE. In the historical runs (1951–2005), the daily zonal wind at 850 hPa exhibits three distinct preferred latitudes for the eddy-driven jet position as seen in the reanalysis datasets, which represents a significant improvement from the previous version of the same model. However, the meridional separations between the three jet latitudes are much smaller than those in the reanalyses. In particular, the jet rarely migrates to the observed southernmost position around 37°N. This leads to the bias in blocking frequency that is too low over Greenland and too high over the Azores. These features are shown to be remarkably stable across the 40 ensemble members with negligible member-to-member spread. This result implies the range of internal variability of winter jet latitude and blocking frequency within the 55-year segment from each ensemble member is comparable to that represented by the full large ensemble. Comparison with 2046–2100 from the RCP8.5 future projection runs suggests that the daily jet position is projected to maintain the same three preferred latitudes, with a slightly higher frequency of occurrence over the central latitude around 50°N, instead of shifting poleward in the future as documented in some previous studies. In addition, the daily jet speed is projected not to change significantly between 1951–2005 and 2046–2100. On the other hand, the climatological mean jet is projected to become slightly more elongated and stronger on its southern flank, and the blocking frequency over the Azores is projected to decrease.