A 10-member ensemble from phase 5 of the Coupled Model Intercomparison Project (CMIP5) is used to analyze the Caribbean’s future climate when mean global surface air temperatures are 1.5°, 2.0°, and 2.5°C above preindustrial (1861–1900) values. The global warming targets are attained by the 2030s, 2050s, and 2070s respectively for RCP4.5. The Caribbean on average exhibits smaller mean surface air temperature increases than the globe, although there are parts of the region that are always warmer than the global warming targets. In comparison to the present (using a 1971–2000 baseline), the Caribbean domain is 0.5° to 1.5°C warmer at the 1.5°C target, 5%–10% wetter except for the northeast and southeast Caribbean, which are drier, and experiences increases in annual warm spells of more than 100 days. At the 2.0°C target, there is additional warming by 0.2°–1.0°C, a further extension of warm spells by up to 70 days, a shift to a predominantly drier region (5%–15% less than present day), and a greater occurrence of droughts. The climate patterns at 2.5°C indicate an intensification of the changes seen at 2.0°C. The shift in the rainfall pattern between 1.5°C (wet) and 2.0°C (dry) for parts of the domain has implications for regional adaptation pursuits. The results provide some justification for the lobby by the Caribbean Community and Small Island Developing States to limit global warming to 1.5°C above preindustrial levels, as embodied in the slogan “1.5 to Stay Alive.”

The Statistical Downscaling Model (SDSM) is used to investigate future projections of daily minimum and maximum temperature extremes for 45 stations and rainfall extremes for 39 stations across the Caribbean and neighbouring regions. Models show good skill in reproducing the monthly climatology of the mean daily temperatures and the frequencies of warm days, warm nights, cool days and cool nights between 1961 and 2001. Models for rainfall exhibit lower skill but generally capture the monthly climatology of mean daily rainfall and the spatial distribution of the mean annual maximum number of consecutive dry days (CDD) and mean annual count of days with daily rainfall above 10 mm (R10). Future projections suggest an increase (decrease) in warm (cool) days and nights by 2071-2099 under the A2 and B2 scenarios relative to . An increase in CDD is suggested for most stations except some eastern Caribbean stations and Bahamas. Decreases in RX1 (monthly maximum 1-day precipitation), R10 and R95p (annual total rainfall above the 95th percentile) are also suggested for some northern Caribbean locations and Belize under the A2 scenario, compared to a mixture of increases and decreases for the eastern Caribbean. Atmospheric predictors used in SDSM correlate well with known oceanic and atmospheric drivers of Caribbean climate, e.g. the Atlantic Multidecadal Oscillation (AMO) on a seasonal timescale. Atlantic sea surface temperatures and the Caribbean low level jet appear to have significant influence on Caribbean temperature and rainfall extremes.

This study assesses the skill of four statistical models in hindcasting North Atlantic annual tropical cyclone (TC) frequency over 1950–2008 with the aim of projecting future activity. Three of the models are motivated by operational statistical forecast schemes and are premised on standard hurricane predictors including sea surface temperatures (SSTs) and near‐surface zonal winds. The fourth model uses an SST gradient index previously proposed for Caribbean seasonal rainfall prediction. The statistical models, created from backward regression, explain 24–48% of the observed variability in 1950–2008 annual TC frequency. The future state of the predictors is extracted from the ECHAM5, HadCM3, MRI CGCM2.3.2a, and MIROC3.2 global climate model (GCM) simulations under the Coupled Model Intercomparison Project Phase 3. Models utilizing SST and near‐surface wind predictors suggest significant increases in mean annual frequency by 2–8 TCs by 2070–2090, compared to a single surface wind predictor model, indicating that positive trends in SSTs under global warming have a larger relative influence on projections than changes in the variability of the surface winds. Wind‐only models exhibit declines in TC frequency, while the SST gradient model yields little change relative to the present‐day mean. Backward regression reapplied against the 1990–2008 period, analogous to future warmer oceanic and atmospheric state relative to the earlier years in the record, retains only the Caribbean low‐level jet (CLLJ)‐type predictors, explaining up to 82% of TC frequency variability and suggesting a more dominant role for the CLLJ in a warmer climate. Projections using the new models show either a more conservative increase or a stronger decrease in frequency, consistent with a stronger CLLJ.

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Given recent insights into the role of anticyclonic Rossby wave breaking (AWB) in driving subseasonal and seasonal North Atlantic tropical cyclone (TC) activity, this study further examines tropical versus subtropical impacts on TC activity by considering large-scale influences on boreal summer tropical zonal vertical wind shear (VWS) variability, a key predictor of seasonal TC activity. Through an empirical orthogonal function analysis, it is shown that subtropical AWB activity drives the second mode of variability in tropical zonal VWS, while El Niño–Southern Oscillation (ENSO) primarily drives the leading mode of variability. Linear regressions of the four leading principal components against tropical North Atlantic zonal VWS and accumulated cyclone energy show that while the leading mode holds much of the regression strength, some improvement can be achieved with the addition of the second and third modes. Furthermore, an index of AWB-associated VWS anomalies, a proxy for AWB impacts on the large-scale environment, may be a better indicator of summertime VWS anomalies. The utilization of this index may be used to better understand AWB’s contribution to seasonal TC activity.