Central America is a region regularly affected by natural disasters, with most of them having a hydro-meteorological origin. Therefore, the understanding of annual changes of precipitation upon the region is relevant for planning and mitigation of natural disasters. This thesis focuses on studying the precipitation variability at annual scales in Central America within the framework of the Swedish Centre for Natural Disaster Science. The aims of this thesis are: i) to establish the main climate variability sources during the boreal winter, spring and summer by using different statistical techniques, and ii) to study the connection of sea surface temperature anomalies of the neighbouring oceans with extreme precipitation events in the region. Composites analysis is used to establish the variability sources during winter. Canonical correlation analysis is employed to explore the connection between the SST anomalies and extreme rainfall events during May-June and August-October. In addition, a global circulation model is used to replicate the results found with canonical correlation analysis, but also to study the relationship between the Caribbean Sea surface temperature and the Caribbean low-level jet. The results show that during winter both El Niño Southern Oscillation and the Pacific Decadal Oscillation, are associated with changes of the sea level pressure near the North Atlantic Subtropical High and the Aleutian low. In addition, the El Niño Southern Oscillation signal is intensified (destroyed) when El Niño and the Pacific Decadal Oscillation have the same (opposite) sign. Sea surface temperature anomalies have been related to changes in both the amount and temporal distribution of rainfall. Precipitation anomalies during May-June are associated with sea surface temperature anomalies over the Tropical North Atlantic region. Whereas, precipitation anomalies during August-September-October are associated with the sea surface temperature anomalies contrast between the Pacific Ocean and the Tropical North Atlantic region. Model outputs show no association between sea surface temperature gradients and the Caribbean low-level jet intensification. Canonical correlation analysis shows potential for prediction of extreme precipitation events, however, forecast validation shows that socio-economic variables must be included for more comprehensive natural disaster assessments.