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The Combined and Individual Effects of the North Atlantic Oscillation and the Atlantic Meridional Mode on Early Rainfall Season Precipitation in the Insular Caribbean
  • Flavia Moraes,
  • Gabriel Kooperman,
  • Thomas Mote
Flavia Moraes
University of Georgia

Corresponding Author:flavia.moraes@uga.edu

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Gabriel Kooperman
University of Georgia
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Thomas Mote
Univ Georgia
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Abstract

The insular Caribbean is a region influenced by Atlantic Ocean climate variability. Effects of low-frequency atmospheric circulation patterns on the precipitation of the Caribbean have been well documented. However, individual modes of variability are usually only considered in isolation. Here we analyse the combined and individual effects of the North Atlantic Oscillation (NAO) and the Atlantic Meridional Mode (AMM) on insular Caribbean precipitation. This work focuses on the Early Rainfall Season (ERS, April-July), which explains much of the interannual variability in precipitation for this region, from 1960-2016. Correlation analysis compare monthly NAO and AMM indices from the National Oceanic and Atmospheric Administration (NOAA) against monthly Caribbean precipitation from the Climate Research Unit (CRU) year-by-year climate variables by country. Sea surface temperature (SST) and sea level pressure (SLP) composites using NOAA data were also created to analyse regional patterns. Analysis of the results show that the NAO and AMM presented a correlation of opposite signs and affected the Eastern Caribbean (from Dominican Republic to Grenada) during ERS, resulting in precipitation anomalies above/below ± 10%. The combined and individual effects of NAO and AMM indicate that Feb-Mar NAO and AMM are significant correlated to May-Jun Eastern Caribbean precipitation anomalies. More frequent and consistent regional effects on precipitation anomalies, and more regionally spread and persistent SLP and SST were registered when both NAO and AMM occurred together in the previous winter. These results could be helpful in seasonal forecasting, by indicating whether a wetter or drier ERS would be expected based on the previous season NAO and AMM activity.