Rainfall variability in Suriname and its relationship with the Tropical Pacific ENSO SST anomalies and the Atlantic SST anomalies

Abstract

Spatial correlations (r) in the annual rainfall anomalies are analyzed using principle component analyses (PCA). Cross correlation analysis and composites are used to measure the influence of sea surface temperatures anomalies (SSTAs) in the tropical Atlantic and tropical Pacific Ocean with the seasonal rainfall in Suriname. It is shown that the spatial and time variability in rainfall is mainly determined by the meridional movement of the Inter-tropical Convergence Zone (ITCZ). It occurs that the rainfall anomalies are fairly uniformly over the whole country. The strongest correlation between the December-January rainfall (short wet season) at station Cultuurtuin is found with the SSTAs in the Pacific region and is about c k Nino 1+2 = 0.59 at lag 1 month. In March-May rainfall (beginning long wet season) there is a lagged correlation with the SSTAs in the Pacific region (c lag 3 Nino 1+2 = 0.59). The June-August rainfall (end part of long wet season) shows the highest correlation with SSTAs in the TSA region and is about c = -0.52 for lag 0. In the September-November long dry season there is also a lagged correlation with the TSA SSTAs of about c lag 3 = 0.66. The different correlations and predictors can be used for seasonal rainfall predictions.

Spatial correlations (r) in the annual rainfall anomalies are analyzed using principle component analyses (PCA). Cross correlation analysis and composites are used to measure the influence of sea surface temperatures anomalies (SSTAs) in the tropical Atlantic and tropical Pacific Ocean with the seasonal rainfall in Suriname. It is shown that the spatial and time variability in rainfall is mainly determined by the meridional movement of the Inter-tropical Convergence Zone (ITCZ). It occurs that the rainfall anomalies are fairly uniformly over the whole country. The strongest correlation between the December-January rainfall (short wet season) at station Cultuurtuin is found with the SSTAs in the Pacific region and is about c k Nino 1+2 = 0.59 at lag 1 month. In March-May rainfall (beginning long wet season) there is a lagged correlation with the SSTAs in the Pacific region (c lag 3 Nino 1+2 = 0.59). The June-August rainfall (end part of long wet season) shows the highest correlation with SSTAs in the TSA region and is about c = -0.52 for lag 0. In the September-November long dry season there is also a lagged correlation with the TSA SSTAs of about c lag 3 = 0.66. The different correlations and predictors can be used for seasonal rainfall predictions.