Relationship between the Indian Ocean and ENSO with precipitation in the Caribbean of Costa Rica. Applied to the pineapple and banana crops

OROZCO-MONTOYA, R. Y PENALBA, O.

Trieste

Workshop; Workshop on Indian Ocean Variability and Teleconnections.; 2021

In the framework of the doctoral research one of the goals is to improve the knowledge of the physical mechanisms responsible for the spatio-temporal variability of the occurrence of extreme rainfall events in the Caribbean region of Costa Rica, with focus in pineapple (ananas comosus) and banana (musa spp) main crops exported in the country. Due to the relative predictability of the Indian Ocean Dipole (IOD) episodes and El Niño-Southern Oscillation (ENSO), the aim of this research is to understand the teleconnectivity of the Dipole Mode Index (DMI) and the Oceanic Niño Index (ONI) with the rainfall in December, critical month for pineapple and banana crops.28 monthly rainfall series located in the Caribbean region of Costa Rica were analyzed in 2 periods: 1985-2009 (23 stations) and 1997-2019 (5 stations, strategically located for crop analysis). For each period, the correlation between December rainfall and the DMI for October and November, and correlation between December rainfall and ONI in ASO, SON and OND were analyzed. In some stations, as the case of Limón, it was possible to analyze both periods in order to perform if the teleconnection change in time.The teleconnection analysis shows an inverse relationship between DMI of October and November and December rainfall. The significant signal is located in the southern of the study area and to the north close to the coast (Figure 1, left). The correlation associated with the ONI is also present in the region mainly in SON in the southern (Figure 1, right). The Limón station shows changes in the correlations between both periods, being higher for the most recent period in both indices.These results indicate a potentially relationship between IOD and rainfall in Caribbean region of Costa Rica, which will contribute to improve its predictability in the study region.