Author(s): Leonardo Franco Castillo Navarro; Pedro Rau; Jaime Luyo

Linked Author(s): Leonardo Franco Castillo Navarro, Pedro Rau

Keywords: ENSO; Discharge data; Sea Surface Temperature Anomaly; Correlation Pearson; Predictive model

Abstract: The Pacific coastal sector of Peru is mainly a dry area where precipitation events are episodic, however, on interannual time scales, in the North, there are extraordinary precipitation events associated with El Niño Southern Oscillation (ENSO). Therefore, an evaluation of climatic variables such as the Sea Surface Temperature Anomaly (SSTa) and its correlation with river discharges data is necessary to define prediction models. 19 stations with river discharge data (1965-2015) distributed along the North Pacific coast of Peru are analyzed. To classify El Niño and La Niña events we will use the Oceanic Niño Index (ONI)) where the Niño 3.4 anomalies are represented by the SSTa. A map of lags that improve the correlation in each discharge station and their respective statistical and physic interpretation is proposed. Finally, as results, a predictive model is built for each discharge station based on its preceding flows and the SSTa (corresponding to region 1+2 or region 3.4 associated with a lag that maximizes its correlation). The interpretation of results contains a physical support for the choice of the best significant variables.

DOI: https://doi.org/10.3850/IAHR-39WC252171192022241

Year: 2022