Potential predictability of an Iberian river flow based on its relationship with previous winter global SST

We examine the potential predictability of an important Iberian river (Douro) based on the coupling of a time series approach (ARMA) and previous seasonal sea surface temperature (SST) anomalies. A comprehensive search for predictors has identified only two key regions where spring streamflow anomalies are stably correlated with previous winter SST anomalies during the whole period under study (1956–2006); (1) central North Atlantic Ocean and (2) south-western Atlantic. A modelling scheme (the SST_model), based on linear regression, is developed and applied to simulate streamflow anomalies from these key SST regions. An additional study carried out over the residual time series (residual = flow − SST_model) shows three significant quasi-oscillatory modes with periods around 5, 3 and 2.4 years. Based on this information an ARMA(4,3) model was fitted to the residual. The combined [SST_model + ARMA(4,3)] model considerably improves the skill of the model compared to the climatology or persistence, explaining 76% of the total variance for spring Douro streamflow series. We conclude that the predictability of the spring Douro streamflow can be divided in two parts: the seasonal predictability associated with the previous winter Atlantic SST and the linear interannual predictability, which is considerable lower and shows some kind of association with El Niño.