| description abstract | A link between peak summer monsoon rainfall in central-east Brazil, composing part of the South American monsoon core region, and antecedent conditions in spring is disclosed. Rainfall in this region during part of spring holds a significant inverse correlation with rainfall in peak summer, especially during ENSO years. A surface?atmosphere feedback hypothesis is proposed to explain this relationship: low spring precipitation leads to low spring soil moisture and high late spring surface temperature; this induces a topographically enhanced low-level anomalous convergence and cyclonic circulation over southeast Brazil that enhances the moisture flux from northern and central South America into central-east Brazil, setting up favorable conditions for excess rainfall. Antecedent wet conditions in spring lead to opposite anomalies. The main links in this hypothesis are confirmed through correlation analysis of observed data: spring precipitation is negatively correlated to late spring surface temperature in central-east Brazil, and surface temperature in southeast Brazil is positively correlated with peak summer monsoon precipitation in central-east Brazil. The intermediary links of the surface?atmosphere feedback are tested in sensitivity experiments with the regional climate model version 3 (RegCM3). These experiments confirm that the proposed links are possible: the reduced soil moisture in central-east Brazil is shown to increase the surface temperature and produce a cyclonic anomaly over southeast Brazil, as well as increased precipitation in central-east Brazil. A crucial role of the mountains of southeast Brazil in anchoring the patterns of intraseasonal variability, and sustaining the ?dipolelike? precipitation mode observed over South America, is suggested. The low predictability of monsoon rainfall anomalies in central-east Brazil during the austral summer might be partially ascribed to the fact that the models do not well reproduce the topographical features and the land?atmosphere interactions that are important for the variability in that region. | |
