期刊
CLIMATE RESEARCH
卷 87, 期 -, 页码 67-80出版社
INTER-RESEARCH
DOI: 10.3354/cr01685
关键词
Brazilian Global Atmospheric Model; Amazon basin; Water balance; Climate modeling
资金
- Coordination for Improvement of Higher Level Personnel (CAPES)
This study evaluated the isolated effects of interannual and decadal time scales on the water balance of the Amazon basin. The results showed that isolated interannual scales weakened the impacts of El Nino and La Nina on water balance components. These findings are important for monitoring the climate of humid tropical regions.
In this study, we evaluated the isolated effects of interannual and decadal time scales on the water balance of the Amazon basin. This research is interesting because it brings the dynamical response of water balance components to a particular ocean-scale variability. For this, we used the Brazilian Global Atmospheric Model (BAM) and SST filtering techniques. The impact of isolated interannual and decadal time scales was quantified for episodes of ENSO and the Atlantic dipole (AD). The results show that isolated interannual scales weaken the impacts of El Nino and La Nina on water balance components in the northern Amazon and northeastern Brazil. Such weakening is more evident in episodes of El Nino than in those of La Nifia. This indicates that El Nino is more dependent on other time scales (in addition to interannual) than is La Nina. In relation to the Atlantic, a positive AD increases (decreases) precipitation in the northern (southern) Amazon basin in the experiment with all SST time scale variabilities. On the other hand, when the decadal scale is isolated, an increase in precipitation in the northern basin is not observed, losing the dipole pattern in the precipitation anomaly between the northern and southern Amazon basin. BAM is not sensitive to a negative AD when SST is isolated in the decadal scale. These results are important for monitoring the climate of humid tropical regions, mainly for the study of ENSO, since, according to recent research, these extreme events will be increasingly frequent and intense.
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