CR prepress abstract  -  DOI:

Multi-scale structure of tropical rainfall response to SST fluctuations

Miguel Nogueira*


ABSTRACT: The sensitivity of tropical rainfall to sea surface temperature (SST) fluctuations was investigated using a multi-scale analysis framework, covering time-scales between a few days and one decade. The analysis includes an inter-comparison between a satellite-based observational dataset, and two twentieth-century GCM-based products: ERA-20CM ensemble of atmospheric simulations, and ERA-20C reanalysis. The results provide robust evidence for the physical linear response of regional rainfall to SST fluctuations at multi-year time-scales. Indeed, all datasets showed tight correlations between rainfall and local SST, Niño-3.4 index, and local surface downwelling longwave radiation (DLR) over wide tropical regions. Additionally, the rainfall-DLR correlation held under a clear-sky approximation. These three correlations are tightly related since Niño-3.4 index and clear-sky DLR can be computed from SST alone. The latter requires a robust correlation between local precipitable water vapour (W) and SST (i.e. Clausius-Clapeyron relationship), which was confirmed at multi-year scales over large portions of the tropics. All datasets also showed a robust transition in all these correlations at faster time-scales (below ~1-year), suggesting a change in the physical mechanisms controlling rainfall (and W) variability. Based on the linear sensitivities, three simplified models were proposed to reconstruct 3-yearly tropical rainfall time-series at 5º-resolution, forced only by ERA-20CM’s prescribed SST fields. The simplified linear response models were shown to reproduce observations with similar accuracy to GCM-based products, despite having a (easily correctable) systematic bias. The good agreement between all datasets, including the simplified model, provides confidence to the representation of the tropical rainfall response to SST fluctuations in GCM-based and satellite-based products, at least at multi-year time-scales.