The South Atlantic dipole and variations in the characteristics of the South American Monsoon in the WCRP-CMIP3 multi-model simulations

Abstract

This study investigates relationships between Atlantic sea surface temperature (SST) and the variability of the characteristics of the South American Monsoon System (SAMS), such as the onset dates and total precipitation over central eastern Brazil. The observed onset and total summer monsoon precipitation are estimated for the period 1979-2007. SST patterns are obtained from the Empirical Orthogonal Function. It is shown that variations in SST on interannual timescales over the South Atlantic Ocean play an important role in the total summer monsoon precipitation. Negative (positive) SST anomalies over the topical South Atlantic along with positive (negative) SST anomalies over the extratropical South Atlantic are associated with early (late) onsets and wet (dry) summers over southeastern Brazil and late (early) onset and dry (wet) summers over northeastern Brazil. Simulations from Phase 3 of the World Climate Research Programme Coupled Model Intercomparison Project (CMIP-3) are assessed for the 20th century climate scenario . Most CMIP3 coupled models reproduce the main modes of variability of the South Atlantic Ocean. GFDL2.0 and MIROC-M are the models that best represent the SST variability over the South Atlantic. On the other hand, these models do not succeed in representing the relationship between SST and SAMS variability.

The South American monsoon variability over the last millennium in climate models

“…Recent studies indicate that CMIP5 simulations tend to overestimate rainfall over the Atlantic ITCZ (Yin et al, 2013) and exhibit either an east or west Atlantic bias, in association with overestimated rainfall along the African (Gulf of Guinea) or South American (Brazil) coast, respectively (Siongco et al, 2014). Such a misinterpretation of the local ITCZ has been shown to bias rainfall simulations in the core of the SAMS (Bombardi and Carvalho, 2011). A stronger Atlantic ITCZ, for example, may contribute to enhanced surface divergence over tropical South America, inducing drier conditions in the region (e.g.…”

How well can CMIP5 simulate precipitation and its controlling processes over tropical South America?

“…We take advantage of these recent improvements, as well as knowledge accumulated earlier, in determining the metrics. In particular, it has been established that SST anomalies over the adjacent tropical oceans are the primary forcing for drought and extreme events in some part of Amazonian basin (Chen et al 2011;Davidson et al 2012;Doi et al 2012;Liebmann and Marengo 2001;Moura and Shukla 1981;Bombardi and Carvalho 2011), through their impacts on atmospheric circulation patterns and moisture transport (Wang and Fu 2002;Fu et al 1999). Surface soil moisture and vegetation feedbacks, as well as land, regulate rainfall variability by altering the surface Bowen ratio and buoyancy of air in the boundary layer (Nepstad et al 1999;Malhi and Wright 2004;Fu and Li 2004;Chen et al 2011;Lee et al 2011;Toomey et al 2011).…”

How the two nodes of the tropical Atlantic sea surface temperature dipole relate the climate of the surrounding regions during austral autumn

“…Whereas, the PGRAD_TSA_EN and PGRAD_TSA cases feature a dipole‐like pattern in the South Atlantic (Figure b,d). For the first case, the secondary positive centre in the subtropical and extratropical TSA and the main negative centre in the eastern equatorial TSA form a negative South Atlantic dipole (SAD) mode (Bombardi and Carvalho, ). Meanwhile for the second case, the negative node occurs in the subequatorial central TSA and the positive one in the subtropical TSA (Figure d).…”