South American Monsoon System simulation of the last millennium: interannual to multidecadal variability and forcing mechanisms

Abstract

The South America Monsoon System (SAMS) is the dominant mode of climate variability over most of the continent, from Amazon River to the South of La Plata Basin, with summer precipitation exceeding 55 % of the annual total. Interannual to multidecadal variability of the SAMS is also related to the El Niño Southern Oscillation (Garreaud et al., 2009), the North Atlantic Oscillation (Robertson and Mechoso, 1998), to the tropical Atlantic meridional SST gradient (Zhou and Lau, 2001) and the Pacific Decadal Oscillation (Garreaud et al., 2009). In the paleoclimate time scale, SAMS precipitation variability is mainly influenced by two factors: orbital parameters variations and the meridional gradient of Atlantic SSTs (Baker and Fritz, 2015). However, in the Last Millennium volcanic eruptions, land-use change, and greenhouse gas concentrations were also external forcings to the most prominent climate anomalies in this period: the Medieval Climate Anomaly (MCA, ca. 950-1250 CE) and the Little Ice Age (LIA, ca. 1450-1850 CE). Paleoclimate proxies and climate models results (Reuter et al., 2009; Vuille et al., 2012; Rojas et al., 2016) showed a weaker monsoon during the MCA and a relatively stronger monsoon during LIA. However, these signals may differ for other regions of South America. MCA was a hot and moist period over Southeastern Brazil (Oliveira et al., 2009), while the climate over Northeast Brazil was drier for both MCA and LIA periods (Novello et al., 2012). This project aims to investigate SAMS interannual to multidecadal variability due to external forcings in the Last Millennium. Specifically, we will examine the causes of trends and variability of the SAMS using past climate simulations (CMIP5/CMIP6) and forcing experiments of the last 1000 years. We will provide a quantitative and comprehensive assessment of what aspects of the SAMS variability are adequately represented by current models, giving credibility to the future climate change projections. (AU)