Investigating the climate predictability in the Southern Ocean using global and regional coupled models

The PARAMOUR project (Decadal Predictability and vAriability of polar climate: the Role of AtMosphere-Ocean-cryosphere mUltiscale inteRactions) is a new project funded in the framework of the Belgian program EOS - The excellence of Science. It aims at revealing fundamental drivers of climate variability and assessing the predictability in high-latitudes by using coupled regional climate models in both hemispheres. In this communication, we will present the ongoing contribution of the Earth and Life Institute in Louvain-la-Neuve (ELI, Belgium) and the Barcelona Supercomputing Center (BSC, Spain) to the PARAMOUR project, specifically in the Austral regions. The ELI and BSC efforts centre around two main objectives. The first one is improving our understanding of key processes that control the variability of the ice-ocean-atmosphere system at decadal timescales. The focus will initially be on the interactions between the components at regional scale and, later on, on the links with larger spatial scales. The second one is to determine how those interactions will lead to some predictability of the full ice-ocean-atmosphere system at decadal timescales or of some specific components only. Achieving our goals will require the development of coupled regional models including the atmosphere, ocean, sea ice and ice sheets, driven at their boundaries by the results of global models. Three configurations are proposed in the PARAMOUR project, covering 1/ Greenland, the Arctic and the North Atlantic sector, 2/ Antarctica and the Southern Ocean, 3/ The Totten glacier region. We will focus here on the latter two configurations, for the Austral regions. Retrospective (1980-2015) and prospective (2015-2045) climate simulations at high resolution will be conducted to evaluate the respective roles of initial conditions, some specific physical processes, teleconnections and couplings in the recent trends and to appreciate the potential fluctuations of key climate indicators within the next decades. A specific aspect will also be to determine the added-value of the regional models compared to the global ones.