Coupled regional climate simulations of the future precipitation climate of the Central Andes

The meridional extent and complex orography of the South American continent helps promote a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. Global climate models have been a main stay of climate research, but their spatial and temporal resolution makes them inadequate for fully-resolving the strong climatic and complex orography that defines the Tropical Andes. Recent computational advances now make possible the application of high-resolution, prognostic mesoscale coupled modelling systems, such as the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system for climate studies. Previous work has shown COAWST to reasonably simulate the entire 2003-2004 South American wet season (Dec-Feb) when validated against both satellite and model analysis data. More recently, COAWST simulations have also been shown to sensibly reproduce the entire annual rainfall cycle (Oct 2003 – Oct 2004) over South America when applying historical climate model input for both model initialization and boundary conditions.

Using future atmospheric and oceanic global climate model output as input for COAWST, the present work will investigate changes to the overall precipitation climate (spatial distribution, precipitation rates, and diurnal cycle) of the Central Andes in response to predicted climatic change. This work entails the completion of year-long, atmosphere-ocean coupled COAWST simulations, spanning October to October, for the years 2031, 2059, and 2087 assuming the most likely regional climate pathway (RCP): RCP 6.0. Results will be based upon these yearly “snapshots” and global climate model output for all years in between. Initial results show little change to precipitation coverage or its diurnal cycle, however precipitation amounts did tend to be drier over the Brazilian Plateau and wetter over the Western Amazon and Central Andes. These results suggest potential adjustments to large-scale climate features, such as the Bolivian High.