Influence of Elevated Andes Topography on South American Precipitation Biases

General circulation models (GCMs) exhibit systemic precipitation biases over much of South America during its wet season (December to March), undermining their utility in projecting future mean and extreme precipitation shifts and Amazon carbon cycle feedbacks in response to rising greenhouse gases. Though these biases, including a dry bias over the Amazon, have persisted across generations of model development, their origins are an ongoing topic of debate. Here, we explore whether the underestimation of Andes peak heights—and thus their orographic blocking effect—due to overly-smooth resolved topographic boundary conditions in GCMs underlies the biases. We performed a suite of idealized experiments forced by elevated topography over the Andes (and Central America) to better capture orographic blocking with the NASA GISS ModelE version 2.1 (E2.1) and 3 (E3). In the E2.1 experiments conducted with a fully-coupled atmosphere-ocean, we find precipitation over the central Amazon and South Atlantic Convergence Zone (SACZ) is increased relative to a control simulation forced with the default topography, reflecting a reduction of the model’s precipitation biases in these regions. The former results from enhanced blocking of low-level tropical easterly winds and thus moisture convergence east of the mountains, while the latter is driven by shifting stationary wave patterns that enhance moisture convergence in the SACZ. Yet, the wet bias in the eastern Amazon is worsened in the elevated topography experiment due to an intensification of the ITCZ bias in the southern tropical Atlantic. Analysis of analogous experiments run with E2.1 and E3 in atmosphere-only mode and prescribed sea surface temperatures reveals that the high pressure stationary wave pattern generated in the south Atlantic relied on coupled atmosphere-ocean mechanisms. Coupled processes are shown to be important to generating stationary wave patterns arising from orographic blocking and sea surface temperature interactions, enhancing moisture convergence and thus reducing model biases over the central Amazon and SACZ, though this is balanced by increased model biases influenced by the ITCZ.