Circulation Patterns and Associated Rainfall Over South Tropical South America: GCMs Evaluation During the Dry-To-Wet Transition Season

The representation of the South American Monsoon System (SAMS) by general circulation models (GCMs) is of key relevance for a better understanding of the physical rationale behind the recent climate changes over South Tropical South America (STSA) and their expected changes in a global warming scenario. During the last four decades, STSA experienced a lengthening of the dry season associated with diverse forcings. In this work, a set of 16 GCMs historical Coupled Model Intercomparison Project Phase 6 coupled simulations were evaluated during 1979-2014 in terms of how well they reproduced the atmospheric circulation over STSA through a circulation-patterns (CPs) approach. Nine CPs were first identified based on low-level winds from the ERA5 reanalysis. Focus was put on the representation of CPs during the dry-to-wet transition season (July-October). Model performance depended on the seasonal cycle and spatial structure of the CPs. GCMs adequately reproduced the different CPs, with lower skills in the transition seasons. GCMs tended to go from dry to wet conditions too quickly, evidencing deficiencies in the representation of the SAMS onset, related to a poor representation of the southerly wind intrusions to STSA and the variability of the South American low-level jet. Some GCMs were able to associate the occurrence of anomalous dry and wet years with specific CPs, suggesting well-represented physical mechanisms controlling precipitation variability. This study could identify a few GCMs that adequately simulated the CPs in STSA (among them, CESM2, CMCC-CM2-HR4 and MPI-ESM1-2-HR), which is relevant for driving high-resolution models and the analysis of future projections.

Automated summary

This study evaluates the representation of atmospheric circulation over South Tropical South America (STSA) by a set of 16 general circulation models (GCMs). The models adequately reproduce different circulation patterns, but show lower skills during the transition seasons. Some GCMs are able to associate precipitation variability with specific circulation patterns. The study identifies several GCMs that can effectively simulate the circulation patterns in STSA.