Gross Discrepancies between Observed and Simulated Twentieth-to-Twenty-First-Century Precipitation Trends in Southeastern South America

Abstract

AbstractSoutheastern South America (SESA; encompassing Paraguay, southern Brazil, Uruguay, and northern Argentina) experienced a 27% increase in austral summer precipitation from 1902 to 2019, one of the largest observed trends in seasonal precipitation globally. Previous research identifies Atlantic multidecadal variability and anthropogenic forcing from stratospheric ozone depletion and greenhouse gas emissions as key factors contributing to the positive precipitation trends in SESA. We analyze multimodel ensemble simulations from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP) and find that not only do Earth system models simulate positive SESA precipitation trends that are much weaker over the historical interval, but some models persistently simulate negative SESA precipitation trends under historical forcings. Similarly, 16-member ensembles from two atmospheric models forced with observed historical sea surface temperatures never simulate precipitation trends that even reach the lower bound of the observed trend’s range of uncertainty. Moreover, while future twenty-first-century projections from CMIP6 yield positive ensemble mean precipitation trends over SESA that grow with increasing greenhouse gas emissions, the mean forced response never exceeds the observed historical trend. Preindustrial control runs from CMIP6 indicate that some models do occasionally simulate centennial-scale trends in SESA that fall within the observational range, but most models do not. Results point to significant uncertainties in the attribution of anthropogenically forced influences on the observed increases in precipitation over SESA while also suggesting that internal decadal-to-centennial variability of unknown origin and not present in state-of-the-art models may have also played a large role in generating the twentieth-to-twenty-first-century SESA precipitation trend.