Detection and attribution of precipitation trends associated with the poleward shift of the South Atlantic Convergence Zone using CMIP5 simulations

다국어 초록 (Multilingual Abstract)

Observational studies demonstrate a poleward shift in the South Atlantic Convergence Zone (SACZ) in recent decades with regional impacts on extreme precipitation. However, the relative contribution of anthropogenic forcing and natural variability to the observed trends is presently unknown. To evaluate the main forcings associated with the recent trends in precipitation rate consistent with the poleward shift of the SACZ, this study examines the last 40 years of the historical scenario of 20 global climate models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The relative contribution of natural variability and anthropogenic‐related forcings to precipitation in the 20th century is assessed based on historical, natural, anthropogenic, and pre‐industrial simulations from CMIP5 models. Over the study area, precipitation trends simulated by the CMIP5 historical scenario are small, with large disagreement among models and members. Despite the small magnitude of the trends, the spatial pattern emerging is coherent with a poleward displacement of the SACZ, as indicated by a reduction (increase) in the precipitation rate over Southeastern Brazil (Southeastern South America). Even with large discrepancies among models, the attribution analysis suggests that precipitation trends could partially result from land‐use change, followed by changes in ozone concentrations, with more significant influence over Southeastern Brazil. The large uncertainty in the simulated precipitation suggests that not all mechanisms related to the position and intensity of the SACZ events are well captured by the CMIP5 models considered here.
Trends in precipitation rate spatially averaged over Southeastern Brazil (top) and Southeastern South America (bottom). Comparison between trends observed in GPCP and simulated by the multi‐model mean (bars) and the multi‐member mean of each model (dots), considering historical, natural, greenhouse gas, anthropogenic aerosol, ozone, and land‐use change scenarios. Despite large uncertainties, the attribution analysis indicates the dominant influence of anthropogenic forcings, especially changes in land use, on simulated precipitation trends.