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Abstract This study investigates the potential effects of historical deforestation in South America using a regional climate model driven with reanalysis data. Two different sources of data were used to quantify deforestation during the 1980s to 2010s, leading to two scenarios of forest loss: smaller but spatially continuous in scenario 1 and larger but spatially scattered in scenario 2. The model simulates a generally warmer and drier local climate following deforestation. Vegetation canopy becomes warmer due to reduced canopy evapotranspiration, and ground becomes warmer due to more radiation reaching the ground. The warming signal for surface air is weaker than for ground and vegetation, likely due to reduced surface roughness suppressing the sensible heat flux. For surface air over deforested areas, the warming signal is stronger for the nighttime minimum temperature and weaker or even becomes a cooling signal for the daytime maximum temperature, due to the strong radiative effects of albedo at midday, which reduces the diurnal amplitude of temperature. The drying signals over deforested areas include lower atmospheric humidity, less precipitation, and drier soil. The model identifies the La Plata basin as a region remotely influenced by deforestation, where a simulated increase of precipitation leads to wetter soil, higher ET, and a strong surface cooling. Over both deforested and remote areas, the deforestation-induced surface climate changes are much stronger in scenario 2 than scenario 1; coarse-resolution data and models (such as in scenario 1) cannot represent the detailed spatial structure of deforestation and underestimate its impact on local and regional climates. 

South America, especially the Amazon region, is considered a hotspot of biosphere–atmosphere interactions and presents a unique challenge for regional climate modeling. Here, we evaluate the performance of a regional model in simulating the climate–vegetation system in South America and use the model to investigate the potential role of large‐scale warming in the recently observed trend of hydroclimate and vegetation. Compared with prescribing vegetation based on observational data, adding the predictive vegetation capacity to the regional climate model enabled the model to simulate the vegetation response to climate while sustaining the model performance in reproducing the mean, variability and extremes of the regional climate. The coupled vegetation–climate model captures the recent trends in hydroclimate and vegetation productivity and their spatial contrasts, including a trend toward warmer, drier, and less productive conditions in the Amazon and Nordeste regions and a trend toward cooler, wetter, and more productive condition in the La Plata region. Results from sensitivity experiment driven by detrended boundary forcing for the regional climate suggest that much of the trends in the Amazon and Nordeste regions can be attributed to the effects of large‐scale warming, but contribution from decadal variability also plays a role especially for the most recent decade. However, the trend in the La Plata region cannot be attenuated by the removal of the boundary forcing trend, indicating the role of large‐scale circulation pattern changes. The recent trends in vegetation productivity may be early manifestation of future changes in the Amazon and surrounding regions.