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We show a recent increasing trend in Vapor Pressure Deficit (VPD) over tropical South America in dry months with values well beyond the range of trends due to natural variability of the climate system defined in both the undisturbed Preindustrial climate and the climate over 850–1850 perturbed with natural external forcing. This trend is systematic in the southeast Amazon but driven by episodic droughts (2005, 2010, 2015) in the northwest, with the highest recoded VPD since 1979 for the 2015 drought. The univariant detection analysis shows that the observed increase in VPD cannot be explained by greenhouse-gas-induced (GHG) radiative warming alone. The bivariate attribution analysis demonstrates that forcing by elevated GHG levels and biomass burning aerosols are attributed as key causes for the observed VPD increase. We further show that There is a negative trend in evaporative fraction in the southeast Amazon, where lack of atmospheric moisture, reduced precipitation together with higher incoming solar radiation (~7% decade⁻¹cloud-cover reduction) influences the partitioning of surface energy fluxes towards less evapotranspiration. The VPD increase combined with the decrease in evaporative fraction are the first indications of positive climate feedback mechanisms, which we show that will continue and intensify in the course of unfolding anthropogenic climate change.

Key spatiotemporal patterns of monthly scale temperature variability are characterized over southern South America usingk‐means clustering. The resulting clusters reveal patterns of temperature variability, referred to as temperature variability states. Analysis is performed over summer and winter months separately using data covering the period 1980–2015. Results for both seasons show four primary temperature variability states. In both seasons, one state is primarily characterized by warm temperature anomalies across the domain while another is characterized by cold anomalies. The other two patterns tend to be characterized by a warm north–cold south and cold north–warm south feature. This suggests two primary modes of temperature variability over the region. Composites of synoptic‐scale meteorological patterns (wind, geopotential height, and moisture fields) are computed for months assigned to each cluster to diagnose the driving meteorology associated with these variability states. Results suggest that low‐level temperature advection promoted by anomalies in atmospheric circulation patterns is a key process for driving these variability states. Moisture‐related processes also are shown to play a role, especially in summer. The El Niño–Southern Oscillation and the Southern Annular Mode exhibit some relationship with temperature variability state frequency, with some states more common during amplified phases of these two modes than others. However, the climate modes are not a primary driver of the temperature variability states.