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This study examines the uncertainties and the representations of anomalies of a set of evapotranspiration products over climatologically distinct regions of South America. The products, coming from land surface models, reanalysis, and remote sensing, are chosen from sources that are readily available to the community of users. The results show that the spatial patterns of maximum uncertainty differ among metrics, with dry regions showing maximum relative uncertainties of annual mean evapotranspiration, while energy‐limited regions present maximum uncertainties in the representation of the annual cycle and monsoon regions in the representation of anomalous conditions. Furthermore, it is found that land surface models driven by observed atmospheric fields detect meteorological and agricultural droughts in dry regions unequivocally. The remote sensing products employed do not distinguish all agricultural droughts and this could be attributed to the forcing net radiation. The study also highlights important characteristics of individual data sets and recommends users to include assessments of sensitivity to evapotranspiration data sets in their studies, depending on region and nature of study to be conducted.

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Southeastern South America (SESA) is found to be the main hot spot of soil moisture-evapotranspiration coupling of South America during a dry summer. However, only its eastern part is a soil moisture-precipitation hot spot. Pathways between soil moisture and precipitation are evaluated through studying the coupling of soil moisture with surface and boundary layer variables. The outcome suggests that both the moist static energy and its vertical gradient are important for the development of precipitation, as a result of the total surface heat fluxes that are affected by soil moisture only in the eastern part of SESA.

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Southeastern South America has been identified as a hot spot of soil moisture and evapotranspiration coupling efficiency during austral summer in a previous study. Here, hydrological processes such as coupling and memory of soil moisture, evapotranspiration and precipitation and the links between these variables are discussed on the daily time scale over this region. The correlations between surface variables, rainfall persistence and soil moisture memory are discussed over three subregions selected on basis of their coupling efficiency and mean daily intensity of precipitation. The relationship between surface climate and land cover is qualitatively assessed. The memory, or statistical persistence, is longer and has a more robust spatial pattern for the root zone than for the top soil moisture. Where the coupling efficiency between soil moisture and evapotranspiration is high, the evapotranspiration is regulated by soil moisture conditions independently on the intensity of precipitation, whereas in a region with low coupling efficiency and high intensity, the evapotranspiration is regulated by the atmosphere. The coupling efficiency is in general related to the memory of the root‐zone layer, since the soil state is modified when the soil moisture and the atmosphere interact, resulting in an anticorrelation between these metrics. The persistence of rainfall is another factor that modulates the memory. Nevertheless, there are some areas around the La Plata River where both the coupling efficiency and the memory are relatively high, such as Uruguay and the northeast of Argentina, where an improvement of soil moisture initial conditions could improve predictability of surface variables on a monthly timescale.

The land-atmosphere interaction for reference and future climate is estimated with a regional climate model ensemble. In reference climate, more than 50% of the models show interaction in southeastern South America during austral spring, summer and autumn. In future climate, the region remains a strong hotspot although somewhat weakened due to the wet response that enhance energy limitation on the evapotranspiration. The region of the Brazilian Highlands and Matto Grosso appears as a new extensive hotspot during austral spring. This is related to a dry response which is probably accentuated by land surface feedbacks.