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To quantify the effects of land cover changes in the Amazon on local and global climate, numerical simulation experiments using the Goddard Institute for Space Studies Model II global climate model are conducted. An ensemble approach is adopted, in which a group of six control simulations is compared with a group of six deforested simulations. The deforestation effect in the Amazon is strong, with reductions in precipitation, evapotranspiration, and cloudiness. We also detect a noticeable impact in several other regions of the world, several of which show a reduction in rainy season precipitation that exhibits a high signal-to-noise ratio (determined by the t statistic). To determine the significance of the deforestation signal, we create several \'false\' ensembles, combining control and deforested members randomly, for comparison with the actual \'true\' ensemble. Such an analysis has not been used previously in deforestation studies and is useful for verifying the significance of a purported effect. The globally averaged precipitation deficits for the true ensemble are generally high in comparison with the false ensembles. Furthermore, changes in the Amazon due to the deforestation correlate significantly with remote changes in several areas. This suggests that the Amazon deforestation is producing a detectable signal throughout the Earth, and this finding underscores the importance of human activity in that region

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