Robust Amazon precipitation projections in climate models that capture land-atmosphere feedbacks

Abstract:

Land-atmosphere interactions have an important influence on Amazon precipitation (P), but evaluation of these processes in climate models has so far been limited. We analysed relationships between Amazon P and evapotranspiration (ET) in CMIP5 models to evaluate controls on surface moisture fluxes and assess the credibility of regional P projections. We found that only 13 out of 38 models captured an energy limitation on Amazon ET, in agreement with observations, while 20 models instead showed Amazon ET is limited by water availability. Soil depth was identified as a key factor affecting model representation of Amazon ET controls. Land-atmosphere feedbacks were also shown to play an important role in modelled climate change, with large future changes in Amazon P suppressed in models that simulated the right energy-limited control on ET over the historical period through a ‘buffering’ feedback mechanism. By discounting projections from models that simulated unrealistic feedbacks, our analysis halved uncertainty in the basin-wide future P change, while revealing end-of-century P reductions over the eastern Amazon and in the dry season that were comparable to the P anomalies observed during recent major Amazon droughts, which caused widespread tree mortality (i.e. <50 %). Finally, we showed that factors controlling Amazon ET evolve over time in realistic models, destabilising the land-atmosphere feedback mechanism. These results substantially reduce the uncertainty in Amazon P projections, and highlight the vulnerability of the Amazon under an extreme warming scenario.