Robust Amazon precipitation projections in climate models that capture realistic land–atmosphere interactions

Autor: John H. Marsham, Caio A. S. Coelho, Paulo Yoshio Kubota, Jessica C. A. Baker, D. Castilho de Souza, Dominick V. Spracklen, Luis Garcia-Carreras, Manuel Gloor, Wolfgang Buermann
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Baker, J C A, Garcia-Carreras, L, Buermann, W, Souza, D C D, Marsham, J H, Kubota, P Y, Gloor, M, Coelho, C A S & Spracklen, D V 2021, ' Robust Amazon precipitation projections in climate models that capture realistic land–atmosphere interactions ', Environmental Research Letters, vol. 16, no. 7, 074002 . https://doi.org/10.1088/1748-9326/abfb2e
ISSN: 1748-9326
Popis: 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 the 5th Coupled Model Intercomparison Project 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. Models that misrepresented controls on ET over the historical period projected both large increases and decreases in Amazon P by 2100, likely amplified by unrealistic land–atmosphere interactions. In contrast, large future changes in annual and seasonal-scale Amazon P were suppressed in models that simulated realistic controls on ET, due to modulating land–atmosphere interactions. By discounting projections from models that simulated unrealistic ET controls, our analysis halved uncertainty in basin-wide future P change. The ensemble mean of plausible models showed a robust drying signal over the eastern Amazon and in the dry season, and P increases in the west. Finally, we showed that factors controlling Amazon ET evolve over time in realistic models, reducing climate stability and leaving the region vulnerable to further change.
Databáze: OpenAIRE