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Divergent Representation of Precipitation Recycling in the Amazon and the Congo in CMIP6 Models.

Jessica C A BakerD V Spracklen
Published in: Geophysical research letters (2022)
Moisture evaporated from the land contributing to precipitation in a given area is known as precipitation recycling and needs to be accurately represented in climate models. The Amazon and Congo basins are reported to have the highest precipitation recycling rates globally, but model representation has not yet been assessed over these regions. We evaluated recycling over the Amazon and Congo in 45 Coupled Model Intercomparison Project Phase 6 models. Regional annual means from models and reanalyzes agreed well over both basins. Models captured seasonal variation in recycling over the Congo but there was a large-scale underestimation of recycling during the Amazon dry-to-wet transition season relative to ERA5, caused by models underestimating Amazon evapotranspiration and overestimating incoming wind speed and associated water vapor imports. Both regions show robust declines in precipitation recycling over the next century under future climate-change scenarios. Our results suggest models may underestimate impacts of deforestation on regional precipitation in the Amazon.
Keyphrases
  • climate change
  • neural network