Divergent Representation of Precipitation Recycling in the Amazon and the Congo in CMIP6 Models. Issue 10 (13th May 2022)

• Record Type: Journal Article
• Authors: Baker, J. C. A.; Spracklen, D. V.
• Is Part Of: Geophysical research letters. Volume 49:Issue 10(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-13
• Subjects: land‐atmosphere interactions -- model evaluation -- tropical forest -- deforestation -- hydrological cycle -- land‐use change; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2021GL095136
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: 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. Plain Language Summary: In the Amazon and Congo basins, much of the rain that falls to Earth is transferred back to the atmosphere through evaporation over tropical forests, providing essential moisture for further rainfall events downwind. This process of rainfall recycling, which is vital for sustaining the rainforest, is disrupted when forest is cut down. For researchers to understand how deforestation in the Amazon and Congo might impact the climate it is vital that climate models accurately represent the fraction of rain coming from recycled moisture. Our study found that models represented rainfall recycling relatively well in the Congo, but underestimate recycling in the Amazon dry‐to‐wet transition season. This is important because it could mean these models underpredict the influence of deforestation on climate in the Amazon. Key Points: This study quantifies, for the first time, precipitation recycling ratios over the Amazon and Congo Basins in Coupled Model Intercomparison Project Phase 6 models Seasonal recycling is well represented in the Congo but there is a large‐scale underestimation in the Amazon dry‐to‐wet transition season These findings have implications for model representation of land‐use change impacts in the Amazon