The Ability of CMIP6 Models to Simulate 34-years of precipitation over the Brazilian Amazon

• DOI: 10.1002/essoar.10509477.2
• Publication Date: 2021-12-14T17:07:24Z
• Authors: Corrie Monteverde
• Keywords: Empirical orthogonal functions; Dry season; Wet season; Water cycle; Annual cycle

The Brazilian Amazon provides important hydrological cycle functions, including precipitation regimes that bring water tothe people and environment are critical to moisture recycling transport, represents an variable forclimate models simulate accurately. This paper evaluates the performance of 13 Coupled Model Intercomparison Projectphase 6 (CMIP6) models. is done by discussing results from spatial pattern mapping, Taylor diagram analysis Taylorskill score, annual climatology comparison, Empirical Orthogonal Function (EOF) analysis. Precipitation shows1) region displays a more uniform distribution with higher rainfall in north-northwest anddrier conditions south. Models tend underestimate northern values or overestimate central northwest averages.2) Southern has defined dry season (June, July, August) wet (December, January, andFebruary) able this well. Northern tends occur August, September, andOctober occurs March, April, May, not capture as well.Models produce too much at start either over- under-estimate dryseason, although ensemble means typically display overall precisely. 3) EOF tocapture dominant mode variability, which was SAMS. 4) When all evaluation metrics taken intoaccount perform best CESM2, MIROC6, MRIESM20, SAM0UNICON, mean. Thispaper supports research determining most up date CMIP6 model regime for 1981-2014for Amazon. Results will aid understanding future projections selected subset ofglobal climate allow scientists construct reliable ensembles, plays role many sectorsof economy, ecosystem, agriculture, energy, security.