Coupled model intercomparison project phase 6 (CMIP6) high resolution model intercomparison project (HighResMIP) bias in extreme rainfall drives underestimation of amazonian precipitation

Negron-Juarez, Robinson; Wehner, Michael; Silva Dias, Maria Assunção F.; Ullrich, Paul; Chambers, Jeffrey Q.; Riley, William J.

doi:10.1088/2515-7620/ad6ff9

Title: Coupled model intercomparison project phase 6 (CMIP6) high resolution model intercomparison project (HighResMIP) bias in extreme rainfall drives underestimation of amazonian precipitation

Journal Article · 02 September 2024 · Environmental Research Communications

DOI: https://doi.org/10.1088/2515-7620/ad6ff9 · OSTI ID:2439297

;

; Silva Dias, Maria Assunção F.; Ullrich, Paul; Chambers, Jeffrey Q.;

Abstract Extreme rainfall events drive the amount and spatial distribution of rainfall in the Amazon and are a key driver of forest dynamics across the basin. This study investigates how the 3-hourly predictions in the High Resolution Model Intercomparison Project (HighResMIP, a component of the recent Coupled Model Intercomparison Project, CMIP6) represent extreme rainfall events at annual, seasonal, and sub-daily time scales. TRMM 3B42 (Tropical Rainfall Measuring Mission) 3 h data were used as observations. Our results showed that eleven out of seventeen HighResMIP models showed the observed association between rainfall and number of extreme events at the annual and seasonal scales. Two models captured the spatial pattern of number of extreme events at the seasonal and annual scales better (higher correlation) than the other models. None of the models captured the sub-daily timing of extreme rainfall, though some reproduced daily totals. Our results suggest that higher model resolution is a crucial factor for capturing extreme rainfall events in the Amazon, but it might not be the sole factor. Improving the representation of Amazon extreme rainfall events in HighResMIP models can help reduce model rainfall biases and uncertainties and enable more reliable assessments of the water cycle and forest dynamics in the Amazon.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: NONE; AC52-07NA27344; AC02-05CH11231

OSTI ID:: 2439297

Journal Information:: Environmental Research Communications, Journal Name: Environmental Research Communications Journal Issue: 9 Vol. 6; ISSN 2515-7620

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United States

Language:: English

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