2021
DOI: 10.1002/cli2.27
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Assessing the representation of South American monsoon features in Brazil and U.K. climate model simulations

Abstract: This paper assesses how well the CPTEC/INPE Brazilian Global Atmospheric Model (BAM-1.2) and the atmospheric component of the UK Met Office Hadley Centre Global Environment Model (HadGEM3-GC3.1) represent the main South American monsoon features. Climatological (1981Climatological ( -2010 ensemble means of Atmospheric Model Intercomparison Project (AMIP)-type climate simulations are evaluated. The assessment evaluated the models' ability to represent the South America austral summer and winter precipitation co… Show more

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Cited by 16 publications
(27 citation statements)
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References 50 publications
(85 reference statements)
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“…The realistic representation of South American climate features remains a challenge for numerical models [15,[68][69][70][71][72][73][74][75]. Global climate models (GCMs) reproduce and predict the main characteristics of precipitation, temperature, and circulation over the continent.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…The realistic representation of South American climate features remains a challenge for numerical models [15,[68][69][70][71][72][73][74][75]. Global climate models (GCMs) reproduce and predict the main characteristics of precipitation, temperature, and circulation over the continent.…”
Section: Introductionmentioning
confidence: 99%
“…Global climate models (GCMs) reproduce and predict the main characteristics of precipitation, temperature, and circulation over the continent. Nevertheless, they fail in simulating regional climate over terrains with a complex topography and still show systematic rainfall biases in regions such as tropical SA, Andes, and La Plata Basin (LPB) [15,[68][69][70][71][72][73][74][75]. In the SACZ region, limitations persist since summer rain predictability over the SACZ area is lower over the continent than in the ocean [76,77].…”
Section: Introductionmentioning
confidence: 99%
“…Much of the summer rainfall in subtropical Brazil comes from tropical regions transported Southward through cloud bands (Zilli and Hart, 2021). Understanding these dynamics enables more robust evaluation of models' dynamical fields (Coelho et al, 2022), and improved understanding of the dynamics of past drought events (Paulo et al, 2021). Ongoing research is looking at how to expand seasonal scale predictions tailored to end users such as the agricultural sector's requirement to know about dry spells and heatwaves.…”
Section: Understanding Climate Changementioning
confidence: 99%
“…Many of the impacts being felt in Brazil are related to rainfall, and so the modelling focus in CSSP Brazil has been on rainfall processes to understand near-term (seasonal) predictability as well as long-term changes. Coelho et al (2022) present an overview of seasonal and subseasonal rainfall modelling and how this has advanced bringing improved capability for early warnings. Much of the summer rainfall in subtropical Brazil comes from tropical regions transported Southward through cloud bands (Zilli and Hart, 2021).…”
Section: Understanding Climate Changementioning
confidence: 99%
“…The monsoon is one of the most important phenomena in terms of both scientific and societal interests, as a large portion of the world's population lives in regions affected by monsoon climate features. In a second climate-related CSSP-Brazil study, Coelho et al (2021b) assessed the representation of South American Monsoon features in simulations produced with the Brazilian (Coelho et al, 2021a) and UK (Ridley et al, 2018;Williams et al, 2018) global climate models. The assessment evaluated the models' ability to represent major climate features, such as the South American summer and winter precipitation contrast and associated atmospheric circulation, key elements of the South American monsoon system during spring and summer, and the climatological distributions of rainy season onset and demise dates over the core South American monsoon region.…”
mentioning
confidence: 99%