Dynamically downscaled coastal flooding in Brazil’s Guanabara Bay under a future climate change scenario

Raquel Toste (), Adriano Vasconcelos (), Luiz Paulo de Freitas Assad () and Luiz Landau ()
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Raquel Toste: Federal University of Rio de Janeiro
Adriano Vasconcelos: Federal University of Rio de Janeiro
Luiz Paulo de Freitas Assad: Federal University of Rio de Janeiro
Luiz Landau: Federal University of Rio de Janeiro

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 8, No 35, 7845-7869

Abstract: Abstract In recent years, extensive research has been conducted on various aspects of climate change, with particular attention given to the sea level rise (SLR) as a significant consequence of global warming. Although a general trend of positive SLR exists worldwide, regional variations in SLR rates are observed. This study aims to investigate the potential impact of SLR projected by a Coupled Model Intercomparison Project phase 5 model, under a 4.5 W m $$^{-2}$$ - 2 radiative forcing stabilization scenario by 2100, on coastal flooding along the Brazilian Coast. To achieve this, an ocean numerical downscaling approach was employed using multiple nested grids with the Regional Ocean Modeling System, with a specific focus on the Guanabara Bay region. Guanabara Bay is a vital water body that receives substantial water discharges from the densely populated Rio de Janeiro metropolitan area. Two experiments were conducted simulating the present (1995–2005) and future conditions (2090–2100), and the projected changes were evaluated. The results reveal a projected SLR of 0.69 m at Fiscal Island by the end of the century, anticipating potential loss of remaining mangrove areas and the expansion and persistence of coastal flooding in important tourist destinations within the Rio de Janeiro Municipality. Overall, this study provides valuable insights into the potential impacts of SLR on coastal flooding in the Brazilian Coast, emphasizing the importance of considering regional variations in SLR rates for effective coastal management and adaptation strategies.

Keywords: Climate change; Coastal flooding; Ocean modeling; CMIP5; ROMS (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11069-024-06556-7

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