<b>Tropical Atlantic Hydroclimatic Extremes in the past 1,500 years</b>

• Ano de defesa: 2025
• Autor(a) principal: Júnior, Paulo Sergio da Silva
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertacoes da USP; Universidade de São Paulo; Instituto Oceanográfico
• Palavras-chave em Português: Atlântico Tropical; Seca; Eventos extremos; Past2k; Grande conjunto de simulações; Large ensemble; Extreme events; Drought; Tropical Atlantic
• Link de acesso: https://teses.usp.br/teses/disponiveis/21/21135/tde-07042026-145816/

Extreme hydroclimatic events have profound socio-economic and environmental consequences, and are expected to increase in both frequency and severity as the planet warms. Northeast Brazil and the Sahel are particularly vulnerable due to their semi-arid climate and reliance on rain-fed agriculture. In this context, it is critical to distinguish the role of internal climate variability, which dominated before the industrial era, from that of external anthropogenic forcing to understand to what extent recent and future events deviate from natural climatic variability. Here, we use a large ensemble of simulations of the past 1,500 years from the IPSL-CM6ALR model to investigate hydroclimatic extremes in the Tropical Atlantic region in the past and how their frequency, duration, and magnitude compare to present and future extremes under the SSP2-4.5 shared socioeconomic pathway scenario. We show that before the 20th century precipitation variability was dominated by internal variability and episodic volcanic forcing and that since the mid-20th century, the anthropogenic forcing has emerged as the leading mode of precipitation-sea surface temperature variability, with increased dry extremes over Northeast Brazil and wet extremes in the Sahel. We find that these changes are not solely a consequence of a shifting mean state, but also reflect alterations in the distribution of extremes. These results highlight the need to redefine baselines for extreme events as the planet continues to warm to better inform adaptation strategies in a climate moving beyond preindustrial variability.