High-resolution chronological model for reconstructing climate variations in the Equatorial Atlantic during the last glacial-interglacial cycle

• Grant number: 24/23156-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: March 01, 2025
• End date: December 31, 2025
• Field of knowledge: Physical Sciences and Mathematics - Oceanography - Geological Oceanography
• Principal Investigator: Thiago Pereira dos Santos
• Grantee: Lara Valotto Silva
• Host Institution: Escola de Artes, Ciências e Humanidades (EACH). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 18/15123-4 - Past perspectives on tipping elements of the climate system: the Amazon Rainforest and the Atlantic Meridional Overturning Circulation (PPTEAM), AP.PFPMCG.JP2

Abstract

This Scientific Initiation project seeks to establish a robust chronological model for two complementary marine sediment cores, MD23-3652Q and MD23-3653, retrieved from the equatorial Atlantic during the Franco-Brazilian scientific expedition AMARYLLIS-AMAGAS II. As these cores extend beyond the radiocarbon dating limit (~50,000 years), the age model will be constructed using epibenthic foraminifera oxygen isotope (d18O) stratigraphy. Preliminary d18O data from core MD23-3652Q demonstrate a correlation with the global reference curve LR04, indicating a temporal coverage of approximately 60,000 years. However, current analyses at a 10 cm resolution lack the detail required to capture rapid transitions, such as the penultimate glacial-interglacial transition (ca. 140,000 to 128,000 years ago). To improve the precision of the age model and its alignment with the reference curve, this project will generate a high-resolution d18O record (at 5 cm intervals) for periods of low sedimentation, including the penultimate glacial-interglacial transition and the Last Interglacial (ca. 128.000 - 115.000 years). This improvement is critical for reducing chronological uncertainties and advancing the understanding of past climate variability.