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Título del libro: Proceedings Of Spie - The International Society For Optical Engineering
Título del capítulo: El Niño-Southern Oscillation (ENSO) 2022-2024 in the ocean and coast of the Central Mexican Pacific

Autores UNAM:
ALEJANDRA AURELIA LOPEZ CALOCA; MARIA ADELA MONREAL GOMEZ;

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Autores externos:

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Idioma:

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Año de publicación:
2025

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Palabras clave:

Coastal change; Coastline; El Nino southern oscillation; Mexican pacific sentinel; Oceanographic campaign; Oscillation phasis; Sea surfaces; Surface temperatures; Synthetic aperture radar; Work-flows

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Resumen:

© 2025 COPYRIGHT SPIE.The El Niño-Southern Oscillation (ENSO) stands out among climate phenomena due to its intensity, predictability, and global reach. However, despite decades of study, its impact on sandy coastlines in the Pacific remain insufficiently explored. This study investigates the 2022-2024 ENSO event and its influence on coastal changes in the central Mexican Pacific, specifically in the state of Sinaloa, Mexico. The analysis focuses on sandy coasts with three types of covers and nearby land use. Three coastal transects were studied: urban, agricultural, and low-disturbance, and an oceanic subtransect near the Mazatlán shoreline, composed of five stations of an oceanographic campaign. To characterize the ENSO signal in the ocean, we used 30-year climatological averages derived from historical satellite data obtained from the Copernicus Marine Service. The selected variables include sea surface temperature (SST), surface geostrophic currents and surface wind. A comprehensive database was constructed using level-4 satellite products and validated with in situ measurements collected during the 2023-2024 ENSO oceanographic campaign aboard the R/V El Puma (UNAM). While oceanographic analysis provides essential context, the study's contribution to coastal change analysis lies in the use of SENTINEL-1A level-1 satellite imagery from 2022 to 2024. This temporal window encompasses the neutral, La Niña (cold), and El Niño (warm) ENSO phases. To address computational constraints, an automated processing workflow was developed using the ESA-SNAP Python API. The workflow integrated GLCM texture metrics, edge-detection thresholding algorithms to enhance image binarization, and the Digital Shoreline Analysis System (DSAS) to track shoreline positional changes over time. The methodology was validated using high-resolution PlanetScope imagery. satellite observations were aligned with data obtained from the oceanographic campaign, with SST showing a mean error of - 0.6 °C Coastal accretion was detected during the warm ENSO phase in 2023-2024, particularly in summer and autumn, corresponding to elevated SST anomalies. In contrast, shoreline retreat dominated during the cold phase in 2022-2023, especially in winter and spring, highlighting that in Mazatlán ENSO's impacts on coastal dynamics diverge from regional patterns and may be strongly modulated by local processes.

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Entidades citadas de la UNAM:

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Fuente:



ISBN:
9781510692718
Editorial:
SPIE

Tipo de producto:
Conference Paper

DOI:
10.1117/12.3069991