Modelos preditivos para análise da variação da Altitude da Superfície do Mar utilizando leituras marégráficas

Predictive models for analyzing sea surface altitude variation using tide gauge records

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DOI:

https://doi.org/10.21680/2447-3359.2025v11n1ID38147

Abstract

Evaluating Sea Surface Altitude (SSA) is crucial for predicting the consequences that global warming may have on coastal cities, as well as for establishing a reference altimetry. Monitoring this altimetric component can be conducted through tide gauges or Satellite Altimetry (ALTSAT). The aim of this research was to analyze the readings from the tide gauge in Fortaleza, Brazil, to determine the SSA and generate predictive models for the variation of this component. Based on a five-year sample of readings, a linear regression was conducted using the statistical software R. Starting in 2020, there was a change in the measurement pattern of the readings, which significantly impacted the validation of the models. The average variation of the SSA was 1.0198 cm ± 0.2034 cm, suggesting an increase in sea surface elevation at the location.

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Author Biography

Alessandra Svonka Palmeiro, UFRRJ, Programa de Pós-Graduação em Modelagem e Evolução Geológica, Seropédica/RJ, Brasil



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Published

24-03-2025

How to Cite

MELO, Paulo Leoncio da Silva de; MUNIZ, Évelyn Monteiro; PALMEIRO, Alessandra Svonka; DEBIASI, Paula. Modelos preditivos para análise da variação da Altitude da Superfície do Mar utilizando leituras marégráficas: Predictive models for analyzing sea surface altitude variation using tide gauge records. Notheast Geoscience Journal, [S. l.], v. 11, n. 1, p. 519–526, 2025. DOI: 10.21680/2447-3359.2025v11n1ID38147. Disponível em: https://periodicos.ufrn.br/revistadoregne/article/view/38147. Acesso em: 26 aug. 2026.

Issue

Vol. 11 No. 1 (2025):

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Artigos

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