What is it about?

This study analyzes the year-to-year (interannual) fluctuations in global sea levels using data from the National Oceanic and Atmospheric Administration (NOAA) spanning 1993 to 2019. Specifically, the research focuses on the "residual" variability—the unpredictable ups and downs that remain after long-term trends (like global warming-induced rise) and land movements (like Glacial Isostatic Adjustment) are removed. The author used a statistical method called ARIMA (Autoregressive Integrated Moving Average) to model these fluctuations and forecast potential variability for the next 100 years.

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Why is it important?

While long-term sea level rise is a well-known threat, short-term year-to-year fluctuations are equally critical because they can trigger immediate coastal flooding and erosion. This research is important because it establishes that these short-term fluctuations are largely unpredictable (behaving like a "random walk"). By quantifying this unpredictability and providing confidence intervals for future uncertainty, the study gives coastal planners and engineers a statistical baseline to better design resilient infrastructure and emergency plans, even without precise annual predictions.

Perspectives

In conclusion, this research demonstrates that while the adjusted sea level exhibits significant annual variability, this variability is largely unpredictable using ARIMA models. This finding underscores the importance of separating the analysis of these kinds of fluctuations from the long-term sea level rise trend, which must be modeled using different approaches.

Independent Researcher & Consultant Mostafa Essam Eissa

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This page is a summary of: Statistical Characterization of Residual Interannual Fluctuations for Sea Level from ARIMA Modeling of Adjusted NOAA Data, Acta Natura et Scientia, December 2025, Prensip Publishing,
DOI: 10.61326/actanatsci.v6i2.349.
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