B1680
Title: Analyzing sea level fluctuations and breakpoints: A statistical approach in support of sustainable development goal 14
Authors: Ana Borges - CIICESI, ESTG, Politécnico do Porto (Portugal) [presenting]
Clara Cordeiro - DM-FCT, Universidade do Algarve and CEAUL (Portugal)
M Rosario Ramos - FCiencias.ID (Portugal)
Abstract: The purpose is to employ a statistical methodology to detect irregularities in time series data concerning sea level patterns, aiming to better understand sea level fluctuations, a prominent consequence of climate change. This aligns with the United Nations' 14th sustainable development goal (SDG): the conservation and sustainable utilization of oceans, seas, and marine resources. It is essential to proactively anticipate and prepare for these changes to develop effective strategies for addressing this urgent environmental issue. This analytical approach integrates various techniques tailored for analyzing time series data related to water consumption. The initial step involves decomposing the time series using the seasonal-trend decomposition based on the Loess method. Subsequently, a breakpoint analysis is performed on the seasonally adjusted time series to identify shifts in the pattern's evolution. Following this, the Mann-Kendall test and Sen's slope estimator are applied to assess the presence of significant sea level increases or decreases. Implementing this strategy on sea level data has yielded positive outcomes, successfully identifying breakpoints associated with notable upward or downward trends.
