The temporal evolution of the global mean sea level (GMSL) has been recently studied. This study was performed by using monthly mean averages derived from two distinct datasets: a reconstructed timeseries and a satellite altimeter timeseries. To examine the scaling characteristics of the dataset employed two established methodologies: detrended fluctuation analysis (DFA) and multifractal DFA (MF-DFA). The key finding of this study was that both timeseries of the global average sea level exhibit power-law long-range correlations as well as multifractality. Interestingly, the scaling features of the 134-year and the most recent 28-year GMSL-dataset were remarkably found similar, indicating that the long-range correlations may primarily arise from factors of nature. This highlighted the need for further extensive research on the association among the fluctuations of climate change and sea-level, as their indirect processes have significant implications for ecology and conservation.