## Materials and Methods  
Two regressions are usually applied to the measured monthly average mean sea levels (MSL) of a tide gauge record to compute the sea level rate of rise and the acceleration. A linear regression:  
\[y(x)=B+M\cdot x,\]  
returns the sea level rate of rise as the slope \(M\). \(A\) quadratic regression:  
\[y(x)=B^{\prime}+M^{\prime}\cdot x+A\cdot x^{2},\]  
returns the acceleration as twice the second-order coefficient \(2\cdot A\). These computations are not reliable if the tide gauge record is segmented.  
While the issue of different sea and land contributions moving from one tide gauge location to the other, or other biases to the tide gauge results originating from malfunctioning of the instrument or measurement errors, could not be addressed, there was the opportunity to verify if the alignments of the different segments satisfied some conditions, such as breakpoint alignments assuming a known pattern--for example, linear--across the segments, and extrapolate the values at the interface from both sides [2; 3; 21]. Regarding breakpoints detection in oceanic environmental variables, the reader is also referred to [22]. If there are \(n\) segments, the segmented time series is given as:  
\[y(x)=\sum\
olimits_{k=1}^{n}y_{k}(x)+\delta_{k},\]  
where \(y_{k}(x)\) are the measurements collected by the tide gauge \(k\), and \(\delta_{k}\) is the shift that is applied to these measurements to produce a single time series. If \(n\) is the number of segments, there are \((n-1)\) relative shifts \(\delta_{i,\,i+1}\) for \(i=1\), \(n-1\) that must be verified. The number of segments composing the record was sometimes shown by comparing the PSMSL (www.psmsl.org) metric data, the raw data that the PSMSL stores before trying their alignment in their revised local reference (RLR) data set, with this latter result. Some other times, unfortunately, there was no information in PSMSL that a tide gauge record may be segmented. The databases considered for sea level information were PSMSL (www.psmsl.org) and NOAA (tidesandcurrents.noaa.gov). Supporting sea level analyses were sourced from sealevel.info (www.sealevel.info) as well as NOAA (tidesandcurrents.noaa.gov). Subsidence data were sourced from SONEL (www.sonel.org), JPL (sideshow.jpl.nasa.gov/post/series.html), and Nevada Geodetic Lab (geodesy.unr.edu).  
The breakpoint alignment method alone fails to cover the option of legitimate changes in the trends, such as [22], that may occur during periods with missing values. This is the reason why the similarity between sea level patterns in the records from different tide gauges of the same ocean basin was sought. The breakpoint alignment method alone could not address the issues of the missing information periods in the records of Aden, Mumbai, or Karachi taken individually. The breakpoint alignment method coupled with the similarity analysis of the patterns between the sea levels of Aden, Mumbai, Karachi, and Fremantle could better address the issue, without being free of criticism. There is no fully satisfactory procedure that can overcome the issue of missing measurements, malfunction of instruments, or other perturbing issues. The suggestion is to flag the segmented tide gauge records as having quality issues and avoid computing any trend with these records.