I have two datasets, both measures of sea level at a particular location. Although these are both measuring sea level, they are measured with different devices and different methods, and thus have different values and scales at many points.

I know for sure that one dataset is more accurate than the other, and thus I want to fit the second dataset to the first as closely as possible, and then find a way to measure agreement.

The datasets also do not have the same lengths, and for each x value, there is not always a y value for both (e.g. on a certain day and hour, one dataset has a point, but the other may not)

I tried matching the distance between their minimum and maximum points and then shifting in order to match the mean of each, but this isn’t ideal as there are some outliers which make the fit imperfect.

Image below shows what I’ve gotten to

This is what I currently have, based on trial and error