On Friday, July 24, 2020 at 10:39:51 AM UTC+1, Norman Lynagh wrote:
Here is one example of the sort of problems that I encounter:

If you have 20 years of hourly wind data from what is normally a
relatively benign location, but the data includes 6 hours of high winds
resulting from the passage of a hurricane, how do you extrapolate the
distribution to predict the once in 50-year wind event? The short
answer is that it is impossible.

The problem is that the winds produced by the passage of the hurricane
are not part of the same population as all of the other (benign) winds
and therefore the total wind environment cannot be described by any
single statistical function. In this case, what is necessary is to
determine the long-term hurricane climate of the location and work
backwards from that to produce an estimate of the once in 50-year wind
event.

Have you not considered using a technique similar to that used by Nigel Cook. He uses several methods to project sea level rise. You could use several databases to predict your 50 year wind event. The first would be the total record, the second would be the periods during hurricanes, and the third the total record less those during hurricane periods. So long as you make it clear which set you are using.

In predicting future sea-level rise what is first of all needed is to
determine the 'climate' of the events responsible for sea level rise.

I was not predicting that sea level will be 82 cm. I was saying that if you extend the trend until 2100 then you get an 82 cm rise. Nigel extended using four methods, so he can’t be accused of predicting a value either.