I am in disagreement with a statement that a part time teacher made. This is more of a theoretical question (no calculations).

Suppose I am analyzing a data set of wind speed of monthly data.

I fit a distribution to my data and I determine the CDF function.

Now, I am asked what is the 50-year design wind speed?

The question is: how do you translate the given return period?

Usually, a 50 year return period corresponds to P(X>x) = 1/50 = 0.02 (regardless of measurement units, it is the definition).

However, my part-time professor argues that since the data we are working with has units of month, we need to find: P(X>x)=1/(50*12)

I do not agree with the latter. Once you analyse your data and devlop the CDF, units become meaningless. The concept of return period is in years and simply conveys a probability of exceedance (there are no units attached to it.)

Can someone please advise?

Thank you

EDIT:

What I am trying to say is that the frequency of the data measurement has nothing to do in determining the probability of exceedance for a given return period. The frequency (monthly, hourly, yearly) only affects how many data points you have and as a result how accurate your CDF is.