The frequency versus number of bad weeks per year will follow a power curve. The binary "bad weather" is not enough information to say much more than that. The "analysis" needs to be redone and produce a dataset of weather weeks that can be sampled.
What do you mean by "8% of the time?" Is that 8 weeks out of a hundred? Hard to square with 2-9 weeks out of 52, or ~4-18 weeks out of a hundred. Are you saying that the bad weeks per annum parameters are min:2, mode:7, max:9, mean:4?
Your choice of min and max seems a bit naive. Are you saying that there is zero probability of a year with one or ten bad weeks?
Re second question: You have three ways to express this: As the probability of the event occuring within a particular time scale (.01 probability of occurence in any one year), or the expected number of events in a (longer) time scale, or preferably as a probability distribution plotting frequency against elapsed time (this is where I would sample the data used for the "analysis").