In order to model the weather effects basically two things are needed, the software capable of doing so and the input data. While I have access to computer models that can theoretically do it the problem I am facing is with the data to be used.
We can get weather data for a period of over 30 years in most localities but how this translates into the format that is to be imputed into our models?
Recently the trend of government agencies is toward requiring in a very vague language for contractors to consider weather into their models and take 100% of the risk on what is expected and only what is way above normal (whatever it means) that had an impact is to be considered a shared risk. Although I believe the vague language will not hold in court I am looking for some guidance on what is an acceptable methodology for this purposes. I get completely lost when the agencies talk about NOAA and at the same time they provide their own estimate, I do not know which one prevails.
As I am from a tropical region where it rains frequently I would like the procedure to be done using NOAA and the NWS (National Weather Service) data for Dorado Puerto Rico to see if we can agree what are the average expected days to be lost for every month and expand to a probabilistic distribution to be used in Monte Carlo models.
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Thanks in advance for your contributions,
Rafael