How can I perform weibull analysis on monthly recorded data of wind speeds? I've read several articles about how to perform Weibull distribution but they all did it with wind speed data in a time series manner (example: recorded data every 10mins and then averaged to every hour). My prob is that I've got only mean monthly wind speed for a year (from January to December). So how should I deal with this situation to perform Weibull distribution on these data?
I have data for 5 years namely 2006, 2007, 2008, 2009, 2010 and like i said, its monthly wind speed from January to December. I'd appreciate if you could help out. Thank you in advacnce...
 A: The first question is whether the Weibull distribution is still a good model of wind speed when it is a monthly average.  I'm not familiar with this field, but from what you say it sounds as though average hourly wind speed is often modelled as having a Weibull distribution.  If you take the average of 700 or so such random variables (24*30) the distribution will be very nearly normally distributed because of the central limit theorem, even with the autocorrelation of the underlying hourly observations.
I'd suggest looking at the actual distribution of your 60 data points and comparing it to a normal distribution, using something like the qqnorm() function in R to draw a plot being the obvious starting point.
But basically, I doubt the probability distribution of your variables is your main problem here.  The challenge with modelling your data will be more related to the need for you to estimate and control for seasonal effects from quite a small data set (by time series standards).  Exactly what sort of challenge that is though depends on what your research question is (for example, do you need to see if one year's wind speed was different from others? or are you looking for a trend? or what?).
