Machine Learning - Data Pre-Processing
No.  You can leave the month as is.  It shouldn't matter.  For a random forest, there's no value in normalizing it; it won't make the classifier any more or less accurate.

(The same is actually true for temperature, wind, and humidity data, too: there's no harm in normalizing them, but also no benefit, if you're using a random forest classifier.)