This looks like a textbook Bayesian inference problem to me. It's even been tagged Bayesian.
[EDIT] However first we need to assume that weatherman's accuracy is independent of the weather in order to apply that hunch. It needs to be consistently 90% regardless of rain or no rain. If we can assume that then we can calculate as follows:
$$P(\text{rain | weatherman says rain})=\frac{P(\text{weatherman says rain |rain})P(\text{rain})}{P(\text{weatherman says rain})}$$
$$P(\text{weatherman says rain |rain})=\frac{90}{100}$$ from the text.$$P(\text{rain})=\frac{5}{365}$$ as per the text (on a local average anyway). $$P(\text{weatherman says rain})=P(\text{weatherman says rain, rain})+P(\text{weatherman says rain, no rain})=\frac{90}{100}\frac{5}{365}+\frac{10}{100}\frac{360}{365}$$You put it together and you get $$\frac{1}{9}\approx 11.11\%$$ so there is agreement.
My guess is that this question is simply a textbook problem.
@Henry I'm too disreputable to comment directly in your answer space but I like your approach to finding an upper bound in a dependent case.