Recently, there has been much talk in the media of it being the hottest day of the year so far. It has always seemed to me that there are likely many more of these in the northern hemisphere than the southern.
In the northern hemisphere "the year" starts close to the local minimum and so for a good half of the year there is a fairly reasonable chance that a given day will be the hottest so far.
However, in the southern hemisphere after an initial cluster of hot days it is very unlikely there will be another so hot until the end of the year, limiting the number "hottest so far". (And vice versa for cold).
I'm interested in quantitative models of this kind of phenomenon (not just for temperature, but similar patterns). But I don't know how to start developing a model which is tractable. Maybe the year could be modeled as a sinusoid, with a superimposed zero-mean normally distributed random element. It seems that the likely number of "highest"/"lowest" so-fars should be expressible in terms as a function of starting phase and variance.
Is this something that has been studied, or is maybe trivial to those with the relevant skills?