How to develop a likelihood based prediction model to predict chance of rain in a particular hour of a year?

I have time-series weather data (from 2005-2018) of temperature and rainfall (every one-hour interval) from three different location weather stations. I want to predict/see what likely be a chance of rain in a particular hour of a day in the year (e.g., 2 pm May) using the likelihood. I don’t want to forecast the rain or chance of rain in the future time (e.g., 1 pm, 10 May 2020). I don’t have enough experience in machine learning. I would appreciate if someone suggests a way to do that in python or share a tutorial/example where I can get some basic idea to build my own model.