I'm looking at a time series which has a very strong daily cycle in it. However, on top of having a daily cycle in the actual values of the time series, it also has a very strong daily variance cycle.
I am wondering if I can meaningfully remove the 'variance trend' from my time series. I can calculate the 'average variance' for a given hour and then divide by it, but I'm not sure I'm doing anything useful if I do this?
The large variance does correlate with large values in the daily cycle too, but taking a log doesn't seem to help much.
EDIT: EXTRA INFORMATION
As pointed out in the comments, this problem is rather under-defined. Unfortunately, this is a symptom I am also dealing with and so I can't fix that. However, I will try to give some more information.
The goal is to have a model of the time series from which realisations can be drawn. The time series data is a measure of concentration over time, with clear daily and yearly cycles and a linear trend. There are many covariate time series which at least follow the same daily and yearly cycles.
I am currently just trying to explore and learn different time series techniques. I wasn't hoping for a 'solution' but rather for a bit of direction as I hadn't been able to find much information about trends in the variance.