Seasonal change is often studied as how the climate of a certain block of time constituting a calendar season is changing. However calendar categorisation loses some aptness when just applied globally and is not necessarily the optimal framework for looking for climate change effects on what we fundamentally call seasonality – the varying nature of climate over the year. Many different cultures, such as Aboriginal nations of Australia have very different seasonal calendars which often may be better at characterising the yearly cycle of a particular locality.  Taking a no assumptions approach, beyond that the cyclic nature of the season can be modeled with a combination of sinusoids, an attempt to identify changes in this seasonality in temperature records has been made with particular focus on the shifts in timing of seasonal transitions. The data used was the ACORN-SAT V2 which includes high quality temperature records for 112 Australian stations back to 1910 (for some but not all stations). New methods of identifying these changes using the properties of multiple orders of Fourier series fits were explored. First order fits have a well-defined phase and amplitude to the cycle which can be seen to have significantly shifted at locations across Australia in the past 100 years. Higher order fits give a much more accurate fit to the data and thus eliminate ambiguity of what actual change the measure is detecting. The downside of using higher order fits is the loss of a simple phase measure, but this can be substituted by identifying the shift of meaningful milestones such as inflection points in seasonal transitions and mean crossing points. There results were analyzed for geographical patterns with spatial coherence seen in some measures, such as a uniform positive seasonal phase shift in the northern latitudes of the country.