So I have daily temperature data for each day of the year going back up to 100 years for different locations. With this, I have created a mean value for each day of the year and a 95th percentile again for each day of the year.

I am comparing these values to the daily readings for a specific year (e.g.2016). However, I am only interested if the 2016 values are greater than the daily mean/95th percentile.

Is there a way to determine if the values are significantly greater than the mean/95th percentile?

In essence, there are 366 values for each column (one for each day of the year), and the mean/95th percentile and the 2016 data would be paired.

A rough idea of what my data looks like:

DAY OF YEAR: 1, 2, 3

MEAN TEMP: 12, 10, 11

2016 Temp: 17, 20.6, 13

Then:

DAY OF YEAR: 1, 2, 3

95th Percentile: 16, 14, 13

2016 Temp: 17, 20.6, 13

Apologies if the formatting is confusing.

So, all the 2016 values are larger than they 'should' be, but is this significant?

Is there a way to determine if the values are significantly greater than the mean/95th percentile, not just statistically different?