Z-scores of time series data (temperatures)

I need to compute the z-scores of daily temperature data. My data runs from 1975 - 2010, November - March. Each November - March is relates to each day of the season's average temperature (1 - 151 days of season, so 151 avg temperatures). For example, a z-score for day 1 of the season (November 1st) would begin with an average for all 35 Nov. 1st days (1975 - 2010). I computed this in Excel by fitting a polynomial regression to each day of the season's average (151 averages), then divided the output of the polynomial regression equation for each day by the standard deviation of that particular day, but this is quite taxing to compute over multiple large data sets. Any ideas on how to approach this would be great!

Answer 1

[Chad Greene]

Does the zscore function do what you want?

[Tyler Smith]

I don't believe so. If I'm not mistaken, the zscore function computes the zscore of all temperatures without respect to the day of the season. The day of the season is a necessary component because climatologically each day of the season has a different avg, thus a different stdev.

[Chad Greene]

It sounds like you could loop through 1 to 151 and compute the z scores for each day? Alternatively, you could deseason the signal and then calculate the z scores for the whole dataset.