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I have been tasked with analyzing temperature time series from multiple weather stations. I have minute and hour resolution temperature data spanning three years at 4 stations and 35 stations respectively. The stations reside on ~1000 km^2 (southern tip of Vancouver Island) so they cover a relatively concentrated area.

I am looking for additional "statistical" techniques I can apply to the data. You might ask: what exactly do you want to glean from your data? Well, I am a complete amateur in weather and time series analysis. Pretty much anything that gives useful interpretation of data.

So far I have performed the following:

  • Power spectral density on minute data
  • Probability distribution plots on minute data
  • Auto lag correlation and cross-correlation between stations on minute data
  • Principal component analysis on hourly data

Techniques I have come across:

  • Canonical correlation analysis
  • Cluster analysis
  • ?

Any suggestions for books/papers/websites explaining analysis and practical applications are also much appreciated. I have found "Statistical Methods in the Atmospheric Sciences" (2006) by Wilks to be quite informative.


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You write "You might ask: what exactly do you want to glean from your data?" Indeed! But you then answer by saying you are new to this type of analysis. OK. But try to explain it to us in non-statistical terms. What do you want to find out? – Peter Flom Nov 22 '12 at 13:52

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