Discrete wavelet decomposition (wavedec) using less than 365 days per year

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Hi!
I am trying to run a wavelet coherence analysis of daily streamflow from two gage stations. I have for each year daily streamflow from October and November (61 days) over a period of 75 years, that means that I have daily flow only for 61 days a year. This results on 4575 daily flows (75 years x 61 days) in each station.
When I run the wavelet coherence analysis using the 4575 samples I got the following image
However, I do not know how to convert the Normalized Frequency (cycles/sample) to period of years?
I want to understand how coherent were the daily streamflow data for October and November (the fall season) of each year for different periodicities of 1 year, 2years, 4years, and 8years.
How can i understand this normalized frequency?
Thank you for the help!
  10 Comments
Jonas
Jonas on 30 Jun 2022
I have re-run the wavelet coherence function over this new data but with the new frequency:
365 (samples / year) * (1 year / 365 days) * (1 day / 24 hours) * (1 hour / 3600 seconds) = 1.1574E-5
using the following expresion:
wcoherence(upstream,downstream,0.0000157431)
just an error from typing you forgot a 1
num2str(1/(24*60*60),'%.12f')
ans =
'0.000011574074'
About the first approach to try, do you mean to multiply the nHz of the y axis in the frist Figure by 6, this will mean then 512 nHz * 6 = 3072 nHz?
Yes, the first figure and the yticklabels changed by factor of 6 to compensate for the fact, that the data were taken ober two months only and not over a whole year. in addition, you can also change the yticklabels by your formular from nano Herz to years, to make it better readable
I have tried to run the wcoherence function using 6 samples/year (365/61) with a frequency equal to:
6 (samples / year) * (1 year / 365 days) * (1 day / 24 hours) * (1 hour / 3600 seconds) = 1.9024E-7
i think this does not make sence.

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