Regression Analysis of Tidal Phases

In summary: If you are fitting a model to a time series, you might also want to consider autocorrelation, which is the correlation of successive values.
  • #1
edge333
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0
I have some 3-D model output for a river system that is tidally forced at the entrance. Right now, I'm trying to perform some linear regression on the harmonic constants of various tidal constituents at for several locations along the river compared to the observed tidal data. A linear regression of the model vs. observed tidal amplitudes is straightforward but how would you do a similar OLS regression of the tidal phases if they are cyclical (phase wraps)?

For example, say the downstream station 1 (S1) M2 tide has an observed phase of 230 degrees and a modeled phase of 240 degrees but the upstream station 5 (S5) M2 tide has an observed phase of 358 degrees and the a modeled phase of 3 degrees. Obviously the S5 regression point will appear as an outlier even the the phase difference is truly 5 degrees.

1877_K1_M2_regress_chezy_53.png

The third plot (bottom left) are phases plotted using tangent with domain -pi < theta < pi

I thought about adjusting all of the phases by subtracting the minimum phase of the observed data (x-value to 0) but that may not fix the problem if the difference between observed and modeled phase of one station is greater than that minimum value.

Can I transform the phases into some phase difference? I attempted to just take the cosine(phase) but that restricts the phases to a domain of -1 to 1 where cosine(90) and cosine(270) both give me 0. Is there a way to use four-quadrant tangent technique? There must be some non-linear OLS model to apply to the phase. How would I get confidence intervals and R values?
 
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  • #2
If there is no ambiguity, you can fix the phase values before the fit, e. g. assign -2 degrees to your observed phase because this is closer to the modeled phase.
If there is ambiguity (like a measured phase of 170 degrees with a model phase of 0 degrees), you'll need something better. Depending on the software you use, there might be some algorithm for those fits, or you can modify the fit to consider both options (and to take the one with the smaller deviation).
 
  • #3
I'd think that a natural measure for the "distance" between two functions with the same period and a different phase would be the root mean square strength (per period) of the signal that is given by the difference of the two functions.
 

1. What is regression analysis of tidal phases?

Regression analysis of tidal phases is a statistical method used to analyze the relationship between tidal phases and other variables. It is used to identify patterns and trends in tidal data and make predictions about future tidal behavior.

2. What type of data is needed for regression analysis of tidal phases?

In order to perform regression analysis of tidal phases, you will need data on tidal phases (such as high tide and low tide times), as well as data on other variables that may affect tidal behavior, such as lunar cycles, weather patterns, or ocean currents.

3. How is regression analysis of tidal phases performed?

Regression analysis of tidal phases involves creating a mathematical model that describes the relationship between tidal phases and other variables. This model is then used to make predictions about future tidal behavior.

4. What are the benefits of using regression analysis of tidal phases?

Regression analysis of tidal phases can provide valuable insights into the patterns and trends of tidal behavior. It can also help to identify factors that may be influencing tidal phases, and make predictions about future tidal behavior.

5. Are there any limitations to regression analysis of tidal phases?

Like any statistical method, regression analysis of tidal phases has its limitations. It assumes a linear relationship between variables and may not be accurate if there are non-linear relationships or if there are other external factors that are not accounted for in the model.

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