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I'm working on timedomain astronomy galaxies that change over time and applying SETI signal recovery methods to ordinary astronomical data to learn more about the interstellar "channel," or the contents of the space in between stars and galaxies.

The timedomain function representing the sound is simply the sum of the timedomain functions from each instrument (or for a polyphonic instrument like a piano, the sum of the timedomain function for each note).

A Fourier Transform can transform timedomain into a frequencydomain and visa versa.

Yee, original developer of the Finitedifference timedomain method.
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Well, the same multistable behavior observed in the timedomain appears in the spatial domain as well, whether you are talking shortterm weather or longterm climate.

When filtering a timedomain signal, we signal processing folk have to account for filter delay, do the smoothing operations do the same?

Econometricians tend to prefer to look at timedomain information such as autocorrelation functions.

In the case of a correlation of tree ring widths with temperature, the permitted use would be that finding a similar tree with a correspondingly similar ring width within the timedomain of the correlation may imply a similar local temperature.

But what if those residuals are already detrended in timedomain plot?

Something wrong with that timedomain residual data or MBH99 reconstructions are lowpass filtered after the error analysis phase..
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