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I am writing an automated target selection application in which the seeing at the time of observation is an important factor: some fields are important to observe under good seeing, others, less so. Of course, it can only choose based on current conditions, not the conditions a few minutes in the future under which the observation will actually occur.

In writing simulations to evaluate the effectiveness of different algorithms, I need to generate simulated seeing values. I have global statistics for the seeing at the site, but determining how the seeing changes over time is important.

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up vote 5 down vote accepted

I'm not sure if this directly answers your question, but the Greenwood Frequency defines the speed at which the atmosphere changes substantially enough on a small scale that an adaptive optics system needs to adjust. Typical Greenwood frequencies are around 20Hz, meaning that the conditions in an isoplanatic patch of the sky change substantially enough to cause seeing problems around 20 times per second.

But that's just for a particular isoplanatic patch, not the whole sky. If you are interested in how the general seeing changes over time - like perhaps how the Fried parameter fluctuates over a night, I'm afraid it's going to be extremely difficult to model correctly since atmospheric turbulence is chaotic. You might be better off looking for historical data on this, though I'm not sure where you'd find it.

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I am currently looking at data for the PSF widths for long SDSS runs as baseline historical data. – ehneilsen Jun 7 '11 at 19:21
@Eric Sounds good. By the way, remember that the variability of the PSF width will depend on the observing site; at a poor site like Yerkes the seeing varies between 1" and 5", while at Apache Point (which is where the SDSS is done) its only between 0.5" and 2" typically. I don't know for sure, but I'd guess that the speed with which conditions can change also varies for different sites. – spencer nelson Jun 7 '11 at 22:09

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