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This does not reflect what I am reading on the CDC website. They say they are normalizing to the 10th percentile of the previous year, which is very different from what you describe. Can you point me to where you are getting your understanding?

And can you clarify what you mean by "value of the previous year"? Do you mean the median? Single day median from one year ago, or annual median from the previous 12 months? Something else?

This is what they say: "The 'baseline' is the 10th percentile of the log-transformed and normalized concentration data within a specific time frame... baselines are re-calculated every six calendar months (January 1st and July 1st) using the past 12 months of data."

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Log transformation of the SARS-CoV-2 concentration data should produce a normal distribution (bell curve) & the selection of the 10th percentile of that bell curve should produce a baseline representing the lowest 10% values of the last 12 months of observation If I understand what they are saying

Normalizing to a 10th percentile is not a completely unreasonable thing to do. When you're measuring things on a log scale, you need to pick a non-zero value as your baseline. The 10th percentile likely represents a conservative compromise that retains some stability in the metric.

If you get too close to zero then your normalized values will be very sensitive to small absolute changes in the baseline values. Go too high and you risk cancelling out too much of the signal. My guess is that the 10th percentile was the lowest they could go without sacrificing stability.

Not really. The difference from baseline is being expressed in terms of standard deviations. But even if it was just giving a ratio, the fact remains that you need to normalize to something, and once you have a few years of data, a low quantile of previous years is a reasonable option.