Dear @davidhassell 

Thanks for raising this point. I agree with your suggestion (when we spoke) 
that it would be better to *require* `sigma` and `zlev` to contain missing data 
at levels to which they do not apply. In that case, if the first element `zlev` 
contains missing data, or the first element of `sigma` does _not_ contain 
missing data, you can infer that the layers are arranged in order of increasing 
depth, from the surface to the bottom; if the opposite, that they are arranged 
from the bottom upwards. This should be stated in the text. It also implies 
that the non-missing elements of both `sigma` and `zlev` are in monotonic order.

In writing this, I wondered why we assume that layers should be numbered from 
1, rather than 0, or any other number. We don't have to make any such 
assumption, since layer number is not part of formula terms. What matters is 
only the _order_ of the elements along the dimension.

Furthermore, if we require the missing data, `nsigma` is redundant, because you 
can count the number of non-missing `sigma` values. We could omit `nsigma` from 
`formula_terms`. Possibly that would be better, because there is a danger of 
`nsigma` not being updated if the data is processed to keep only subset of the 
sigma layers; the `formula_terms` might be copied without modification, and 
thus the metadata could become incorrect and would lead to misinterpretation of 
the coordinates. However, I expect that existing software may rely on `nsigma`. 
We don't normally have conformance rules for `formula_terms`, but maybe we 
should include one to require `nsigma` to agree with missing data in `sigma` 
and `zlev`, if we keep `nsigma`.

What do you and @johnwilkin think of this?

Jonathan

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