This would require adding output variables for these quantities and then performing the above calculation as part of the YOG calculation.

It looks like the code above would be a 'number concentration tendency' is that correct?

A couple of further comments:

• Our cloud liquid and ice tendencies could be either positive or negative, unlike ZM which can only give positive tendencies due to detrainment because of the assumptions of the scheme. Thus we shouldn't have the max(0,) functions in our expressions for the number tendencies. However, we should add a constraint that these tendencies can't lead to negative values of the number concentrations themselves.
• We should also output these number concentration tendencies to the statistics files.

OK, the above approach has been implemented as part of pull request #23
I will add in the same pull request the addition of YOG number concentration tendencies to the outputs, and look at allowing negative tendency but with a limit of reducing n at most to 0.0.

As a related question 0.0 number concentration should (physically) coincide with 0.0 liquid water or ice content?

I have now extended #23 to implement a constraint that YOG number concentration tendency can be negative, but cannot reduce total number concentration below zero.

I have added @paogorman and @MarionBWeinzierl as reviewers there to look at the changes.

For number concentration tendencies output those from YOG directly.
For ZM look at clubb but try and generate the comparison using explicitly the convective contribution to tendencies.