# Changes between Initial Version and Version 2 of Ticket #152

Ignore:
Timestamp:
07/13/16 00:57:28 (3 years ago)
Comment:

Hello Jonathan,

The answer to the first question is yes, and I've modified the layout to make it a bit clearer.

On the 2nd point, I'm not sure. What I'm proposing is clarifying the usage with time-varying area fractions, or, in principle, area fractions which vary with any other coordinate dimension (e.g. an ensemble index). At the moment the construct is still dependent on the standard name area_fraction, so it can only apply to horizonal areas.

I've added a sentence to the proposed insert to clarify that time can be replaced by another dimension.

regards, Martin

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• ## Ticket #152 – Description

 initial The proposal is to make it clear that use of `where` for non-spatial dimensions is allowed by adding examples in section 7. It is also necessary to provide these examples to clarify the subtle differences implied by different formulations of the `cell_methods` statement. The following should be added as a new example in section 7.3.3: == New example for time-varying area fractions == ''The following new example and explanatry text should be added in section 7.3.3:'' Example 7.8: Time mean over area fractions which vary with time float partial_mean(lat,lon): partial_mean:cell_methods: area: mean where sea_ice over sea time:mean partial_mean:cell_methods: area: mean where sea_ice over sea time: mean }}} When the area fraction is varying with time, there are several different ways in which a time mean can be formulated. Three of these are illustrated in this example. Suppose, for instance, we are averaging over three time steps and the data at one grid point is -10, -6, -2 with area fractions .75, .50, .25. The values of the simple_mean, weighted_mean and partial mean are, respectively, (-10 -6 -2)/3 = -6, (-10*.75 - 6*.5 -2*.25)/(.75+.5+.25) = -7.33 , and (-10*.75 - 6*.5 -2*.25)/3 = -3.667. The partial mean provides the contribution to the mean over the entire grid from a specified area type. The simple mean is weighting each time period equally, while the weighted mean provides equal weighting to each unit area of `sea_ice`. In example 7.8, `time` could be replaced by any other coordinate over which an average is taken, such as an ensemble index.