Due to the current gap in continued funding from the U.S. National Science Foundation (NSF), the NSF Unidata Program Center has temporarily paused most operations. See NSF Unidata Pause in Most Operations for details.
Due to the current gap in continued funding from the U.S. National Science Foundation (NSF), the NSF Unidata Program Center has temporarily paused most operations. See NSF Unidata Pause in Most Operations for details.
Dear John Happy New Year! Thanks for your lengthy contribution to our discussion about representing contracted axes for time coordinates. You raise some useful points about what information we need to record. The main difference between your approach and ours is that you have chosen to attach information about the contracted axis to another axis, whereas we proposed to store it as a singleton axis of its own. For instance, in the first example of a timeseries of 12 monthly average temperatures derived from daily means, * you have Tavg(avgtime,lat,lon), where avgtime is a 12-element time axis, and has attributes describing how each month was derived from days, whereas * we have Tavg(day,month,lat,lon), where month has a dimension of 12 and day a dimension of 1, the latter recording the information about the contraction of daily means into a monthly mean. One reason for adopting your approach is that you say that existing software would not be able to handle our approach, with its two (or more) time axes. That would be undeniably an obstacle to adopting our scheme - what is the problem, in fact (generically)? Apart from this problem, you argue that our approach is more difficult to understand. I would like to argue that it has important advantages of flexibility and consistency. * It is flexible because it can easily be extended. In your system, you can describe a timeseries of 12 monthly means, each derived from daily means; and you can describe a timeseries of climatological daily means for particular days of the year, each derived from a mean of corresponding days from several years. But I do not see how you can describe a combination of these two e.g. the climatological maximum daily mean for each month of the year, i.e. (1) for each day, calculate the mean; (2) within each month, find the maximum daily mean; (3) compute the mean of these maxima for corresponding months over several years. This is represented in our scheme by three time axes (day,month,year), where both day and year are contracted singleton axes. I think your inclusion of the attribute contraction_itemiscontraction indicates that you recognise a need for contractions within contractions; but I would argue that information of the same detail and kind needs to be recorded for each one, and it is simplest to use the same structures to do it. * It is consistent because it is the same as the approach we propose for contracted spatial axes. In our scheme, from a two-dimensional variable (lat,lon) with lat=72, lon=96, we derive a zonal-mean field (lat,con_lon), with con_lon=1 as a contracted axis recording information about the range and spacing of longitudes over which the average is formed. This is exactly the same as our treatment of a time contraction. In your example 5, you have treated a contraction of a pressure axis in just this way, leaving a contracted singleton axis. But in your treatment of time contractions, you don't do this: you record the contraction using attributes on the remaining uncontracted time axis, not using a contracted singleton axis.
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