Jonathan,

>> Typical producers of this kind of data are numerical particle tracking
>> models.  These codes step through time, following the (x,y,t) or
>> (x,y,z,t) trajectories of individual particles.  At each time step,
>> more particles may be introduced to be tracked, while other particles
>> stop being tracked because they leave the domain, hit the boundary, or
>> whatever.
>
> This kind of data could be described by the trajectory feature type, but each
> trajectory would be entirely independent, so they'd all have separate times,
> whereas as you describe it the time coord is common to all trajectories (that
> exist at a particular time). To arrange this, an indirection could be used on
> the time dimension:
>  data(i,o)     x(i,o) y(i,o) z(i,o) t(tindex(i,o))
> where i is the instance (which of the trajectories), o is the point along that
> trajectory, t is the coordinate vector of common times, and tindex is an index
> to t. For example, we might have these two trajectories (x,t) (omitting y and
> z for simplicity)
>  (0,10) (1,11) (2,12)
>         (3,11) (2,12) (1,13) (0,14)
> Then t would be [10,11,12,13,14] (all the times). For the first trajectory
>  x=[0,1,2] tindex=[0,1,2]
> and for the second
>  x=[3,2,1,0] tindex=[1,2,3,4]
> Is that right? Perhaps/probably there's a neater or more natural way to do it.

Yes, that's exactly right.

With the approach you suggest, if you wanted to obtain all the
particle positions at a particular time step, would you need to read
all tindex for all particles?  (I'm a little fuzzy on what the CDL
would look like...)

Thanks,
Rich
-- 
Dr. Richard P. Signell   (508) 457-2229
USGS, 384 Woods Hole Rd.
Woods Hole, MA 02543-1598
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