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Hi,
Your datasets do not share a time range, so this is not a typical ensemble.
Usually, you can define an ensemble when the datasets do not have the same space/time grids, by first defining a regridding operation so that all datasets have the same space/time grid as the first dataset in your list. On the page,
scroll down in that page to find "Ensemble Examples". Example 3 shows how to define an ensemble for data on two different grids, including for this data a modulo regridding operation to define variables with consistent grids. The variable names must also match, so that example also shows how to rename the file variable within the Ferret session, and then define the new regridded variables using the desired names.
I am not sure what commands you tried using @AVE. If you did a time average, then the resulting grid no longer depends on time, so there should not be an error message about time axes. Look at this example:
! Make a file containing the variables in the first dataset, averaged in time.
! An ensemble needs one file with the grid that is going to be used in the
! ensemble; not all of the grids can come from LET definitions.
yes? use dataset_1
yes? let/like=precip p_tave = precip [t=@ave]
yes? save/file=data1.nc p_tave
yes? cancel data 1! Now open this data and define variables in the other dataset(s) so that
! they can be included in an ensemble.
yes? use data1.nc
yes? use dataset_2
yes? let/d=2/like=precip p_tave = precip[t=@ave,gxy=p_tave [d=1]]
yes? ensemble time_ave = 1,2
! The ensemble dataset should contain the variable p_tave with a grid in X-Y-E
yes? show data time_ave
On 11/18/2021 3:22 PM, Xiaoyu Bai wrote:
Dear ferreters,
I am trying to ensemble RCPs (2005-2099) and control runs (1949-2005) together but keep getting T axis differs error.
*** NOTE: Variable "PRECIPITATION" excluded from aggregate: T axis differs among members
**ERROR: error defining aggregate dataset: No valid datasets or datasets share no variables that can be aggregated.
It makes sense for pyferret to think the time axis are different. But comparing the @AVE value from different time series should also make sense to pyferret. I am wondering how to solve this problem.
By the way, I already tried to read data in separately and do @AVE first then compare. It still showed the same error because the data still come from different time series.
If you want to learn more about ensembles: https://ferret.pmel.noaa.gov/tutorials/PyFerret_exploring_ensembles.pdf--
Xiaoyu (she/her)