[Go-essp-tech] Handling missing data in the CMIP5 archive

Fri Jun 24 06:46:58 MDT 2011

Thanks Karl,

I appreciate the clarity of the guidance. This will help us proceed.

Kind regards,

Ag

From: Karl Taylor [mailto:taylor13 at llnl.gov]
Sent: 24 June 2011 01:17
To: Martina Stockhause
Cc: Stephens, Ag (STFC,RAL,RALSP); Lawrence, Bryan (STFC,RAL,RALSP); go-essp-tech at ucar.edu
Subject: Re: [Go-essp-tech] Handling missing data in the CMIP5 archive

Dear all,

O.K. I didn't read Martina and Frank's email until now.  Perhaps my last email should have read in summary:

If a  time-slice that should have been included as part of the requested model output  is entirely missing, that dataset will not be assigned a DOI until that time-slice has been:

1) recovered  (ideally)
2) filled entirely with "missing" values (if it is impossible to recover the actual data).

By special exception, DOI's may be assigned to datasets (without requiring infilling missing data) when a modeling group purposely omits some portion of a time-series, as long as the remaining portion is likely to be of interest.  In no case should a single file contain non-contiguous portions of the time series.

Best regards,
Karl

On 6/23/11 7:22 AM, Martina Stockhause wrote:

Dear Ag,

we propose to fill up the gaps, see 2.5.1 in CF:

http://cf-pcmdi.llnl.gov/documents/cf-conventions/1.5/cf-conventions.html#missing-data

which refers to the NetCDF Guide:

http://www.unidata.ucar.edu/software/netcdf/docs/netcdf.html#Attribute-Conventions

However, there are examples where this does not make much sense. e.g. if

sb puts 1970-1999 and 2070-2099 intentionally into one dataset.

So it remains up to the QC manager to decide whatever makes sense.

Required is in all cases an appropriate comment.

Regards... Martina & frank

On 06/23/2011 01:51 PM, ag.stephens at stfc.ac.uk<mailto:ag.stephens at stfc.ac.uk> wrote:

Dear Karl and Bryan,

There was discussion on the handling of missing data a while back. Do we have a policy decision on this issue? It would be great to know exactly where we stand in terms of whether a missing time step will fail QC and hence need fixing before replication (and subsequent DOIs) can be considered.

It looks to me like there are valid arguments either way, so I think what we need is an authoritative decision that we can all follow.

Thanks

Ag

________________________________________

From: Karl Taylor [taylor13 at llnl.gov<mailto:taylor13 at llnl.gov>]

Sent: 04 May 2011 20:40

To: Lawrence, Bryan (STFC,RAL,RALSP)

Cc: go-essp-tech at ucar.edu<mailto:go-essp-tech at ucar.edu>; Stephens, Ag (STFC,RAL,RALSP)

Subject: Re: [Go-essp-tech] Handling missing data in the CMIP5 archive

Hi Bryan,

Oh, I left something out.  Why is it lots of work for the user to notice by looking at the time axis that the spacing between coordinates is greater than normal, and thus some time slices have clearly been skipped?  For daily data,  for example, if the interval between two successive time-coordinates is 10 days, then 9 samples must be missing.

I will concede that for some software and for some purposes having time-slices included that are completely filled with the missing_value flag could provide some advantages, so I guess I wouldn't object to requiring this, but I think it's a judgment call that's not that clear-cut.

cheers,

Karl

On 5/4/11 11:42 AM, Bryan Lawrence wrote:

Hi Karl

I think we're somewhat at cross purposes.

My view is that if the time-slices have actually been lost, we

shouldn't necessarily reject the data as being useless.

Agreed.

I agree,

however, that we should encourage the modeling groups to try to

recover or reproduce the lost time slices to make their output more

complete.

Agreed.

If that is impossible, I still think in many cases

analysts will want access to the portions of the time-series that

are available.

In which case we should require them to write misssing data fields for

that portion. That should be trivial for them to do, and save the

consumers a vast amount of time.  (ie use the CF missing data flag, we're

not suggesintg htey have to re-run anything unless they want to).

This is Ag's option 2c, which you don't seem to mention.

Consider, for example, a 1000 year control run with a decade missing

in the middle (perhaps all contained in a single lost file).  Don't

you think many researchers will make use of the two portions of the

time-series that *are* available, and shouldn't the available data

be assigned a DOI?

As I recall, data not passing QC level 2 won't normally be replicated

and wouldn't be assigned a DOI.  Is this correct?

Correct.

Cheers

Bryan

best regards,

Karl

On 5/4/11 1:08 AM, Bryan Lawrence wrote:

Hi Karl

There are two issues noted in your email:(1) missing variables, and

(2) missing time slices in a sequence.

I agree that (1) is something to be noted, I think (2) is something

that should cause failure, and require a response as Ag has

suggested. I don't think it's too much to ask a modelling group to

either provide the missing data, or provide missing data flags -

but actual missing files in a sequence should be an error and a

failure!

I think we should be holding a candle for the users here. The

reality is that no code is going to read the metadata to find

missing data, whereas code can read and understand missing data

flags.

Bryan

Dear Ag,

There is another possible way of handling the "missing data"

issue. I'm not sure that a dataset should be be required to be

complete (i.e., required to include all time slices) to be

considered eligible for DOI assignment.  That is, we could relax

the criteria. Note that I don't think we require *all* variables

requested within a single dataset to be present, so some datasets

will indeed be incomplete but be eligible for a DOI.  I think the

QC procedure should be to check with the modeling group, and if

they can't supply the missing time-slices, then we somehow note

this flaw in the dataset documentation and if other QC checks are

passed, assign it a DOI.

The criteria for getting a DOI should be that there are no known

errors in the data itself, and that there are no major problems

with the metadata.  In this case the data will be reliable, and

analysts will be welcome to use it and publish results, so I

think it should be assigned a DOI.

What do others think?

Best regards,

Karl

On 4/28/11 3:12 AM, ag.stephens at stfc.ac.uk<mailto:ag.stephens at stfc.ac.uk><mailto:ag.stephens at stfc.ac.uk><mailto:ag.stephens at stfc.ac.uk>  wrote:

Dear all,

At BADC we have come across our first "missing data" issue in the

CMIP5 datasets we are ingesting. We have an example of some

missing months for a particular set of variables that was

revealed when running the QC code from DKRZ.

It would be very useful for the CMIP5 archive managers to make an

authoritative statement about how we should handle missing data

time steps in the archive.

I propose the following response when a Data Node receives a

dataset

in which time steps are missing:

    1. QC manager (i.e. whoever runs the QC code) informs Data

    Provider that there is missing data in a dataset (specifying

    full DRS structure and date range missing).

    2a. If Data Provider says "no, cannot provide this data" then

    the affected datasets cannot get a DOI and cannot be part of

    the "crystallised archive". STOP

    2b. Data Provider re-generates files, data is re-ingested, new

    version is generated, QC is re-run, all is good. STOP

    2c. Data Provider cannot re-generate but wants to pass QC - so

    needs to create the required files full of missing data.

    3. Data Provider creates missing data files and sends, data

    re-ingested, new version is generated, QC re-run, all good.

    STOP

In cases 2a and 2c it would also be very useful if the dataset is

annotated to inform the user which dates have been FILLED with

missing data. This would, I believe, be in the QC logs but we

might want a more prominent record of this if possible.

Cheers,

Ag

BADC--

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--

Bryan Lawrence

Director of Environmental Archival and Associated Research

(NCAS/British Atmospheric Data Centre and NCEO/NERC NEODC)

STFC, Rutherford Appleton Laboratory

Phone +44 1235 445012; Fax ... 5848;

Web: home.badc.rl.ac.uk/lawrence

--

Bryan Lawrence

Director of Environmental Archival and Associated Research

(NCAS/British Atmospheric Data Centre and NCEO/NERC NEODC)

STFC, Rutherford Appleton Laboratory

Phone +44 1235 445012; Fax ... 5848;

Web: home.badc.rl.ac.uk/lawrence

-- 
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