Hi Sebastiien
On 18/10/17 18:19, Sebastien Villaume wrote:
Hi Antonio,
thank you for your detailed answer. You answered some of my questions but
completely misses one crucial point, i.e. how do I distinguish 2 very different
usage of the same generic standard name ?
I understand that you don't mean to have 2 coordinates with
forecast_period as value for the attribute standard_name right?
My point it's to avoid the usage of standard_time="time" unless it's
been used for the valid time concept (for example, observations).
I give you few concrete examples.
Example 1:
dimensions:
i = 360 ;
j = 180 ;
t = 1 ;
variables:
double time(t) ;
time:units = "hours since 2010-01-01 00:00:00" ;
time:standard_name = "time" ;
time:calendar = "gregorian" ;
time:axis = "T" ;
.... lat/long here ....
float data(t, j, i) ;
...
data:standard_name = "temperature" ;
data:coordinates = "time lat lon" ;
...
data:
time = [ 00 ]
...
What is this? Is this an analysis? an observation? or something else?
Because the usage of "time" as standard_name for the time coordinate I'm
not able to say if it's an analysis or a forecast. What I'm able to say
is that the variable "data" are temperatures with valid time at
2010-01-01 00:00:00 (instantaneous)
ith
Example 2:
dimensions:
i = 360 ;
j = 180 ;
t = 5 ;
variables:
double forecast_reference_time(t) ;
forecast_reference_time:units = "hours since 2010-01-01 00:00:00" ;
forecast_reference_time:standard_name = "forecast_reference_time" ;
double leadtime(t) ;
leadtime:units="hours" ;
leadtime:standard_name="forecast_period" ;
.... lat/long ....
float data(t, j, i) ;
...
data:standard_name = "temperature" ;
data:coordinates = "leadtime forecast_reference_time lat lon" ;
...
data:
forecast_reference_time = [ 00, 00, 00, 00, 00 ]
leadtime = [ 00, 06, 12, 18, 24 ]
...
What is this? is it the forecast done back on the 1st January 2010? or is it a
hindcast done years later to test the model of today? or is it a forecast from
a reanalysis dataset, for instance ERA5? or something else?
It's a forecast with analysis time on the 2010-01-01 00:00:00 and time
steps of 00, 06, 12, 18 and 24 which are valid at 2010-01-01 00:00:00,
2010-01-01 06:00:00, 2010-01-01 12:00:00, 2010-01-01 18:00:00 and
2010-01-02 00:00:00 (respectively). IMO a hindcast or reanalysis are
different concepts that doesn't relates to time coordinates directly but
they relate to different "realization" or "source" auxiliary coordinates
or as global attributes.
extra question for example 2: lets assume it is a hindcast. how will I be able
to distinguish this hindcast done today from the hindcast I am going to do in 5
years time to test the model then? or from the hindcast I did 2 years ago for
that date?
They are in fact 2 different realizations that could be encoded, for
examle, using the "realization" as auxiliary/discrete coordinate. The
"source" standard_name could be also used to encode different model
versions as a auxiliary/discrete coordinate or as global attribute.
It is to clarify this sort of things that I would like to have extra standard
name, something less generic than the 3 available standard names.
If I change the standard name in example 1 for "analysis_time", isn't it more
clear what it is?
forecast_reference_time already means analysis time that the reason
because I think you don't need a new standard_name. If the first example
means analysis then I would change the standard_name to
forecast_reference_time with no forecast_periodcoordinate.
If I use hindcast_reference_time and hindcast_period in example 2 AND I include
a mechanism to encode when the hindcast has been computed, isn't it clearer as
well
IMO the forecast_reference_time already has this role. Hindcats and
regular forecast are the same physical concept. If you need to encode
when the product has been generated then other kind of convention could
used (like date_created attribute from Attribute Convention For Data
Discovery) .
more comments are very welcome! :)
Yes, other views and comments from someone else is welcome.
Antonio
cheers,
/Sébastien
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