Before taking this off-line (now that I am back at work and can use my work
email), can I just add that ERDDAP also has many of these features. In my
opinion, a lot of the new efforts are reinventing the wheel. Perhaps taking
time to see what is out there, what they do, and why they are
tity, I believe it was
>> agreed to adopt a plug-in approach.) Perhaps now that SWEET is becoming a
>> more actively managed resource, and once CSDMS is more in the public realm,
>> these may serve as patterns (and vocabulary sources) for using plug-ins in
>&
> On Dec 5, 2018, at 7:18 AM, Lowry, Roy K. wrote:
>
> I also feel that this could take some time and do not feel it would be fair
> to block Simon's request until it is resolved. There are a number of anomaly
> Standard Names and one more isn't going to make a great deal of difference.
Interesting. Look at the archive around April 4, 2016. I was requesting a
standard way to do anomalies, not just variable specific, since anomalies are
calculated all over the place, and it seems to me it makes little sense to have
a new name for each specific anomaly, rather than a generic
Julian day is used in several different ways, as John says:
https://landweb.modaps.eosdis.nasa.gov/browse/calendar.html
-Roy
> On Mar 16, 2017, at 12:49 PM, John Helly wrote:
>
> In language, definitions are based on usage. Julian date, modulo the year, is
> a convention
Sorry I hit the send button by accident. Yes, this is a very real question
for us. If we make a new dataset from say two JPL files, JPL is no longer the
creator, first because they didn't create it, but even more to say they are
are the creator is to imply that they have put their stamp of
> On Jan 20, 2017, at 6:20 PM, John Graybeal wrote:
>
> Hi all,
>
> Over on the ACDD (esip-documentation) list, we started a thread to answer
> some questions about ACDD attributes. One question related to the 3 CF
> attribute definitions for source, institution,
Hi David:
I was unaware of these, thanks. This makes all the more important to look at
the new HDF5 virtual datasets, which are basically virtual aggregations, in the
sense of making sure that there is some harmonization. This is a new feature,
and nows the time to make certain, if at all
Hi All:
We have been given files related o sea surface temperature. The observed value
has the attributes:
analysed_sst:long_name = "analysed sea surface temperature" ;
analysed_sst:standard_name =
"sea_surface_foundation_temperature" ;
and the climatology
> On Mar 28, 2016, at 9:25 AM, Steve Hankin via NetCDF.swg
> wrote:
>
> 2. "Aggregation" -- CF structures to link multiple files into larger
> conceptual datasets. Time series aggregations, union aggregations
> (associated variables in separate files),
> On Dec 18, 2015, at 10:47 AM, V Balaji - NOAA Affiliate
> wrote:
>
> Also, neither I nor any of the original proponents are actively
> developing gridspec at this point. I am happy to support further
> development along the ugrid lines, and treat gridspec's ugrid as a
>
I pass this along to the CF list for obvious reasons.
-Roy
> Begin forwarded message:
>
> From: Ben Domenico
> Subject: Re: [NetCDF.swg] OGC NetCDF SWG DIscussions
> Date: October 21, 2015 at 8:16:22 PM PDT
> To: Cox Simon
> Cc:
Hi All:
Charlie provided me with some sample files. Below, with but two comments, is
the one line command in R for several examples, using David Pierce's wonderful
ncdf4 package, to traverse the complete structure of the file. The results show
the command and the resulting structure. My two
specific featureTypes that we should support.
And if these identified featureTypes demand groups for efficiency or
some other reason, well, let's have that discussion.
-Rich
On Wed, Sep 18, 2013 at 12:08 AM, Roy Mendelssohn - NOAA Federal
roy.mendelss...@noaa.gov wrote:
Hi All:
I am old
Hi All:
I am old and slow, and I must be missing something, because at this point most
of the discussion has been about the desirability of files with groups and
hierarchies. Again, unless I am missing something, there already are data
providers who are distributing data using groups and
15 matches
Mail list logo