I've tinkered with the new GRIB aggregation, made a few subsets. I noticed some funky x/y coords in the data dump : Y begins at -832.6982610175619 (?) and X @ -4226.1069969154705. Noitced in the definition that the units are Kilometers... (from what reference lat/lon ?)
These are projection coordinates, in "km on the projecction plane". The projection is defined by
following the CF-1 conventions. This is the projection contained in the GRIB file.
The particular client I used to access this (GrADS) cannot decern this x/y spatial cooredinate. It is expecting them as lambert grid relative x[1:x] etc.
Not sure weither this is something that can be configured with the aggregation, but it certainly would be nice to have the option to use grid relative x/y coords.
sorry, I dont know what "grid relative x/y coords" are?
Other than this, I see the TDS handles the varying Z dimension across variables quite well. Does it still require the files to be homogenous? Or will it scan each one for the forecast hour = <specified> header tag ~ and use that?
Yes thats the intention, to not need index homogeneity, but to use the times in the GRIB files and make it all work nicely. The GRIB files require another level of XML configuration, to make it all work. We are hoping to work closely with all to get this figured out, and ill explain in more detail then.
Glenn.Rutledge wrote the following on 8/15/2006 8:50 AM:
Dan- You have the lead with Steven to implement this new aggregation service on your platform of choice. This is one of the Web Services I spoke of- and please make this #1 priority. See msg below. Glenn
Subject: Forecast Model Run Collection Aggregation prototype available Date: Mon, 14 Aug 2006 18:02:05 -0600 From: John Caron <address@hidden> Organization: UCAR/Unidata To: address@hidden, Steve Hankin <address@hidden>
An experimental new TDS service "Forecast Model Run Collection Aggregation" is available for poking at on the motherlode development server:
This aggregates a collection of Forecast Model Runs (in this case the IDD NAM CONUS 80km runs), making it available as one dataset with a 2D time coordinate.
Then it creates various other logical datasets:
1) data from one run (what we already are used to) 2) data with the same forecast offset hour (eg all the 3 hour forecasts, from different runs) 3) data with a constant forecast date (eg all the data for 2006-08-08T12:00:00Z, from different runs) 4) the "best" time series, taking the data from the most recent run available
This is not production-ready, so dont clobber it, but any testing and comments welcome.
-- Glenn K. Rutledge Services Team Leader Remote Sensing and Applications Division NOMADS Project Manager National Oceanic and Atmospheric Administration National Climatic Data Center Asheville NC 28801 Phone: (828) 271-4097 Fax: (828) 271-4328
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