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I am struggling to get the GFS from July 1st, July 3rd and July 5th. I can get the global file for each step of the model but when I put them all together expedition crashes. How can I get a small GFS file for like 14 days on each of these days for the transpac course?
Thanks
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One easy solution is NOAA NOMADS.
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Thanks for the replay Nick. Unless I am missing something I can only go back 10 days on the NOMADS site. Am I doing something wrong?
Thanks
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[/img]
Offline
Another option is to use Saildocs.
Make a request from Exp. For example
send GFS:39N,15N,167W,115W/0.25,0.25/0,3,6,9,12,15,18,21,24/MSLP,WIND
Change the model to gfsa (gfs archived)), the hours desired and add a parameter with the start date "|start= YYYYMMDD"
For example, to request 15 days at 6 hour increments
send gfsa:39N,15N,167W,115W|0.25,0.25|0,6..360|PRMSL,WIND|start=20250701
Offline
Unless it has to be GFS, ERA5 is probably a better dataset.
Offline
Thanks Nick. Super helpful, for this look back it has to be the GFS. I tried using the GFSA but that is a zero-hour data from successive model runs as a best-estimate of reality rather than the forecast file from the start of the race.