Hello all,
I just wanted to circle back and give a thanks to the help I received on this
issue. I also wanted to report back what I have found so that others might
benefit should they run into similar issues in the future.
The issue was getting GOES imagery via NOAAPORT and then displaying that data
using metpy/mathplotlib. Specifically, I am talking about the SCMI L2 data.
There are speckles or artifacts in the imagery. After working with some of the
folks at Unidata the root cause was discovered. That being the FillValue is set
to zero in the SCMI files. The issue is that setting the value to zero makes
any bad data set to zero which is also inside the valid range of data. The data
needs to stay outside of the valid range. The easiest work around and what made
the most sense was to change what the FillValue is as to not alter the data. I
used a utility called ncatted to set the FillValue = NaN. Therefore, when
reading imagery files, the bad data was not shifted into a valid range and any
display software would now treat it correctly and not attempt to display the
data.
Jim Weber
From: Ryan May <rmay@xxxxxxxx>
Sent: Tuesday, November 2, 2021 1:45 PM
To: Weber, Jim <Jim.Weber@xxxxxxx>
Cc: python-users@xxxxxxxxxxxxxxxx
Subject: Re: [python-users] Artifacts in Channel 3 GOES 16 imagery
Hi Jim,
Correct, L1 data are not on NOAAPORT. Unidata does distribute them to the
community over the IDD (using LDM).
If you have questions about the artifacts, that's definitely a question for
whoever is producing the L2 products, which I *think* is NESDIS.
Ryan
On Tue, Nov 2, 2021 at 7:13 AM Weber, Jim
<Jim.Weber@xxxxxxx<mailto:Jim.Weber@xxxxxxx>> wrote:
Ryan,
That looks exactly like what I am seeing! Forgive my ignorance…but the L1 are
not on NOAAPORT, correct? I am wondering the path that this data flows to make
it onto NOAAPORT. Is this a case to reach out to NESDIS or someone else to
inquire what might be causing these artifacts?
Thanks!
Jim Weber
From: Ryan May <rmay@xxxxxxxx<mailto:rmay@xxxxxxxx>>
Sent: Monday, November 1, 2021 4:39 PM
To: Weber, Jim <Jim.Weber@xxxxxxx<mailto:Jim.Weber@xxxxxxx>>
Cc: python-users@xxxxxxxxxxxxxxxx<mailto:python-users@xxxxxxxxxxxxxxxx>
Subject: Re: [python-users] Artifacts in Channel 3 GOES 16 imagery
Hi Jim,
There's no reasonable way that goes_restitch would introduce these kinds of
issues that I can think of. All it's doing is directly copying the 2D chunk of
data from the numerous "chunk files" into the single final data file.
My guess is something is going on with NESDIS' (?) creation of the L2 Cloud
Moisture Imagery, as I'm seeing the same artifacts in our datafiles for the L2
products, but not in the original L1 raw ABI imagery (see attached). Note that
both of these datafiles were reassembled with goes_restitch.
Ryan
On Mon, Nov 1, 2021 at 1:34 PM Weber, Jim
<Jim.Weber@xxxxxxx<mailto:Jim.Weber@xxxxxxx>> wrote:
Hello,
I have been working with Tom Yoksas to get all the goes-restitch setup. I have
been trying to make the “True Color” images such as the image attached to this
email called conus1.png The issue I am running into is that there are small
purple specs in the imagery. After looking through the bands I noticed it
appears the issue is in the “green” or channel 3 band. I am also attaching the
channel 3 imagery where you can clearly see the white speckles in the imagery.
I am getting my data via a Novra receiver that working with Tom has very low
error rates, so I feel confident it is not something I am inducing into the
imagery. I am also only finding it in the Channel 3 imagery. Is this something
that the
goes-restitch.py<https://urldefense.proofpoint.com/v2/url?u=http-3A__goes-2Drestitch.py&d=DwQFaQ&c=uw6TLu4hwhHdiGJOgwcWD4AjKQx6zvFcGEsbfiY9-EI&r=KKIRMcmZ6BcKOjHM4171gGDDLEx31ZuiUy6Gn81J_cs&m=Yk4LYfPGd9c9NAmft0-DuBushyXFmVsc1cHHmJ-idOqfh8DlB-yyY8Ds7G3cebZl&s=tiRYlclEntLy-xOyDvT_-9oZpMVLV6NvjZfWVkmUCPg&e=>
script could be causing or do you know what might be causing this issue?
Thanks so much for any help you can provide me!
Jim Weber
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UCAR/Unidata
Boulder, CO
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