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Roof_PROMICE, bad coordinates in AWS_latest_locations.csv #60
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Also, please let me know if metadata issue are supposed to go elsewhere besides |
Hi! I send the info to Robert for correction. Btw, that shows the usefulness of an error warning if the new transmitted coordinates are very far from the past ones. Here Roof_GEUS data is not sent to DMI, but if it had happened to another station, it should raise a flag and send some alert emails. |
Now the toml file for Roof_PROMICE and KAN_Lv3 are fine. But The coordinates of Roof_PROMICE are still wrong because, although no new data is appended to Roof_PROMICE transmission file, past transmissions from KAN_Lv3 are still in the Roof_PROMICE tx file. I have seen this happening on other occasions, when modems and loggers were moved around. Until now, the solution was that someone would open the transmission file of Roof_PROMICE and remove the rows corresponding to KAN_Lv3. It would be much more reliable if pypromice could check (and crop if necessary) the appended transmission files (in the case AWS-L0/tx/_.txt) so that the content of that file only correspond to the time period described in the toml file. I am leaving the issue open until the proper "latest" coordinates for Roof_PROMICE are being recovered. |
I feel that any issue that is also visible for the data user should be reported here. At least to indicate that we know about the issue and are working on it. So all good! |
Good coordinates for Roof_PROMICE recovered in the |
The coordinates for
Roof_PROMICE
are incorrect inAWS_latest_locations.csv
, located here:https://thredds.geus.dk/thredds/catalog/metadata/catalog.html
This currently shows:
Roof_PROMICE,2023-09-05 23:00:00,67.105042,49.930689,683.6
It appears this is the coordinates for
KAN_L
(if you make the longitude negative).Note that the coordinates for
Roof_GEUS
are correct:Roof_GEUS,2023-09-05 23:00:00,55.688535,12.582198,29.0
Not sure where this mix-up could be occurring? The logic to find these positions is here in
csv2bufr.py
:https://github.com/GEUS-Glaciology-and-Climate/pypromice/blob/e4ff5edb8436da0d51f313739724f9f6e51d46ef/src/pypromice/postprocess/csv2bufr.py#L367
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