Return to search results
💡 Advanced Search Tip
Search by organization or tag to find related datasets
Glacier Bay oceanography CON calibration files for CTD#5 s/n 6353
"CON" files define the sensor configuration and calibration parameters of Sea-Bird oceanographic CTD profilers. Until recently they followed a proprietary format set by Sea-Bird Electronics, Inc. Proprietary files are not interpretable by common applications. To view or edit these data, one must invoke SBEDataProc.EXE software from Sea-Bird. (Calibration files are in XML form beginning in December 2011.) CON files, combined with raw HEX data, are used to generate the CNV processed data files required for performing analyses.
A new CON file is generated for a particular CTD each time any instrument on the CTD is calibrated. A revised file may also be created between formal calibrations to reflect a new, removed, or repaired sensor on the unit. The appropriate CON file to use for generating particular CNV files is the first file that is equal to or earlier than the month and year the cast was made. It is possible, though rare, for a CTD to have more than one CON file in a particular month and year. In such cases the second file name is appended with (A), a third with (B), and so on. The actual dates of each calibration in a file may be seen inside the file by using Sea-Bird's proprietary tools.
This is referenced in the protocol as deliverable OC_A.
Complete Metadata
| @id | http://datainventory.doi.gov/id/dataset/085c654fabb596a64adbe8d39e50b451 |
|---|---|
| bureauCode |
[ "010:24" ] |
| dataQuality | true |
| identifier | NPS_DataStore_2258290 |
| issued | 2022-04-14T12:00:00Z |
| landingPage | https://irma.nps.gov/DataStore/Reference/Profile/2258290 |
| programCode |
[ "010:118", "010:119" ] |
| references |
[ "https://irma.nps.gov/DataStore/Reference/Profile/2258290", "https://irma.nps.gov/DataStore/Reference/Profile/2293261" ] |
| spatial | -138.586334,58.1591225,-135.316757,59.4830551 |
| temporal | 2008-08-01T12:00:00Z/2021-01-01T12:00:00Z |
| theme |
[ "Generic Dataset" ] |