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Dataset Title:  "Deepwater CTD - d93e031.bdo.nc - 27.97N, -90.5W - 1993-04-28" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93e031_bdo)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 12)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    depth ?  =  m   12 options
    temperature ?  =  degree_C (potential temperature from ctd)   12 options
    salinity ?  =  PSU   12 options
    oxygen ?  =  milliliters per liter   1 option: -9.0
    nitrite ?  =  micromols   6 options
    nitrate ?  =  micromols   11 options
    phosphate ?  =  micromols   8 options
    silicate ?  =  micromols   11 options
    salinity2 ?  =  PSU   1 option: -9.0
    qualityFlag ?  =  1 option: 0.0

View:      Map of All Related Data ?      Distinct Data Counts ?     Distinct Data ?      Related Data Counts ?     Related Data ?

 
Map of All Related Data ?   (Refine the map and/or download the image)

To view the map, check View : Map of All Related Data above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.
 


Distinct Data Counts ?

To view the counts of distinct combinations of the variables listed above,
check View : Distinct Data Counts above and select a value for one of the variables above.

 


Distinct Data ?   (Metadata)    (Refine the data subset and/or download the data)  

depth temperature salinity oxygen nitrite nitrate phosphate silicate salinity2 qualityFlag
m degree_C (potential temperature from ctd) PSU milliliters per liter micromols micromols micromols micromols PSU
0.0 22.440399169921875 35.53049850463867 -9.0 0.03999999910593033 0.0 0.0 1.3700000047683716 -9.0 0.0
9.0 22.75550079345703 36.27669906616211 -9.0 0.029999999329447746 0.03999999910593033 0.0 1.3700000047683716 -9.0 0.0
23.0 22.779499053955078 36.44329833984375 -9.0 0.029999999329447746 0.009999999776482582 0.0 1.2300000190734863 -9.0 0.0
48.0 22.638900756835938 36.429500579833984 -9.0 0.029999999329447746 0.009999999776482582 0.0 1.25 -9.0 0.0
61.0 22.6018009185791 36.41939926147461 -9.0 0.03999999910593033 0.029999999329447746 0.0 1.2699999809265137 -9.0 0.0
73.0 21.631200790405273 36.619998931884766 -9.0 0.38999998569488525 2.0799999237060547 0.07999999821186066 1.7100000381469727 -9.0 0.0
83.0 20.35610008239746 36.51599884033203 -9.0 0.4000000059604645 6.170000076293945 0.3100000023841858 2.809999942779541 -9.0 0.0
98.0 19.095699310302734 36.45289993286133 -9.0 0.11999999731779099 9.140000343322754 0.4699999988079071 3.7100000381469727 -9.0 0.0
148.0 16.093299865722656 36.134300231933594 -9.0 0.05999999865889549 14.800000190734863 0.8399999737739563 6.559999942779541 -9.0 0.0
197.0 14.671899795532227 35.91579818725586 -9.0 0.03999999910593033 17.690000534057617 1.0499999523162842 7.960000038146973 -9.0 0.0
297.0 12.19890022277832 35.52669906616211 -9.0 0.029999999329447746 22.8700008392334 1.4299999475479126 11.579999923706055 -9.0 0.0
435.0 9.093700408935547 35.093299865722656 -9.0 0.03999999910593033 28.799999237060547 1.8700000047683716 18.059999465942383 -9.0 0.0

In total, there are 12 rows of distinct combinations of the variables listed above. All of the rows are shown above.
To change the maximum number of rows displayed, change View : Distinct Data above.
 


Related Data Counts ?

To view the related data counts,
check View : Related Data Counts above and select a value for one of the variables above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.
 


Related Data ?   (Metadata)    (Refine the data subset and/or download the data)

To view the related data, change View : Related Data above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.


 
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