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Dataset Title:  "Deepwater CTD - d94h002.bdo.nc - 27.82N, -94.0W - 1994-04-24" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94h002_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   9 options
    nitrate ?  =  micromols   10 options
    phosphate ?  =  micromols   9 options
    silicate ?  =  micromols   12 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
1.0 23.37019920349121 35.587100982666016 -9.0 0.029999999329447746 0.0 0.03999999910593033 2.5899999141693115 -9.0 0.0
16.0 21.1875 35.89630126953125 -9.0 0.009999999776482582 0.0 0.03999999910593033 2.390000104904175 -9.0 0.0
31.0 21.235700607299805 36.167198181152344 -9.0 0.0 0.03999999910593033 0.03999999910593033 2.2899999618530273 -9.0 0.0
40.0 20.553800582885742 36.227699279785156 -9.0 0.009999999776482582 0.019999999552965164 0.03999999910593033 2.4600000381469727 -9.0 0.0
56.0 19.874000549316406 36.19279861450195 -9.0 0.11999999731779099 0.7599999904632568 0.07999999821186066 2.569999933242798 -9.0 0.0
62.0 19.798099517822266 36.23360061645508 -9.0 0.019999999552965164 4.730000019073486 0.25999999046325684 3.559999942779541 -9.0 0.0
80.0 19.37969970703125 36.33039855957031 -9.0 0.019999999552965164 9.40999984741211 0.47999998927116394 5.369999885559082 -9.0 0.0
99.0 18.70400047302246 36.330501556396484 -9.0 0.029999999329447746 11.489999771118164 0.5899999737739563 6.519999980926514 -9.0 0.0
114.0 18.22130012512207 36.317100524902344 -9.0 0.05999999865889549 15.890000343322754 0.8399999737739563 8.329999923706055 -9.0 0.0
144.0 16.69809913635254 36.20119857788086 -9.0 0.09000000357627869 17.770000457763672 0.9599999785423279 9.789999961853027 -9.0 0.0
183.0 15.701399803161621 36.07460021972656 -9.0 0.10000000149011612 18.700000762939453 1.0499999523162842 11.140000343322754 -9.0 0.0
202.0 -9.0 -9.0 -9.0 0.03999999910593033 0.0 0.05999999865889549 3.200000047683716 -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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