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Dataset Title:  "Deepwater CTD - 94g0815.bdo.nc - 28.23N, -89.67W - 1994-10-21" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_94g0815_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: 11)
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   11 options
    temperature ?  =  degree_C   11 options
    salinity ?  =  PSU   11 options
    oxygen ?  =  milliliters per liter   11 options
    nitrite ?  =  micromols per liter   3 options
    nitrate ?  =  micromols   10 options
    phosphate ?  =  micromols per liter   11 options
    silicate ?  =  micromols per liter   11 options
    salinity2 ?  =  PSU   1 option:
    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 PSU milliliters per liter micromols per liter micromols micromols per liter micromols per liter PSU
5.0 27.392000198364258 36.104000091552734 5.177000045776367 0.019999999552965164 0.0 0.009999999776482582 2.299999952316284 0.0
50.0 24.29599952697754 36.236000061035156 5.5370001792907715 0.019999999552965164 0.0 0.019999999552965164 1.7000000476837158 0.0
100.0 19.8700008392334 36.57600021362305 3.6059999465942383 0.029999999329447746 8.399999618530273 0.4099999964237213 3.0999999046325684 0.0
150.0 17.02400016784668 36.24100112915039 3.48799991607666 0.009999999776482582 13.0 0.6700000166893005 4.900000095367432 0.0
200.0 15.13700008392334 35.9640007019043 3.3420000076293945 0.009999999776482582 16.799999237060547 0.8999999761581421 6.699999809265137 0.0
300.0 11.802000045776367 35.439998626708984 3.1700000762939453 0.009999999776482582 23.899999618530273 1.3799999952316284 11.300000190734863 0.0
400.0 10.013999938964844 35.20500183105469 3.0320000648498535 0.009999999776482582 27.600000381469727 1.649999976158142 14.899999618530273 0.0
500.0 8.739999771118164 35.04100036621094 3.007999897003174 0.009999999776482582 29.399999618530273 1.809999942779541 17.700000762939453 0.0
600.0 7.704999923706055 34.95199966430664 3.1559998989105225 0.009999999776482582 30.600000381469727 1.9199999570846558 20.600000381469727 0.0
700.0 7.203000068664551 34.917999267578125 3.2330000400543213 0.009999999776482582 30.5 1.9500000476837158 21.700000762939453 0.0
795.0 6.732999801635742 34.902000427246094 3.3350000381469727 0.009999999776482582 30.799999237060547 1.9600000381469727 22.799999237060547 0.0

In total, there are 11 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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