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Dataset Title:  "Deepwater CTD - 88g0528.bdo.nc - 27.0N, -94.75W - 1988-10-20" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_88g0528_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   12 options
    salinity ?  =  PSU   12 options
    oxygen ?  =  milliliters per liter   12 options
    nitrite ?  =  micromols per liter   2 options
    nitrate ?  =  micromols   12 options
    phosphate ?  =  micromols per liter   11 options
    silicate ?  =  micromols per liter   11 options
    salinity2 ?  =  PSU   1 option:
    qualityFlag ?  =  2 options

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
200.0 17.719999313354492 36.354000091552734 2.875999927520752 0.0 13.0 0.6700000166893005 5.400000095367432 0.0
250.0 15.300000190734863 36.029998779296875 2.7330000400543213 0.0 17.799999237060547 0.9700000286102295 8.0 0.0
301.0 13.720000267028809 35.731998443603516 2.5869998931884766 0.0 21.799999237060547 1.2200000286102295 10.399999618530273 0.0
401.0 11.40999984741211 35.40800094604492 2.4860000610351562 0.0 26.5 1.5 14.800000190734863 0.0
500.0 9.979999542236328 35.22999954223633 2.51200008392334 0.0 28.899999618530273 1.649999976158142 16.700000762939453 1.0
600.0 8.220000267028809 35.01499938964844 2.638000011444092 0.0 31.700000762939453 1.8600000143051147 20.799999237060547 0.0
700.0 7.070000171661377 34.92499923706055 2.867000102996826 0.0 32.29999923706055 1.8899999856948853 23.899999618530273 0.0
799.0 6.179999828338623 34.895999908447266 3.2160000801086426 0.0 31.299999237060547 1.8899999856948853 26.0 0.0
900.0 5.53000020980835 34.90700149536133 3.617000102996826 0.0 29.899999618530273 1.7999999523162842 27.299999237060547 0.0
991.0 5.070000171661377 34.92300033569336 3.934999942779541 0.009999999776482582 28.399999618530273 1.7200000286102295 27.799999237060547 0.0
1151.0 4.650000095367432 34.94599914550781 4.343999862670898 0.009999999776482582 26.399999618530273 1.600000023841858 27.700000762939453 0.0
1300.0 4.409999847412109 34.95899963378906 4.598999977111816 0.009999999776482582 25.299999237060547 1.5399999618530273 27.700000762939453 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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