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Dataset Title:  "Deepwater CTD - 91g0407.bdo.nc - 27.76N, -95.01W - 1991-06-17" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_91g0407_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   6 options
    nitrate ?  =  micromols   12 options
    phosphate ?  =  micromols per liter   12 options
    silicate ?  =  micromols per liter   12 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
5.0 28.660999298095703 33.606998443603516 4.586999893188477 0.0 0.0 0.0 0.20000000298023224 0.0
15.0 27.93199920654297 35.78200149536133 4.678999900817871 0.0 0.20000000298023224 0.009999999776482582 0.699999988079071 0.0
30.0 23.424999237060547 36.01900100708008 4.98799991607666 0.0 0.10000000149011612 0.019999999552965164 0.8999999761581421 0.0
49.0 21.98699951171875 36.23899841308594 4.840000152587891 0.029999999329447746 0.4000000059604645 0.05000000074505806 1.2000000476837158 0.0
70.0 21.165000915527344 36.46699905395508 3.6489999294281006 0.05000000074505806 3.799999952316284 0.20000000298023224 1.5 0.0
80.0 20.54800033569336 36.51100158691406 3.3589999675750732 0.029999999329447746 6.300000190734863 0.3199999928474426 1.7999999523162842 0.0
101.0 19.097999572753906 36.47999954223633 3.1559998989105225 0.019999999552965164 9.600000381469727 0.5 2.5 0.0
152.0 16.868000030517578 36.25899887084961 2.9860000610351562 0.009999999776482582 15.399999618530273 0.7900000214576721 4.0 0.0
203.0 14.545999526977539 35.9109992980957 2.941999912261963 0.009999999776482582 20.399999618530273 1.090000033378601 6.400000095367432 0.0
304.0 11.788000106811523 35.4900016784668 2.7980000972747803 0.07000000029802322 24.600000381469727 1.440000057220459 13.5 1.0
352.0 10.812000274658203 35.33399963378906 2.609999895095825 0.0 27.200000762939453 1.590000033378601 12.5 0.0
379.0 10.33899974822998 35.26599884033203 2.7780001163482666 0.019999999552965164 25.899999618530273 1.5499999523162842 13.0 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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