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Dataset Title:  "Deepwater CTD - d94h093.bdo.nc - 27.46N, -94.27W - 1994-05-01" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94h093_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   5 options
    nitrate ?  =  micromols   10 options
    phosphate ?  =  micromols   10 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 23.52359962463379 35.846099853515625 -9.0 0.009999999776482582 0.17000000178813934 0.009999999776482582 3.2300000190734863 -9.0 0.0
24.0 22.040700912475586 36.084800720214844 -9.0 0.0 0.17000000178813934 0.009999999776482582 2.7899999618530273 -9.0 0.0
49.0 20.0049991607666 36.20920181274414 -9.0 0.0 0.17000000178813934 0.029999999329447746 2.380000114440918 -9.0 0.0
59.0 19.653799057006836 36.22200012207031 -9.0 0.0 0.2800000011920929 0.029999999329447746 2.259999990463257 -9.0 0.0
72.0 19.430299758911133 36.276798248291016 -9.0 0.11999999731779099 1.6399999856948853 0.10000000149011612 3.240000009536743 -9.0 0.0
80.0 19.361000061035156 36.335601806640625 -9.0 0.20999999344348907 4.5 0.25 4.190000057220459 -9.0 0.0
100.0 18.841800689697266 36.286598205566406 -9.0 0.03999999910593033 5.789999961853027 0.3400000035762787 5.239999771118164 -9.0 0.0
198.0 15.049400329589844 35.97489929199219 -9.0 0.0 17.06999969482422 1.0 8.380000114440918 -9.0 0.0
403.0 9.780900001525879 35.19380187988281 -9.0 0.009999999776482582 27.15999984741211 1.7000000476837158 17.100000381469727 -9.0 0.0
600.0 7.337100028991699 34.940101623535156 -9.0 0.009999999776482582 30.579999923706055 1.9600000381469727 23.530000686645508 -9.0 0.0
798.0 5.552800178527832 34.903499603271484 -9.0 0.009999999776482582 28.8700008392334 1.8899999856948853 27.600000381469727 -9.0 0.0
998.0 4.860799789428711 34.929500579833984 -9.0 0.009999999776482582 26.489999771118164 1.7599999904632568 28.1200008392334 -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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