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Dataset Title:  "Deepwater CTD - d92b094.bdo.nc - 27.87N, -92.86W - 1992-00-07" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d92b094_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   7 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
0.0 30.340599060058594 34.1338005065918 -9.0 0.0 0.4300000071525574 0.019999999552965164 1.590000033378601 -9.0 0.0
9.0 30.088499069213867 34.17639923095703 -9.0 0.0 0.4300000071525574 0.019999999552965164 1.3700000047683716 -9.0 0.0
24.0 28.879100799560547 35.39390182495117 -9.0 0.0 0.41999998688697815 0.029999999329447746 1.6799999475479126 -9.0 0.0
49.0 22.392499923706055 36.16550064086914 -9.0 0.0 0.4099999964237213 0.029999999329447746 0.47999998927116394 -9.0 0.0
58.0 21.614700317382812 36.28519821166992 -9.0 0.0 0.4099999964237213 0.019999999552965164 0.14000000059604645 -9.0 0.0
70.0 21.01420021057129 36.38370132446289 -9.0 0.20000000298023224 0.7599999904632568 0.03999999910593033 0.36000001430511475 -9.0 0.0
80.0 19.999500274658203 36.32160186767578 -9.0 0.2199999988079071 3.0999999046325684 0.17000000178813934 1.0199999809265137 -9.0 0.0
91.0 19.40220069885254 36.36920166015625 -9.0 0.07000000029802322 8.260000228881836 0.4300000071525574 2.0999999046325684 -9.0 0.0
113.0 18.161399841308594 36.3931999206543 -9.0 0.029999999329447746 12.979999542236328 0.6499999761581421 3.309999942779541 -9.0 0.0
148.0 16.556499481201172 36.20920181274414 -9.0 0.009999999776482582 15.319999694824219 0.8500000238418579 4.420000076293945 -9.0 0.0
177.0 15.498800277709961 36.05569839477539 -9.0 0.0 16.81999969482422 0.9599999785423279 5.519999980926514 -9.0 0.0
212.0 15.232199668884277 36.0166015625 -9.0 0.019999999552965164 17.280000686645508 1.0099999904632568 5.949999809265137 -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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