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Dataset Title:  "Deepwater CTD - d93g108.bdo.nc - 27.75N, -93.0W - 1993-11-13" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93g108_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   11 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
1.0 25.02429962158203 36.37969970703125 -9.0 0.0 0.25 0.009999999776482582 1.850000023841858 -9.0 0.0
18.0 25.023099899291992 36.378501892089844 -9.0 0.0 0.17000000178813934 0.009999999776482582 1.649999976158142 -9.0 0.0
38.0 24.98040008544922 36.36669921875 -9.0 0.0 0.07999999821186066 0.009999999776482582 1.690000057220459 -9.0 0.0
48.0 24.900400161743164 36.35070037841797 -9.0 0.009999999776482582 0.07999999821186066 0.009999999776482582 1.6799999475479126 -9.0 0.0
58.0 22.520200729370117 36.42390060424805 -9.0 0.15000000596046448 0.6200000047683716 0.05000000074505806 1.9600000381469727 -9.0 0.0
67.0 21.727500915527344 36.58829879760742 -9.0 0.18000000715255737 2.1600000858306885 0.12999999523162842 2.1500000953674316 -9.0 0.0
78.0 20.764799118041992 36.4900016784668 -9.0 0.05000000074505806 4.889999866485596 0.25 2.6700000762939453 -9.0 0.0
98.0 18.97599983215332 36.467498779296875 -9.0 0.029999999329447746 10.460000038146973 0.5400000214576721 3.809999942779541 -9.0 0.0
123.0 17.760499954223633 36.338199615478516 -9.0 0.019999999552965164 12.699999809265137 0.6899999976158142 4.789999961853027 -9.0 0.0
147.0 16.58609962463379 36.20790100097656 -9.0 0.009999999776482582 14.600000381469727 0.8100000023841858 5.53000020980835 -9.0 0.0
171.0 15.567899703979492 36.06489944458008 -9.0 0.009999999776482582 16.06999969482422 0.9100000262260437 6.440000057220459 -9.0 0.0
203.0 15.034000396728516 35.98509979248047 -9.0 0.019999999552965164 17.049999237060547 0.9800000190734863 7.150000095367432 -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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