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Dataset Title:  "Deepwater CTD - d92b103.bdo.nc - 27.76N, -93.0W - 1992-00-07" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d92b103_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   12 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 30.499300003051758 33.501800537109375 -9.0 0.0 0.5600000023841858 0.0 1.5800000429153442 -9.0 0.0
24.0 28.554800033569336 35.29399871826172 -9.0 0.0 0.5099999904632568 0.009999999776482582 1.399999976158142 -9.0 0.0
49.0 23.004899978637695 36.178001403808594 -9.0 0.0 0.7099999785423279 0.0 0.6399999856948853 -9.0 0.0
58.0 21.144699096679688 36.19889831542969 -9.0 0.0 0.8199999928474426 0.009999999776482582 0.8100000023841858 -9.0 0.0
73.0 20.129499435424805 36.26789855957031 -9.0 0.23000000417232513 1.75 0.03999999910593033 0.6000000238418579 -9.0 0.0
88.0 19.527299880981445 36.36470031738281 -9.0 0.1599999964237213 8.020000457763672 0.36000001430511475 2.380000114440918 -9.0 0.0
98.0 18.818300247192383 36.41239929199219 -9.0 0.05999999865889549 11.100000381469727 0.5299999713897705 3.200000047683716 -9.0 0.0
128.0 17.138599395751953 36.28219985961914 -9.0 0.029999999329447746 14.539999961853027 0.7799999713897705 4.460000038146973 -9.0 0.0
148.0 16.09119987487793 36.14390182495117 -9.0 0.019999999552965164 15.989999771118164 0.8999999761581421 5.71999979019165 -9.0 0.0
162.0 15.597399711608887 36.0713996887207 -9.0 0.03999999910593033 16.850000381469727 0.9700000286102295 6.480000019073486 -9.0 0.0
178.0 15.152299880981445 36.005699157714844 -9.0 0.029999999329447746 17.739999771118164 1.0299999713897705 7.420000076293945 -9.0 0.0
201.0 14.990699768066406 35.982601165771484 -9.0 0.029999999329447746 17.75 1.0299999713897705 7.010000228881836 -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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