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Dataset Title:  "Deepwater CTD - d93g189.bdo.nc - 27.11N, -96.28W - 1993-11-19" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93g189_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   8 options
    nitrate ?  =  micromols   11 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
0.0 23.22439956665039 34.97380065917969 -9.0 0.0 0.3700000047683716 0.07000000029802322 3.4100000858306885 -9.0 0.0
14.0 23.840200424194336 35.60319900512695 -9.0 0.0 0.15000000596046448 0.029999999329447746 2.890000104904175 -9.0 0.0
28.0 23.923099517822266 35.72200012207031 -9.0 0.009999999776482582 0.029999999329447746 0.029999999329447746 2.6700000762939453 -9.0 0.0
39.0 23.97130012512207 35.7776985168457 -9.0 0.07000000029802322 0.15000000596046448 0.03999999910593033 2.75 -9.0 0.0
44.0 24.044300079345703 35.91339874267578 -9.0 0.14000000059604645 0.36000001430511475 0.05000000074505806 2.8299999237060547 -9.0 0.0
53.0 23.912500381469727 36.10150146484375 -9.0 0.2199999988079071 0.9900000095367432 0.10999999940395355 3.380000114440918 -9.0 0.0
65.0 23.619600296020508 36.1781005859375 -9.0 0.11999999731779099 1.4500000476837158 0.10999999940395355 3.200000047683716 -9.0 0.0
79.0 21.230899810791016 36.33169937133789 -9.0 0.03999999910593033 3.809999942779541 0.20999999344348907 3.240000009536743 -9.0 0.0
108.0 18.907699584960938 36.44309997558594 -9.0 0.019999999552965164 11.479999542236328 0.5899999737739563 4.110000133514404 -9.0 0.0
147.0 16.785999298095703 36.232601165771484 -9.0 0.0 14.819999694824219 0.8199999928474426 5.599999904632568 -9.0 0.0
221.0 13.745699882507324 35.77980041503906 -9.0 0.0 19.3700008392334 1.1299999952316284 8.770000457763672 -9.0 0.0
310.0 12.331899642944336 35.561100006103516 -9.0 0.0 21.989999771118164 1.3200000524520874 10.720000267028809 -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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