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Dataset Title:  "Deepwater CTD - 90g10104.bdo.nc - 28.52N, -89.77W - 1990-07-22" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_90g10104_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   12 options
    salinity ?  =  PSU   12 options
    oxygen ?  =  milliliters per liter   12 options
    nitrite ?  =  micromols   9 options
    nitrate ?  =  micromols   11 options
    phosphate ?  =  micromols   12 options
    silicate ?  =  micromols   12 options
    salinity2 ?  =  PSU   1 option:
    qualityFlag ?  =  2 options

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 PSU milliliters per liter micromols micromols micromols micromols PSU
1.0 29.139999389648438 31.260000228881836 4.605000019073486 0.019999999552965164 0.5 0.019999999552965164 8.800000190734863 0.0
11.0 29.190000534057617 34.6619987487793 4.604000091552734 0.029999999329447746 0.4000000059604645 0.029999999329447746 9.300000190734863 0.0
26.0 26.989999771118164 35.840999603271484 4.71999979019165 0.07000000029802322 0.5 0.07000000029802322 10.199999809265137 0.0
51.0 22.280000686645508 36.14699935913086 4.1519999504089355 0.25999999046325684 2.200000047683716 0.14000000059604645 9.100000381469727 0.0
76.0 19.059999465942383 36.391998291015625 -99.98999786376953 0.07999999821186066 9.600000381469727 0.5600000023841858 9.800000190734863 0.0
100.0 17.809999465942383 36.31800079345703 2.9140000343322754 0.05000000074505806 13.800000190734863 0.7599999904632568 10.899999618530273 0.0
148.0 15.630000114440918 36.0260009765625 2.996000051498413 0.05999999865889549 17.0 0.9599999785423279 11.100000381469727 0.0
199.0 13.680000305175781 35.797000885009766 2.9690001010894775 0.05999999865889549 20.0 1.1200000047683716 12.5 1.0
249.0 11.9399995803833 35.46799850463867 2.811000108718872 0.07000000029802322 24.100000381469727 1.4199999570846558 16.0 0.0
298.0 11.15999984741211 35.35300064086914 2.7790000438690186 0.07000000029802322 25.700000762939453 1.5299999713897705 17.299999237060547 0.0
398.0 9.25 35.09600067138672 2.7730000019073486 0.09000000357627869 28.799999237060547 1.7799999713897705 21.0 0.0
512.0 7.710000038146973 34.957000732421875 2.877000093460083 0.10000000149011612 29.200000762939453 1.9299999475479126 25.0 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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