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Dataset Title:  "Deepwater CTD - d93d099.bdo.nc - 27.35N, -93.0W - 1993-02-11" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93d099_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)   10 options
    salinity ?  =  PSU   10 options
    oxygen ?  =  milliliters per liter   1 option: -9.0
    nitrite ?  =  micromols   6 options
    nitrate ?  =  micromols   10 options
    phosphate ?  =  micromols   8 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 21.038000106811523 36.08919906616211 -9.0 0.009999999776482582 0.10000000149011612 0.07000000029802322 2.549999952316284 -9.0 0.0
9.0 -9.0 -9.0 -9.0 0.009999999776482582 0.09000000357627869 0.05000000074505806 2.200000047683716 -9.0 0.0
29.0 21.031600952148438 36.14569854736328 -9.0 0.009999999776482582 0.09000000357627869 0.05000000074505806 1.9800000190734863 -9.0 0.0
39.0 -9.0 -9.0 -9.0 0.009999999776482582 0.07999999821186066 0.05000000074505806 1.7300000190734863 -9.0 0.0
49.0 20.993799209594727 36.16270065307617 -9.0 0.009999999776482582 0.07999999821186066 0.05000000074505806 1.6299999952316284 -9.0 0.0
72.0 -9.0 -9.0 -9.0 0.019999999552965164 0.12999999523162842 0.05000000074505806 1.590000033378601 -9.0 0.0
97.0 19.721599578857422 36.42369842529297 -9.0 0.07000000029802322 9.4399995803833 0.5199999809265137 3.890000104904175 -9.0 0.0
148.0 16.844100952148438 36.23820114135742 -9.0 0.07000000029802322 14.619999885559082 0.8700000047683716 5.699999809265137 -9.0 0.0
197.0 14.786600112915039 35.93870162963867 -9.0 0.07999999821186066 18.219999313354492 1.1200000047683716 7.829999923706055 -9.0 0.0
296.0 11.260000228881836 35.400299072265625 -9.0 0.10000000149011612 24.969999313354492 1.6100000143051147 12.819999694824219 -9.0 0.0
494.0 7.696300029754639 34.95989990234375 -9.0 0.11999999731779099 30.350000381469727 2.0399999618530273 21.8799991607666 -9.0 0.0
736.0 5.797399997711182 34.89590072631836 -9.0 0.11999999731779099 29.290000915527344 2.0299999713897705 26.81999969482422 -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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