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Dataset Title:  "Deepwater CTD - d92c049.bdo.nc - 27.79N, -92.0W - 1992-11-00" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d92c049_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   5 options
    nitrate ?  =  micromols   11 options
    phosphate ?  =  micromols   11 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
2.0 24.327499389648438 35.68510055541992 -9.0 0.0 0.11999999731779099 0.05999999865889549 2.25 -9.0 0.0
12.0 24.38800048828125 35.72850036621094 -9.0 0.0 0.09000000357627869 0.05000000074505806 2.1500000953674316 -9.0 0.0
32.0 24.73940086364746 36.0625 -9.0 0.0 0.009999999776482582 0.03999999910593033 2.0299999713897705 -9.0 0.0
48.0 24.746700286865234 36.072898864746094 -9.0 0.0 0.0 0.029999999329447746 2.0199999809265137 -9.0 0.0
63.0 24.703899383544922 36.07160186767578 -9.0 0.009999999776482582 0.0 0.03999999910593033 2.109999895095825 -9.0 0.0
72.0 24.029800415039062 36.161399841308594 -9.0 0.20999999344348907 0.23999999463558197 0.07000000029802322 2.990000009536743 -9.0 0.0
82.0 22.452699661254883 36.26029968261719 -9.0 0.14000000059604645 1.090000033378601 0.11999999731779099 3.450000047683716 -9.0 0.0
98.0 20.5231990814209 36.30120086669922 -9.0 0.029999999329447746 4.980000019073486 0.28999999165534973 4.480000019073486 -9.0 0.0
126.0 18.744699478149414 36.37269973754883 -9.0 0.009999999776482582 10.869999885559082 0.6000000238418579 5.349999904632568 -9.0 0.0
167.0 16.980499267578125 36.26679992675781 -9.0 0.009999999776482582 13.460000038146973 0.7599999904632568 5.590000152587891 -9.0 0.0
248.0 14.213700294494629 35.85329818725586 -9.0 0.009999999776482582 19.1299991607666 1.1399999856948853 8.550000190734863 -9.0 0.0
372.0 9.83489990234375 35.19929885864258 -9.0 0.009999999776482582 27.940000534057617 1.7599999904632568 16.690000534057617 -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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