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Dataset Title:  "Deepwater CTD - d92a002.bdo.nc - 27.74N, -94.2W - 1992-05-01" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d92a002_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: 11)
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   11 options
    temperature ?  =  degree_C (potential temperature from ctd)   11 options
    salinity ?  =  PSU   11 options
    oxygen ?  =  milliliters per liter   1 option: -9.0
    nitrite ?  =  micromols   5 options
    nitrate ?  =  micromols   11 options
    phosphate ?  =  micromols   8 options
    silicate ?  =  micromols   11 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 23.478300094604492 32.922401428222656 -9.0 0.009999999776482582 0.009999999776482582 0.009999999776482582 5.199999809265137 -9.0 0.0
14.0 23.73200035095215 34.893001556396484 -9.0 0.009999999776482582 0.05999999865889549 0.009999999776482582 2.7699999809265137 -9.0 0.0
29.0 23.171100616455078 36.1781005859375 -9.0 0.009999999776482582 0.12999999523162842 0.0 1.2999999523162842 -9.0 0.0
39.0 22.48699951171875 36.19960021972656 -9.0 0.009999999776482582 0.07999999821186066 0.009999999776482582 0.8799999952316284 -9.0 0.0
48.0 22.025800704956055 36.28950119018555 -9.0 0.05000000074505806 0.10000000149011612 0.009999999776482582 0.7599999904632568 -9.0 0.0
68.0 20.0137996673584 36.180999755859375 -9.0 0.30000001192092896 0.699999988079071 0.05999999865889549 0.9200000166893005 -9.0 0.0
98.0 18.805400848388672 36.157100677490234 -9.0 0.029999999329447746 4.239999771118164 0.23000000417232513 3.240000009536743 -9.0 0.0
127.0 18.44569969177246 36.378501892089844 -9.0 0.019999999552965164 10.479999542236328 0.5299999713897705 4.130000114440918 -9.0 0.0
197.0 14.589400291442871 35.91469955444336 -9.0 0.009999999776482582 18.290000915527344 1.0299999713897705 8.84000015258789 -9.0 0.0
297.0 11.367799758911133 35.422298431396484 -9.0 0.009999999776482582 24.790000915527344 1.3899999856948853 16.389999389648438 -9.0 0.0
374.0 10.066399574279785 35.240699768066406 -9.0 0.019999999552965164 27.260000228881836 1.6799999475479126 20.260000228881836 -9.0 0.0

In total, there are 11 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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