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Dataset Title:	"Deepwater CTD - d92c003.bdo.nc - 27.8N, -94.19W - 1992-11-05"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d92c003_bdo)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | 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	= (ANY) 2.0 23.0 47.0 68.0 77.0 98.0 118.0 138.0 158.0 197.0 237.0 257.0  m	12 options
temperature	= (ANY) 13.710399627685547 13.88539981842041 15.578900337219238 17.39550018310547 18.61370086669922 20.399799346923828 21.48310089111328 22.93269920349121 23.48870086669922 25.70840072631836 25.712499618530273 25.721900939941406  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 35.77840042114258 35.80550003051758 36.06589889526367 36.238800048828125 36.2421989440918 36.24380111694336 36.33440017700195 36.3385009765625 36.349300384521484 36.363399505615234 36.374000549316406 36.46030044555664  PSU	12 options
oxygen	= (ANY) 2.7699999809265137 2.8499999046325684 3.140000104904175 3.240000009536743 3.2699999809265137 3.5999999046325684 4.260000228881836 4.75 4.760000228881836 4.78000020980835 4.869999885559082 4.900000095367432  milliliters per liter	12 options
nitrite	= (ANY) 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.07000000029802322  micromols	6 options
nitrate	= (ANY) 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.05000000074505806 0.10999999940395355 1.2699999809265137 5.210000038146973 11.199999809265137 12.430000305175781 15.329999923706055 18.280000686645508 20.209999084472656  micromols	12 options
phosphate	= (ANY) 0.029999999329447746 0.03999999910593033 0.07999999821186066 0.25999999046325684 0.550000011920929 0.6299999952316284 0.8500000238418579 1.059999942779541 1.190000057220459  micromols	9 options
silicate	= (ANY) 2.2100000381469727 2.5299999713897705 2.5899999141693115 2.5999999046325684 2.6600000858306885 3.490000009536743 4.809999942779541 5.289999961853027 7.090000152587891 9.109999656677246 11.010000228881836  micromols	11 options
salinity2	= (ANY) 35.78200149536133 35.90299987792969 36.0880012512207 36.250999450683594 36.25199890136719 36.25600051879883 36.34299850463867 36.36000061035156 36.36600112915039 36.37200164794922 36.38100051879883 36.46799850463867  PSU	12 options
qualityFlag	= (ANY) 0.0 1.0	2 options

View:      Map of All Related Data      Distinct Data Counts     Distinct Data  0 10 100 1000 10000 100000      Related Data Counts     Related Data  0 10 100 1000 10000 100000

 

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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.
 

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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.
 

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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	25.70840072631836	36.24380111694336	4.78000020980835	0.019999999552965164	0.10999999940395355	0.03999999910593033	2.6600000858306885	36.250999450683594	0.0
23.0	25.721900939941406	36.2421989440918	4.75	0.019999999552965164	0.009999999776482582	0.03999999910593033	2.5299999713897705	36.25199890136719	0.0
47.0	25.712499618530273	36.238800048828125	4.760000228881836	0.009999999776482582	0.05000000074505806	0.029999999329447746	2.5899999141693115	36.25600051879883	0.0
68.0	23.48870086669922	36.349300384521484	4.900000095367432	0.07000000029802322	0.029999999329447746	0.03999999910593033	2.5999999046325684	36.36000061035156	0.0
77.0	22.93269920349121	36.374000549316406	4.869999885559082	0.07000000029802322	0.019999999552965164	0.029999999329447746	2.2100000381469727	36.37200164794922	0.0
98.0	21.48310089111328	36.33440017700195	4.260000228881836	0.07000000029802322	1.2699999809265137	0.07999999821186066	2.5299999713897705	36.36600112915039	0.0
118.0	20.399799346923828	36.363399505615234	3.5999999046325684	0.03999999910593033	5.210000038146973	0.25999999046325684	3.490000009536743	36.38100051879883	0.0
138.0	18.61370086669922	36.46030044555664	3.140000104904175	0.029999999329447746	11.199999809265137	0.550000011920929	4.809999942779541	36.46799850463867	0.0
158.0	17.39550018310547	36.3385009765625	3.240000009536743	0.029999999329447746	12.430000305175781	0.6299999952316284	5.289999961853027	36.34299850463867	0.0
197.0	15.578900337219238	36.06589889526367	3.2699999809265137	0.019999999552965164	15.329999923706055	0.8500000238418579	7.090000152587891	36.0880012512207	1.0
237.0	13.88539981842041	35.80550003051758	2.8499999046325684	0.03999999910593033	18.280000686645508	1.059999942779541	9.109999656677246	35.90299987792969	1.0
257.0	13.710399627685547	35.77840042114258	2.7699999809265137	0.05000000074505806	20.209999084472656	1.190000057220459	11.010000228881836	35.78200149536133	1.0

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.
 

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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.
 

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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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