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Dataset Title:	"Deepwater CTD - 88g0523.bdo.nc - 26.55N, -94.77W - 1988-10-19"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_88g0523_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: 22)
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) 20.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0 125.0 150.0 175.0 200.0 250.0 300.0 400.0 500.0 600.0 700.0 750.0 1000.0  m	21 options
temperature	= (ANY) 5.159999847412109 6.539999961853027 7.050000190734863 8.399999618530273 9.760000228881836 11.829999923706055 14.510000228881836 16.899999618530273 19.65999984741211 20.329999923706055 21.239999771118164 21.3799991607666 21.649999618530273 22.040000915527344 22.299999237060547 22.700000762939453 23.25 24.3799991607666 26.479999542236328 26.510000228881836  degree_C	20 options
salinity	= (ANY) 34.90299987792969 34.91899871826172 34.91999816894531 34.92100143432617 35.0369987487793 35.19300079345703 35.48899841308594 35.928001403808594 36.23699951171875 36.47700119018555 36.492000579833984 36.50699996948242 36.525001525878906 36.52899932861328 36.53200149536133 36.53300094604492 36.534000396728516 36.5369987487793 36.58000183105469 36.61000061035156 36.650001525878906  PSU	21 options
oxygen	= (ANY) 2.566999912261963 2.5829999446868896 2.6530001163482666 2.7279999256134033 2.9630000591278076 2.9660000801086426 3.0899999141693115 3.5889999866485596 3.947000026702881 3.9509999752044678 4.159999847412109 4.5329999923706055 4.579999923706055 4.670000076293945 4.686999797821045 4.693999767303467 4.806000232696533 4.8429999351501465 4.9070000648498535 5.0320000648498535 5.177000045776367 5.2170000076293945  milliliters per liter	22 options
nitrite	= (ANY) 0.009999999776482582 0.019999999552965164 0.03999999910593033 0.07000000029802322  micromols per liter	4 options
nitrate	= (ANY) 0.0 0.10000000149011612 0.800000011920929 2.0 4.199999809265137 7.699999809265137 14.899999618530273 18.799999237060547 24.799999237060547 27.899999618530273 28.0 28.700000762939453 30.5 31.0 31.399999618530273  micromols	15 options
phosphate	= (ANY) 0.009999999776482582 0.019999999552965164 0.03999999910593033 0.10000000149011612 0.2199999988079071 0.41999998688697815 0.8299999833106995 1.0800000429153442 1.5 1.7699999809265137 1.7999999523162842 1.8200000524520874 1.9299999475479126 2.0 2.009999990463257  micromols per liter	15 options
silicate	= (ANY) 0.0 0.07999999821186066 0.20000000298023224 0.4000000059604645 0.5 0.6000000238418579 0.800000011920929 1.7999999523162842 3.9000000953674316 6.5 10.600000381469727 14.800000190734863 18.399999618530273 22.5 23.899999618530273 26.299999237060547 26.600000381469727  micromols per liter	17 options
salinity2	= (ANY)  PSU	1 option:
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	PSU	milliliters per liter	micromols per liter	micromols	micromols per liter	micromols per liter	PSU
20.0	26.510000228881836	36.50699996948242	4.686999797821045	0.009999999776482582	0.10000000149011612	0.009999999776482582	0.5		0.0
40.0	26.479999542236328	36.61000061035156	4.670000076293945	0.009999999776482582	0.10000000149011612	0.009999999776482582	0.5		0.0
50.0	26.479999542236328	36.650001525878906	4.693999767303467	0.009999999776482582	0.10000000149011612	0.009999999776482582	0.800000011920929		0.0
60.0	24.3799991607666	36.58000183105469	5.177000045776367	0.009999999776482582	0.10000000149011612	0.009999999776482582	0.5		0.0
70.0	23.25	36.525001525878906	5.2170000076293945	0.009999999776482582	0.10000000149011612	0.009999999776482582	0.5		0.0
80.0	22.700000762939453	36.534000396728516	5.0320000648498535	0.009999999776482582	0.10000000149011612	0.009999999776482582	0.4000000059604645		0.0
90.0	22.299999237060547	36.53300094604492	4.9070000648498535	0.009999999776482582	0.10000000149011612	0.019999999552965164	0.20000000298023224		0.0
100.0	22.040000915527344	36.52899932861328	4.8429999351501465	0.009999999776482582	0.10000000149011612	0.019999999552965164	0.07999999821186066		0.0
110.0	21.649999618530273	36.53200149536133	4.806000232696533	0.07000000029802322	0.0	0.019999999552965164	0.0		0.0
125.0	21.3799991607666	36.5369987487793	4.579999923706055	0.03999999910593033	0.800000011920929	0.03999999910593033	0.20000000298023224		0.0
150.0	21.239999771118164	36.534000396728516	4.5329999923706055	0.019999999552965164	2.0	0.10000000149011612	0.20000000298023224		0.0
175.0	20.329999923706055	36.47700119018555	4.159999847412109	0.019999999552965164	4.199999809265137	0.2199999988079071	0.6000000238418579		0.0
200.0	19.65999984741211	36.492000579833984	3.5889999866485596	0.009999999776482582	7.699999809265137	0.41999998688697815	1.7999999523162842		0.0
250.0	16.899999618530273	36.23699951171875	2.7279999256134033	0.009999999776482582	14.899999618530273	0.8299999833106995	3.9000000953674316		0.0
300.0	14.510000228881836	35.928001403808594	2.5829999446868896	0.009999999776482582	18.799999237060547	1.0800000429153442	6.5		1.0
400.0	11.829999923706055	35.48899841308594	2.566999912261963	0.009999999776482582	24.799999237060547	1.5	10.600000381469727		1.0
500.0	9.760000228881836	35.19300079345703	2.6530001163482666	0.009999999776482582	28.700000762939453	1.7699999809265137	14.800000190734863		0.0
600.0	8.399999618530273	35.0369987487793	2.9630000591278076	0.019999999552965164	30.5	1.9299999475479126	18.399999618530273		0.0
700.0	7.050000190734863	34.91999816894531	2.9660000801086426	0.009999999776482582	31.399999618530273	2.009999990463257	22.5		0.0
750.0	6.539999961853027	34.90299987792969	3.0899999141693115	0.009999999776482582	31.0	2.0	23.899999618530273		0.0
1000.0	5.159999847412109	34.91899871826172	3.9509999752044678	0.009999999776482582	27.899999618530273	1.7999999523162842	26.299999237060547		0.0
1000.0	5.159999847412109	34.92100143432617	3.947000026702881	0.009999999776482582	28.0	1.8200000524520874	26.600000381469727		0.0

In total, there are 22 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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