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Dataset Title:	"Deepwater CTD - d92a003.bdo.nc - 27.8N, -94.19W - 1992-05-01"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d92a003_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) 1.0 14.0 29.0 39.0 48.0 58.0 74.0 88.0 118.0 158.0 197.0 237.0  m	12 options
temperature	= (ANY) 12.360799789428711 13.631999969482422 16.941699981689453 18.908700942993164 19.196800231933594 20.0841007232666 21.01140022277832 22.158700942993164 22.61479949951172 22.939800262451172 23.573200225830078 23.585599899291992  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 33.32780075073242 34.742698669433594 35.5718994140625 35.768001556396484 36.06760025024414 36.12839889526367 36.17530059814453 36.18280029296875 36.19499969482422 36.222599029541016 36.26060104370117 36.261199951171875  PSU	12 options
oxygen	= (ANY) 2.680000066757202 2.759999990463257 2.880000114440918 3.799999952316284 4.420000076293945 4.659999847412109 4.840000152587891 4.849999904632568 4.889999866485596 4.929999828338623 4.980000019073486  milliliters per liter	11 options
nitrite	= (ANY) 0.0 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.05999999865889549 0.07000000029802322 0.1899999976158142 0.30000001192092896  micromols	8 options
nitrate	= (ANY) 0.1899999976158142 0.2800000011920929 0.28999999165534973 0.33000001311302185 0.3700000047683716 0.6899999976158142 0.7599999904632568 3.059999942779541 6.579999923706055 14.880000114440918 20.520000457763672 23.09000015258789  micromols	12 options
phosphate	= (ANY) 0.0 0.009999999776482582 0.019999999552965164 0.03999999910593033 0.05999999865889549 0.07000000029802322 0.1599999964237213 0.3499999940395355 0.9700000286102295 1.2100000381469727 1.3799999952316284  micromols	11 options
silicate	= (ANY) 0.05999999865889549 0.23000000417232513 0.30000001192092896 0.6600000262260437 0.7300000190734863 0.7699999809265137 2.069999933242798 2.180000066757202 2.240000009536743 3.809999942779541 7.929999828338623 10.050000190734863  micromols	12 options
salinity2	= (ANY) 33.32899856567383 34.78300094604492 35.571998596191406 35.762001037597656 36.07500076293945 36.10300064086914 36.17399978637695 36.178001403808594 36.20000076293945 36.22200012207031 36.23699951171875 36.268001556396484  PSU	12 options
qualityFlag	= (ANY) 0.0	1 option: 0.0

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
1.0	23.585599899291992	33.32780075073242	4.980000019073486	0.009999999776482582	0.1899999976158142	0.0	2.240000009536743	33.32899856567383	0.0
14.0	23.573200225830078	34.742698669433594	4.929999828338623	0.0	0.28999999165534973	0.009999999776482582	2.180000066757202	34.78300094604492	0.0
29.0	22.939800262451172	36.06760025024414	4.889999866485596	0.0	0.2800000011920929	0.009999999776482582	0.7699999809265137	36.07500076293945	0.0
39.0	22.61479949951172	36.18280029296875	4.849999904632568	0.0	0.33000001311302185	0.019999999552965164	0.23000000417232513	36.20000076293945	0.0
48.0	22.158700942993164	36.222599029541016	4.659999847412109	0.05999999865889549	0.3700000047683716	0.03999999910593033	0.30000001192092896	36.22200012207031	0.0
58.0	21.01140022277832	36.12839889526367	4.659999847412109	0.1899999976158142	0.6899999976158142	0.05999999865889549	0.6600000262260437	36.10300064086914	0.0
74.0	20.0841007232666	36.19499969482422	4.840000152587891	0.30000001192092896	0.7599999904632568	0.07000000029802322	0.05999999865889549	36.17399978637695	0.0
88.0	19.196800231933594	36.17530059814453	4.420000076293945	0.07000000029802322	3.059999942779541	0.1599999964237213	0.7300000190734863	36.178001403808594	0.0
118.0	18.908700942993164	36.261199951171875	3.799999952316284	0.029999999329447746	6.579999923706055	0.3499999940395355	2.069999933242798	36.268001556396484	0.0
158.0	16.941699981689453	36.26060104370117	2.880000114440918	0.029999999329447746	14.880000114440918	0.9700000286102295	3.809999942779541	36.23699951171875	0.0
197.0	13.631999969482422	35.768001556396484	2.759999990463257	0.029999999329447746	20.520000457763672	1.2100000381469727	7.929999828338623	35.762001037597656	0.0
237.0	12.360799789428711	35.5718994140625	2.680000066757202	0.019999999552965164	23.09000015258789	1.3799999952316284	10.050000190734863	35.571998596191406	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.
 

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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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