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Dataset Title:	"Deepwater CTD - d92b102.bdo.nc - 27.66N, -93.0W - 1992-00-07"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d92b102_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) 0.0 24.0 44.0 58.0 66.0 78.0 98.0 123.0 148.0 197.0 247.0 306.0  m	12 options
temperature	= (ANY) 11.854900360107422 13.321100234985352 14.558199882507324 16.114999771118164 17.340499877929688 18.72879981994629 20.259899139404297 21.0137996673584 21.95240020751953 23.761699676513672 28.116500854492188 30.5575008392334  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 33.68510055541992 35.49100112915039 35.715301513671875 35.910400390625 36.12969970703125 36.142799377441406 36.311500549316406 36.43659973144531 36.44200134277344 36.46590042114258 36.50339889526367 36.537498474121094  PSU	12 options
oxygen	= (ANY) 2.630000114440918 2.700000047683716 2.7799999713897705 2.809999942779541 2.8399999141693115 3.009999990463257 3.5899999141693115 4.21999979019165 4.519999980926514 4.559999942779541 4.889999866485596 4.960000038146973  milliliters per liter	12 options
nitrite	= (ANY) 0.0 0.009999999776482582 0.07999999821186066 0.09000000357627869 0.10000000149011612 0.1599999964237213 0.1899999976158142 0.2199999988079071 0.23999999463558197 0.28999999165534973  micromols	10 options
nitrate	= (ANY) 0.75 1.0 1.0700000524520874 1.5099999904632568 3.109999895095825 7.610000133514404 12.829999923706055 15.819999694824219 17.440000534057617 19.59000015258789 21.899999618530273 24.479999542236328  micromols	12 options
phosphate	= (ANY) 0.0 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.05999999865889549 0.3199999928474426 0.6100000143051147 0.7900000214576721 0.949999988079071 1.1299999952316284 1.3200000524520874 1.5099999904632568  micromols	12 options
silicate	= (ANY) 0.20000000298023224 0.47999998927116394 0.5699999928474426 0.6499999761581421 1.5 1.6100000143051147 3.0999999046325684 4.130000114440918 5.28000020980835 6.949999809265137 8.739999771118164 11.0  micromols	12 options
salinity2	= (ANY) 33.98099899291992 35.492000579833984 35.69499969482422 35.895999908447266 36.10900115966797 36.15800094604492 36.2869987487793 36.41400146484375 36.43199920654297 36.44499969482422 36.486000061035156 36.507999420166016  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
0.0	30.5575008392334	33.68510055541992	4.519999980926514	0.09000000357627869	0.75	0.009999999776482582	1.6100000143051147	33.98099899291992	0.0
24.0	28.116500854492188	36.12969970703125	4.960000038146973	0.009999999776482582	1.0	0.0	0.47999998927116394	36.15800094604492	0.0
44.0	23.761699676513672	36.44200134277344	4.889999866485596	0.0	1.0700000524520874	0.019999999552965164	0.20000000298023224	36.43199920654297	0.0
58.0	21.95240020751953	36.50339889526367	4.559999942779541	0.009999999776482582	1.5099999904632568	0.029999999329447746	0.5699999928474426	36.486000061035156	0.0
66.0	21.0137996673584	36.46590042114258	4.21999979019165	0.23999999463558197	3.109999895095825	0.05999999865889549	0.6499999761581421	36.44499969482422	0.0
78.0	20.259899139404297	36.537498474121094	3.5899999141693115	0.1599999964237213	7.610000133514404	0.3199999928474426	1.5	36.507999420166016	0.0
98.0	18.72879981994629	36.43659973144531	3.009999990463257	0.07999999821186066	12.829999923706055	0.6100000143051147	3.0999999046325684	36.41400146484375	0.0
123.0	17.340499877929688	36.311500549316406	2.7799999713897705	0.09000000357627869	15.819999694824219	0.7900000214576721	4.130000114440918	36.2869987487793	0.0
148.0	16.114999771118164	36.142799377441406	2.8399999141693115	0.10000000149011612	17.440000534057617	0.949999988079071	5.28000020980835	36.10900115966797	0.0
197.0	14.558199882507324	35.910400390625	2.809999942779541	0.1899999976158142	19.59000015258789	1.1299999952316284	6.949999809265137	35.895999908447266	0.0
247.0	13.321100234985352	35.715301513671875	2.700000047683716	0.2199999988079071	21.899999618530273	1.3200000524520874	8.739999771118164	35.69499969482422	0.0
306.0	11.854900360107422	35.49100112915039	2.630000114440918	0.28999999165534973	24.479999542236328	1.5099999904632568	11.0	35.492000579833984	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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