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Dataset Title:	"Deepwater CTD - d94h020.bdo.nc - 27.86N, -90.5W - 1994-04-26"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94h020_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 20.0 40.0 72.0 85.0 106.0 140.0 176.0 253.0 323.0 457.0 650.0  m	12 options
temperature	= (ANY) 6.065499782562256 9.812899589538574 12.04699993133545 14.40719985961914 17.121599197387695 18.461999893188477 19.24449920654297 19.608600616455078 19.924800872802734 21.964599609375 23.237699508666992 24.88960075378418  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 34.89659881591797 35.1953010559082 35.509498596191406 35.87670135498047 36.17279815673828 36.19219970703125 36.19300079345703 36.21110153198242 36.261600494384766 36.280601501464844 36.31639862060547 36.38589859008789  PSU	12 options
oxygen	= (ANY) 2.680000066757202 2.809999942779541 2.990000009536743 3.0799999237060547 3.359999895095825 3.4800000190734863 4.610000133514404 4.670000076293945 4.849999904632568 4.929999828338623 5.03000020980835 5.130000114440918  milliliters per liter	12 options
nitrite	= (ANY) 0.0 0.009999999776482582 0.029999999329447746 0.03999999910593033 0.07000000029802322 0.1899999976158142  micromols	6 options
nitrate	= (ANY) 0.3199999928474426 0.33000001311302185 0.44999998807907104 1.2599999904632568 2.490000009536743 3.430000066757202 9.319999694824219 12.640000343322754 18.3799991607666 23.530000686645508 28.06999969482422 30.549999237060547  micromols	12 options
phosphate	= (ANY) 0.009999999776482582 0.019999999552965164 0.05000000074505806 0.10999999940395355 0.1599999964237213 0.4699999988079071 0.7099999785423279 1.0399999618530273 1.3799999952316284 1.690000057220459 1.9299999475479126  micromols	11 options
silicate	= (ANY) 1.909999966621399 1.9500000476837158 2.3499999046325684 2.7100000381469727 2.9800000190734863 4.420000076293945 5.730000019073486 8.479999542236328 12.40999984741211 16.799999237060547 26.040000915527344  micromols	11 options
salinity2	= (ANY) 34.89899826049805 35.194000244140625 35.505001068115234 35.86899948120117 36.178001403808594 36.1870002746582 36.198001861572266 36.20800018310547 36.26900100708008 36.277000427246094 36.32099914550781 36.374000549316406  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	24.88960075378418	36.31639862060547	4.849999904632568	0.0	0.33000001311302185	0.019999999552965164	2.7100000381469727	36.32099914550781	0.0
20.0	23.237699508666992	36.17279815673828	5.03000020980835	0.0	0.3199999928474426	0.009999999776482582	1.9500000476837158	36.178001403808594	0.0
40.0	21.964599609375	36.261600494384766	5.130000114440918	0.009999999776482582	1.2599999904632568	0.009999999776482582	1.909999966621399	36.26900100708008	0.0
72.0	19.924800872802734	36.19300079345703	4.929999828338623	0.1899999976158142	2.490000009536743	0.05000000074505806	2.3499999046325684	36.1870002746582	0.0
85.0	19.608600616455078	36.19219970703125	4.670000076293945	0.07000000029802322	3.430000066757202	0.10999999940395355	2.7100000381469727	36.198001861572266	0.0
106.0	19.24449920654297	36.21110153198242	4.610000133514404	0.03999999910593033	9.319999694824219	0.1599999964237213	2.9800000190734863	36.20800018310547	0.0
140.0	18.461999893188477	36.38589859008789	3.4800000190734863	0.029999999329447746	12.640000343322754	0.4699999988079071	4.420000076293945	36.374000549316406	0.0
176.0	17.121599197387695	36.280601501464844	3.0799999237060547	0.029999999329447746	18.3799991607666	0.7099999785423279	5.730000019073486	36.277000427246094	0.0
253.0	14.40719985961914	35.87670135498047	2.990000009536743	0.029999999329447746	23.530000686645508	1.0399999618530273	8.479999542236328	35.86899948120117	0.0
323.0	12.04699993133545	35.509498596191406	2.809999942779541	0.029999999329447746	28.06999969482422	1.3799999952316284	12.40999984741211	35.505001068115234	0.0
457.0	9.812899589538574	35.1953010559082	2.680000066757202	0.029999999329447746	30.549999237060547	1.690000057220459	16.799999237060547	35.194000244140625	0.0
650.0	6.065499782562256	34.89659881591797	3.359999895095825	0.029999999329447746	0.44999998807907104	1.9299999475479126	26.040000915527344	34.89899826049805	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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