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Dataset Title:	"Deepwater CTD - d93e032.bdo.nc - 27.92N, -90.51W - 1993-04-28"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93e032_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 8.0 23.0 48.0 59.0 68.0 88.0 107.0 148.0 246.0 347.0 489.0  m	12 options
temperature	= (ANY) 8.040599822998047 10.85509967803955 13.757100105285645 16.950199127197266 19.230600357055664 20.27280044555664 22.414100646972656 22.566299438476562 22.586200714111328 22.603300094604492 22.71660041809082 22.871000289916992  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 34.97060012817383 35.332298278808594 35.769798278808594 35.97140121459961 36.12080001831055 36.256500244140625 36.42369842529297 36.42639923095703 36.4718017578125 36.497398376464844 36.59989929199219 36.63029861450195  PSU	12 options
oxygen	= (ANY) 2.6500000953674316 2.7699999809265137 3.0999999046325684 3.2200000286102295 3.490000009536743 3.5199999809265137 4.550000190734863 4.860000133514404 4.880000114440918 4.889999866485596 4.900000095367432 4.929999828338623  milliliters per liter	12 options
nitrite	= (ANY) 0.0 0.019999999552965164 0.029999999329447746 0.09000000357627869 0.10999999940395355 0.23999999463558197  micromols	6 options
nitrate	= (ANY) 0.07000000029802322 0.10000000149011612 0.12999999523162842 0.1899999976158142 0.5799999833106995 6.699999809265137 7.809999942779541 12.630000114440918 19.360000610351562 25.8700008392334 30.190000534057617  micromols	11 options
phosphate	= (ANY) 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.07000000029802322 0.09000000357627869 0.3199999928474426 0.38999998569488525 0.699999988079071 1.1699999570846558 1.659999966621399 2.049999952316284  micromols	11 options
silicate	= (ANY) 1.100000023841858 1.1200000047683716 1.149999976158142 1.2599999904632568 1.409999966621399 1.559999942779541 2.509999990463257 2.8299999237060547 5.070000171661377 8.710000038146973 13.859999656677246 20.299999237060547  micromols	12 options
salinity2	= (ANY) 34.986000061035156 35.34299850463867 35.770999908447266 35.987998962402344 36.277000427246094 36.42399978637695 36.43899917602539 36.479000091552734 36.59600067138672 36.599998474121094 36.625  PSU	11 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	22.603300094604492	35.97140121459961	4.929999828338623	0.029999999329447746	0.1899999976158142	0.09000000357627869	1.559999942779541	35.987998962402344	0.0
8.0	22.71660041809082	36.12080001831055	4.900000095367432	0.019999999552965164	0.12999999523162842	0.07000000029802322	1.409999966621399	36.42399978637695	0.0
23.0	22.871000289916992	36.4718017578125	4.889999866485596	0.019999999552965164	0.10000000149011612	0.03999999910593033	1.2599999904632568	36.479000091552734	0.0
48.0	22.586200714111328	36.42639923095703	4.860000133514404	0.019999999552965164	0.10000000149011612	0.029999999329447746	1.149999976158142	36.43899917602539	0.0
59.0	22.566299438476562	36.42369842529297	4.880000114440918	0.019999999552965164	0.07000000029802322	0.019999999552965164	1.100000023841858	36.43899917602539	0.0
68.0	22.414100646972656	36.497398376464844	4.550000190734863	0.10999999940395355	0.5799999833106995	0.019999999552965164	1.1200000047683716	36.59600067138672	0.0
88.0	20.27280044555664	36.63029861450195	3.5199999809265137	0.23999999463558197	6.699999809265137	0.3199999928474426	2.509999990463257	36.625	0.0
107.0	19.230600357055664	36.59989929199219	3.490000009536743	0.09000000357627869	7.809999942779541	0.38999998569488525	2.8299999237060547	36.599998474121094	0.0
148.0	16.950199127197266	36.256500244140625	3.2200000286102295	0.0	12.630000114440918	0.699999988079071	5.070000171661377	36.277000427246094	0.0
246.0	13.757100105285645	35.769798278808594	3.0999999046325684	0.029999999329447746	19.360000610351562	1.1699999570846558	8.710000038146973	35.770999908447266	0.0
347.0	10.85509967803955	35.332298278808594	2.6500000953674316	0.029999999329447746	25.8700008392334	1.659999966621399	13.859999656677246	35.34299850463867	0.0
489.0	8.040599822998047	34.97060012817383	2.7699999809265137	0.029999999329447746	30.190000534057617	2.049999952316284	20.299999237060547	34.986000061035156	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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