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Dataset Title:	"Deepwater CTD - d92a098.bdo.nc - 27.66N, -93.0W - 1992-05-00"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d92a098_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 28.0 44.0 58.0 74.0 87.0 103.0 128.0 138.0 158.0 207.0 285.0  m	12 options
temperature	= (ANY) 11.367799758911133 14.879799842834473 16.222000122070312 17.227500915527344 17.5403995513916 19.21929931640625 19.643600463867188 20.35110092163086 20.66819953918457 20.885400772094727 22.37339973449707 22.715999603271484  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 35.420799255371094 35.62730026245117 35.767799377441406 35.95719909667969 36.17250061035156 36.195899963378906 36.24760055541992 36.26089859008789 36.261600494384766 36.29290008544922 36.30459976196289 36.332801818847656  PSU	12 options
oxygen	= (ANY) 2.6700000762939453 2.8299999237060547 2.9100000858306885 2.930000066757202 2.9800000190734863 4.070000171661377 4.489999771118164 4.980000019073486 5.019999980926514 5.079999923706055 5.139999866485596 5.170000076293945  milliliters per liter	12 options
nitrite	= (ANY) 0.0 0.009999999776482582 0.03999999910593033 0.07000000029802322 0.07999999821186066 0.09000000357627869 0.10000000149011612 0.10999999940395355 0.11999999731779099  micromols	9 options
nitrate	= (ANY) 0.5699999928474426 0.6200000047683716 0.6499999761581421 0.6600000262260437 3.0299999713897705 5.46999979019165 14.069999694824219 14.6899995803833 15.479999542236328 18.770000457763672 25.030000686645508  micromols	11 options
phosphate	= (ANY) 0.07000000029802322 0.07999999821186066 0.09000000357627869 0.1899999976158142 0.30000001192092896 0.75 0.7900000214576721 0.8299999833106995 1.059999942779541 1.5299999713897705  micromols	10 options
silicate	= (ANY) 1.559999942779541 1.649999976158142 1.9199999570846558 2.559999942779541 2.569999933242798 2.9800000190734863 3.1700000762939453 5.400000095367432 5.940000057220459 6.170000076293945 8.600000381469727 13.75  micromols	12 options
salinity2	= (ANY) 35.42300033569336 35.62699890136719 35.816001892089844 35.95500183105469 36.19300079345703 36.20899963378906 36.25299835205078 36.26300048828125 36.263999938964844 36.290000915527344 36.29899978637695 36.32899856567383  PSU	12 options
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 (potential temperature from ctd)	PSU	milliliters per liter	micromols	micromols	micromols	micromols	PSU
0.0	22.715999603271484	35.62730026245117	5.019999980926514	0.009999999776482582	0.6499999761581421	0.07999999821186066	2.9800000190734863	35.62699890136719	0.0
28.0	22.37339973449707	35.767799377441406	5.079999923706055	0.0	0.5699999928474426	0.07000000029802322	2.559999942779541	35.816001892089844	0.0
44.0	20.885400772094727	36.195899963378906	5.170000076293945	0.0	0.6200000047683716	0.07000000029802322	1.9199999570846558	36.19300079345703	0.0
58.0	20.66819953918457	36.24760055541992	5.139999866485596	0.0	0.5699999928474426	0.07000000029802322	1.649999976158142	36.25299835205078	0.0
74.0	20.35110092163086	36.261600494384766	4.980000019073486	0.03999999910593033	0.6600000262260437	0.09000000357627869	1.559999942779541	36.263999938964844	0.0
87.0	19.643600463867188	36.26089859008789	4.489999771118164	0.10999999940395355	3.0299999713897705	0.1899999976158142	2.569999933242798	36.26300048828125	0.0
103.0	19.21929931640625	36.30459976196289	4.070000171661377	0.07000000029802322	5.46999979019165	0.30000001192092896	3.1700000762939453	36.29899978637695	0.0
128.0	17.5403995513916	36.332801818847656	2.930000066757202	0.07999999821186066	14.069999694824219	0.75	5.400000095367432	36.32899856567383	0.0
138.0	17.227500915527344	36.29290008544922	2.9100000858306885	0.07999999821186066	14.6899995803833	0.7900000214576721	5.940000057220459	36.290000915527344	0.0
158.0	16.222000122070312	36.17250061035156	2.9800000190734863	0.09000000357627869	15.479999542236328	0.8299999833106995	6.170000076293945	36.20899963378906	1.0
207.0	14.879799842834473	35.95719909667969	2.8299999237060547	0.10000000149011612	18.770000457763672	1.059999942779541	8.600000381469727	35.95500183105469	0.0
285.0	11.367799758911133	35.420799255371094	2.6700000762939453	0.11999999731779099	25.030000686645508	1.5299999713897705	13.75	35.42300033569336	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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