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Dataset Title:	"Deepwater CTD - d93f096.bdo.nc - 27.66N, -94.22W - 1993-00-01"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93f096_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 7.0 14.0 24.0 39.0 53.0 68.0 99.0 137.0 189.0 288.0 388.0  m	12 options
temperature	= (ANY) 9.877300262451172 12.13659954071045 15.022299766540527 16.688899993896484 18.230600357055664 20.196800231933594 21.76259994506836 25.031200408935547 28.512300491333008 29.755599975585938 29.91119956970215 30.27669906616211  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 34.826900482177734 35.0984992980957 35.21860122680664 35.43389892578125 35.537498474121094 35.9838981628418 36.163299560546875 36.24610137939453 36.25170135498047 36.29349899291992 36.312801361083984 36.404998779296875  PSU	12 options
oxygen	= (ANY) 2.609999895095825 2.690000057220459 2.880000114440918 3.049999952316284 3.240000009536743 3.7200000286102295 4.570000171661377 4.590000152587891 4.710000038146973 4.769999980926514 4.900000095367432 4.909999847412109  milliliters per liter	12 options
nitrite	= (ANY) 0.009999999776482582 0.019999999552965164 0.03999999910593033 0.10000000149011612  micromols	4 options
nitrate	= (ANY) 0.14000000059604645 0.1599999964237213 0.17000000178813934 0.18000000715255737 0.1899999976158142 4.929999828338623 11.779999732971191 12.989999771118164 17.270000457763672 23.200000762939453 27.520000457763672  micromols	11 options
phosphate	= (ANY) 0.0 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.27000001072883606 0.6399999856948853 0.7400000095367432 1.0099999904632568 1.409999966621399 1.7100000381469727  micromols	10 options
silicate	= (ANY) 1.8600000143051147 1.9800000190734863 2.009999990463257 2.2300000190734863 2.2899999618530273 2.5199999809265137 3.549999952316284 5.039999961853027 6.489999771118164 7.289999961853027 11.09000015258789 15.710000038146973  micromols	12 options
salinity2	= (ANY) 34.80699920654297 35.159000396728516 35.2130012512207 35.53099822998047 35.821998596191406 35.97700119018555 36.198001861572266 36.23899841308594 36.24399948120117 36.292999267578125 36.38999938964844 36.39799880981445  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	30.27669906616211	34.826900482177734	4.570000171661377	0.009999999776482582	0.1899999976158142	0.009999999776482582	2.5199999809265137	34.80699920654297	0.0
7.0	29.91119956970215	35.0984992980957	4.590000152587891	0.009999999776482582	0.18000000715255737	0.019999999552965164	2.2899999618530273	35.159000396728516	0.0
14.0	29.755599975585938	35.43389892578125	4.710000038146973	0.009999999776482582	0.17000000178813934	0.029999999329447746	2.2300000190734863	35.821998596191406	0.0
24.0	28.512300491333008	36.163299560546875	4.909999847412109	0.009999999776482582	0.1599999964237213	0.0	1.9800000190734863	36.198001861572266	0.0
39.0	25.031200408935547	36.312801361083984	4.900000095367432	0.009999999776482582	0.1599999964237213	0.0	1.8600000143051147	36.38999938964844	0.0
53.0	21.76259994506836	36.24610137939453	4.769999980926514	0.009999999776482582	0.14000000059604645	0.019999999552965164	2.009999990463257	36.23899841308594	0.0
68.0	20.196800231933594	36.29349899291992	3.7200000286102295	0.10000000149011612	4.929999828338623	0.27000001072883606	3.549999952316284	36.292999267578125	0.0
99.0	18.230600357055664	36.404998779296875	3.049999952316284	0.03999999910593033	11.779999732971191	0.6399999856948853	6.489999771118164	36.39799880981445	0.0
137.0	16.688899993896484	36.25170135498047	3.240000009536743	0.009999999776482582	12.989999771118164	0.7400000095367432	5.039999961853027	36.24399948120117	0.0
189.0	15.022299766540527	35.9838981628418	2.880000114440918	0.009999999776482582	17.270000457763672	1.0099999904632568	7.289999961853027	35.97700119018555	0.0
288.0	12.13659954071045	35.537498474121094	2.690000057220459	0.009999999776482582	23.200000762939453	1.409999966621399	11.09000015258789	35.53099822998047	0.0
388.0	9.877300262451172	35.21860122680664	2.609999895095825	0.019999999552965164	27.520000457763672	1.7100000381469727	15.710000038146973	35.2130012512207	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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