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Dataset Title:	"Deepwater CTD - d92b053.bdo.nc - 27.97N, -91.33W - 1992-00-04"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d92b053_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 28.0 44.0 53.0 64.0 73.0 98.0 123.0 148.0 197.0 258.0  m	12 options
temperature	= (ANY) 12.968500137329102 15.06659984588623 16.414899826049805 17.328500747680664 18.902099609375 19.97170066833496 20.491300582885742 21.75200080871582 23.243799209594727 26.30660057067871 29.92300033569336 30.0802001953125  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 31.958499908447266 34.93109893798828 35.66310119628906 35.990501403808594 36.04199981689453 36.170501708984375 36.19219970703125 36.193599700927734 36.198001861572266 36.23529815673828 36.324501037597656 36.41310119628906  PSU	12 options
oxygen	= (ANY) 2.799999952316284 2.9200000762939453 2.990000009536743 3.0999999046325684 3.2200000286102295 4.190000057220459 4.550000190734863 4.619999885559082 4.730000019073486 5.079999923706055 5.099999904632568 5.150000095367432  milliliters per liter	12 options
nitrite	= (ANY) 0.0 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.05000000074505806 0.12999999523162842  micromols	6 options
nitrate	= (ANY) 0.07999999821186066 0.11999999731779099 0.12999999523162842 0.14000000059604645 0.30000001192092896 2.509999990463257 9.600000381469727 12.550000190734863 14.539999961853027 17.360000610351562 20.739999771118164  micromols	11 options
phosphate	= (ANY) 0.019999999552965164 0.03999999910593033 0.05000000074505806 0.07000000029802322 0.18000000715255737 0.5299999713897705 0.7200000286102295 0.8600000143051147 1.0399999618530273 1.2799999713897705  micromols	10 options
silicate	= (ANY) 0.18000000715255737 0.3199999928474426 0.38999998569488525 0.9300000071525574 1.2000000476837158 1.4199999570846558 2.359999895095825 3.240000009536743 4.130000114440918 5.760000228881836 8.270000457763672  micromols	11 options
salinity2	= (ANY) 32.52199935913086 35.11399841308594 35.680999755859375 35.94599914550781 36.07400131225586 36.154998779296875 36.16600036621094 36.16999816894531 36.19599914550781 36.21200180053711 36.301998138427734 36.404998779296875  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	29.92300033569336	31.958499908447266	4.550000190734863	0.009999999776482582	0.07999999821186066	0.019999999552965164	1.4199999570846558	32.52199935913086	0.0
8.0	30.0802001953125	34.93109893798828	4.619999885559082	0.0	0.11999999731779099	0.03999999910593033	0.9300000071525574	35.11399841308594	0.0
28.0	26.30660057067871	36.04199981689453	5.079999923706055	0.0	0.11999999731779099	0.03999999910593033	0.18000000715255737	36.07400131225586	0.0
44.0	23.243799209594727	36.198001861572266	5.150000095367432	0.0	0.12999999523162842	0.05000000074505806	0.3199999928474426	36.19599914550781	0.0
53.0	21.75200080871582	36.19219970703125	5.099999904632568	0.0	0.14000000059604645	0.05000000074505806	0.38999998569488525	36.16600036621094	0.0
64.0	20.491300582885742	36.170501708984375	4.730000019073486	0.05000000074505806	0.30000001192092896	0.07000000029802322	0.38999998569488525	36.154998779296875	0.0
73.0	19.97170066833496	36.23529815673828	4.190000057220459	0.12999999523162842	2.509999990463257	0.18000000715255737	1.2000000476837158	36.21200180053711	0.0
98.0	18.902099609375	36.41310119628906	3.2200000286102295	0.029999999329447746	9.600000381469727	0.5299999713897705	2.359999895095825	36.404998779296875	0.0
123.0	17.328500747680664	36.324501037597656	3.0999999046325684	0.019999999552965164	12.550000190734863	0.7200000286102295	3.240000009536743	36.301998138427734	0.0
148.0	16.414899826049805	36.193599700927734	2.990000009536743	0.009999999776482582	14.539999961853027	0.8600000143051147	4.130000114440918	36.16999816894531	0.0
197.0	15.06659984588623	35.990501403808594	2.9200000762939453	0.009999999776482582	17.360000610351562	1.0399999618530273	5.760000228881836	35.94599914550781	0.0
258.0	12.968500137329102	35.66310119628906	2.799999952316284	0.019999999552965164	20.739999771118164	1.2799999713897705	8.270000457763672	35.680999755859375	1.0

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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