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Dataset Title:	"Deepwater CTD - d94h120.bdo.nc - 27.46N, -95.7W - 1994-05-03"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94h120_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 25.0 34.0 49.0 59.0 69.0 78.0 104.0 233.0 313.0 411.0 702.0  m	12 options
temperature	= (ANY) 6.073400020599365 9.909500122070312 12.041500091552734 14.171899795532227 18.55739974975586 19.619800567626953 19.659700393676758 19.8262996673584 20.43560028076172 21.154600143432617 21.96660041809082 24.320499420166016  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 31.204099655151367 34.900001525878906 35.21860122680664 35.5177001953125 35.741600036621094 35.84239959716797 35.94620132446289 36.06769943237305 36.09479904174805 36.164100646972656 36.361900329589844 36.44419860839844  PSU	12 options
oxygen	= (ANY) 2.5799999237060547 2.630000114440918 2.7799999713897705 2.9800000190734863 3.3399999141693115 3.5799999237060547 4.199999809265137 4.369999885559082 4.550000190734863 5.050000190734863 5.090000152587891 5.170000076293945  milliliters per liter	12 options
nitrite	= (ANY) 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.09000000357627869 0.14000000059604645 0.15000000596046448  micromols	6 options
nitrate	= (ANY) 0.10000000149011612 0.15000000596046448 0.23999999463558197 2.450000047683716 3.2100000381469727 6.679999828338623 11.229999542236328 19.239999771118164 23.559999465942383 27.75 29.68000030517578  micromols	11 options
phosphate	= (ANY) 0.05999999865889549 0.07000000029802322 0.07999999821186066 0.17000000178813934 0.2199999988079071 0.3799999952316284 0.6100000143051147 1.149999976158142 1.4500000476837158 1.75 1.9900000095367432  micromols	11 options
silicate	= (ANY) 1.7100000381469727 1.8700000047683716 2.200000047683716 2.5999999046325684 3.2699999809265137 3.4000000953674316 3.8499999046325684 4.78000020980835 9.0600004196167 12.420000076293945 16.639999389648438 26.299999237060547  micromols	12 options
salinity2	= (ANY) 31.23900032043457 34.90399932861328 35.224998474121094 35.52199935913086 35.71500015258789 35.8489990234375 35.96799850463867 36.097999572753906 36.104000091552734 36.189998626708984 36.356998443603516 36.45399856567383  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
1.0	24.320499420166016	31.204099655151367	5.050000190734863	0.029999999329447746	0.23999999463558197	0.07999999821186066	1.7100000381469727	31.23900032043457	0.0
25.0	21.96660041809082	35.741600036621094	5.170000076293945	0.019999999552965164	0.10000000149011612	0.05999999865889549	2.200000047683716	35.71500015258789	0.0
34.0	21.154600143432617	35.94620132446289	5.090000152587891	0.029999999329447746	0.15000000596046448	0.07000000029802322	1.8700000047683716	35.96799850463867	0.0
49.0	20.43560028076172	36.06769943237305	4.199999809265137	0.14000000059604645	3.2100000381469727	0.2199999988079071	3.4000000953674316	36.097999572753906	0.0
59.0	19.8262996673584	36.09479904174805	4.369999885559082	0.09000000357627869	3.2100000381469727	0.2199999988079071	3.2699999809265137	36.104000091552734	0.0
69.0	19.659700393676758	36.164100646972656	4.550000190734863	0.15000000596046448	2.450000047683716	0.17000000178813934	2.5999999046325684	36.189998626708984	0.0
78.0	19.619800567626953	36.361900329589844	3.5799999237060547	0.15000000596046448	6.679999828338623	0.3799999952316284	3.8499999046325684	36.356998443603516	0.0
104.0	18.55739974975586	36.44419860839844	2.9800000190734863	0.03999999910593033	11.229999542236328	0.6100000143051147	4.78000020980835	36.45399856567383	0.0
233.0	14.171899795532227	35.84239959716797	2.7799999713897705	0.019999999552965164	19.239999771118164	1.149999976158142	9.0600004196167	35.8489990234375	0.0
313.0	12.041500091552734	35.5177001953125	2.630000114440918	0.019999999552965164	23.559999465942383	1.4500000476837158	12.420000076293945	35.52199935913086	0.0
411.0	9.909500122070312	35.21860122680664	2.5799999237060547	0.029999999329447746	27.75	1.75	16.639999389648438	35.224998474121094	1.0
702.0	6.073400020599365	34.900001525878906	3.3399999141693115	0.029999999329447746	29.68000030517578	1.9900000095367432	26.299999237060547	34.90399932861328	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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