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Dataset Title:	"Deepwater CTD - d94j159.bdo.nc - 26.93N, -96.44W - 1994-11-12"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94j159_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 19.0 39.0 62.0 73.0 92.0 104.0 115.0 123.0 148.0 173.0 205.0  m	12 options
temperature	= (ANY) 14.936400413513184 15.735600471496582 17.056400299072266 18.67530059814453 19.592500686645508 20.67650032043457 22.291500091552734 23.65839958190918 26.30769920349121 26.331199645996094 26.340700149536133 26.353500366210938  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 35.9744987487793 36.09270095825195 36.27259826660156 36.272701263427734 36.27370071411133 36.27450180053711 36.27519989013672 36.368099212646484 36.378501892089844 36.38690185546875 36.410499572753906 36.42399978637695  PSU	12 options
oxygen	= (ANY) 2.680000066757202 2.7200000286102295 2.880000114440918 2.890000104904175 3.0999999046325684 3.700000047683716 4.320000171661377 4.610000133514404 4.630000114440918 4.659999847412109 4.789999961853027 4.869999885559082  milliliters per liter	12 options
nitrite	= (ANY) 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.14000000059604645  micromols	6 options
nitrate	= (ANY) 0.05999999865889549 0.07999999821186066 0.09000000357627869 0.17000000178813934 1.4299999475479126 5.46999979019165 8.569999694824219 11.930000305175781 15.229999542236328 16.81999969482422  micromols	10 options
phosphate	= (ANY) 0.019999999552965164 0.029999999329447746 0.05000000074505806 0.05999999865889549 0.1899999976158142 0.4000000059604645 0.5600000023841858 0.7300000190734863 0.949999988079071 1.0499999523162842  micromols	10 options
silicate	= (ANY) 0.07999999821186066 0.5199999809265137 0.6399999856948853 0.800000011920929 0.8799999952316284 1.0299999713897705 1.4299999475479126 2.549999952316284 2.9100000858306885 3.940000057220459 6.050000190734863 6.730000019073486  micromols	12 options
salinity2	= (ANY) 35.96699905395508 36.0890007019043 36.26499938964844 36.268001556396484 36.27899932861328 36.30699920654297 36.36199951171875 36.369998931884766 36.37699890136719 36.40299987792969 36.43600082397461  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
1.0	26.353500366210938	36.272701263427734	4.630000114440918	0.009999999776482582	0.17000000178813934	0.05000000074505806	1.0299999713897705	36.26499938964844	0.0
19.0	26.340700149536133	36.27259826660156	4.659999847412109	0.009999999776482582	0.09000000357627869	0.029999999329447746	0.8799999952316284	36.26499938964844	0.0
39.0	26.331199645996094	36.27370071411133	4.610000133514404	0.009999999776482582	0.09000000357627869	0.019999999552965164	0.800000011920929	36.268001556396484	0.0
62.0	26.30769920349121	36.27450180053711	4.789999961853027	0.009999999776482582	0.09000000357627869	0.019999999552965164	0.5199999809265137	36.30699920654297	0.0
73.0	23.65839958190918	36.378501892089844	4.869999885559082	0.05000000074505806	0.07999999821186066	0.019999999552965164	0.07999999821186066	36.369998931884766	0.0
92.0	22.291500091552734	36.368099212646484	4.320000171661377	0.14000000059604645	0.05999999865889549	0.05999999865889549	0.6399999856948853	36.36199951171875	0.0
104.0	20.67650032043457	36.38690185546875	3.700000047683716	0.03999999910593033	1.4299999475479126	0.1899999976158142	1.4299999475479126	36.37699890136719	0.0
115.0	19.592500686645508	36.410499572753906	3.0999999046325684	0.029999999329447746	5.46999979019165	0.4000000059604645	2.549999952316284	36.40299987792969	0.0
123.0	18.67530059814453	36.42399978637695	2.880000114440918	0.019999999552965164	8.569999694824219	0.5600000023841858	2.9100000858306885	36.43600082397461	0.0
148.0	17.056400299072266	36.27519989013672	2.890000104904175	0.009999999776482582	11.930000305175781	0.7300000190734863	3.940000057220459	36.27899932861328	0.0
173.0	15.735600471496582	36.09270095825195	2.680000066757202	0.019999999552965164	15.229999542236328	0.949999988079071	6.050000190734863	36.0890007019043	0.0
205.0	14.936400413513184	35.9744987487793	2.7200000286102295	0.03999999910593033	16.81999969482422	1.0499999523162842	6.730000019073486	35.96699905395508	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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