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Dataset Title:	"Deepwater CTD - 89g1507b.ctd.nc - 27.58N, -93.61W - 1989-11-13"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_89g1507b_ctd)
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: 82)
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) 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 20.0 21.0 22.0 23.0 24.0 25.0 26.0 27.0 28.0 29.0 30.0 31.0 32.0 33.0 34.0 35.0 36.0 37.0 38.0 39.0 40.0 41.0 42.0 43.0 44.0 45.0 46.0 47.0 48.0 49.0 50.0 51.0 52.0 53.0 54.0 55.0 56.0 57.0 58.0 59.0 60.0 61.0 62.0 63.0 64.0 65.0 66.0 67.0 68.0 69.0 70.0 71.0 72.0 73.0 74.0 75.0 76.0 77.0 78.0 79.0 80.0 81.0 82.0 83.0 84.0 85.0 86.0 87.0  m	82 options
temperature	= (ANY) 22.62070083618164 22.710599899291992 22.72130012512207 22.749799728393555 22.836599349975586 23.09630012512207 23.098899841308594 23.219499588012695 23.29840087890625 23.396299362182617 23.41830062866211 23.556499481201172 23.74880027770996 23.995399475097656 24.042400360107422 24.21109962463379 24.497400283813477 24.846599578857422 25.014400482177734 25.10260009765625 25.13719940185547 25.165300369262695 25.194900512695312 25.20159912109375 25.228200912475586 25.313499450683594 25.37579917907715 25.437000274658203 25.445100784301758 25.45009994506836 25.46660041809082 25.469200134277344 25.470800399780273 25.472400665283203 25.473100662231445 25.47319984436035 25.47410011291504 25.474300384521484 25.478700637817383 25.481000900268555 25.530799865722656 25.579700469970703 25.624399185180664 25.635900497436523 25.642200469970703 25.647899627685547 25.65180015563965 25.65239906311035 25.658000946044922 25.665700912475586 25.666000366210938 25.666200637817383 25.66670036315918 25.666799545288086 25.666900634765625 25.667400360107422 25.667600631713867 25.667800903320312 25.66790008544922 25.66819953918457 25.66830062866211 25.668399810791016 25.669099807739258 25.669300079345703 25.66939926147461 25.66950035095215 25.669700622558594 25.670000076293945 25.67020034790039 25.670400619506836 25.670900344848633 25.67140007019043 25.671499252319336 25.672300338745117 25.672399520874023  degree_C	75 options
salinity	= (ANY) 36.356300354003906 36.35639953613281 36.35649871826172 36.35660171508789 36.3567008972168 36.3568000793457 36.35689926147461 36.356998443603516 36.35710144042969 36.3572998046875 36.35749816894531 36.357601165771484 36.358001708984375 36.3583984375 36.358699798583984 36.359901428222656 36.360599517822266 36.36149978637695 36.36249923706055 36.36539840698242 36.37110137939453 36.3745002746582 36.374900817871094 36.37739944458008 36.37919998168945 36.38100051879883 36.38349914550781 36.390499114990234 36.39569854736328 36.39680099487305 36.397499084472656 36.39870071411133 36.400901794433594 36.40299987792969 36.40380096435547 36.407798767089844 36.409000396728516 36.40919876098633 36.4109992980957 36.41279983520508 36.41569900512695 36.41740036010742 36.41899871826172 36.423301696777344 36.427799224853516 36.43050003051758 36.43109893798828 36.43119812011719 36.43230056762695 36.432498931884766 36.43360137939453 36.473201751708984 36.51729965209961 36.5526008605957 36.55350112915039 36.554901123046875 36.56079864501953 36.5620002746582 36.56290054321289 36.563201904296875 36.563499450683594 36.563899993896484 36.56549835205078 36.56890106201172 36.57310104370117 36.58570098876953 36.5890007019043 36.589599609375 36.5994987487793  PSU	69 options
oxygen	= (ANY) 2.671999931335449 2.7090001106262207 2.7160000801086426 2.7860000133514404 2.809999942779541 2.9719998836517334 3.177000045776367 3.249000072479248 3.382999897003174 3.384999990463257 3.4649999141693115 3.7119998931884766 4.301000118255615 4.6570000648498535 4.6579999923706055 4.664000034332275 4.665999889373779  milliliters per liter	18 options
nitrite	= (ANY) -99.0  micromols per liter	2 options
nitrate	= (ANY) 0.0 0.4000000059604645 3.299999952316284 7.0 9.399999618530273 10.399999618530273 11.699999809265137 12.399999618530273 17.100000381469727 20.799999237060547 23.0 25.200000762939453 27.299999237060547 28.700000762939453  micromols	15 options
phosphate	= (ANY) 0.05000000074505806 0.09000000357627869 0.10000000149011612 0.17000000178813934 0.18000000715255737 0.1899999976158142 0.3700000047683716 0.5099999904632568 0.6000000238418579 0.699999988079071 0.7099999785423279 1.2999999523162842 1.3300000429153442 1.4800000190734863 1.5800000429153442 1.7300000190734863 2.0899999141693115  micromols per liter	18 options
silicate	= (ANY) 1.600000023841858 1.899999976158142 2.0 2.0999999046325684 2.5999999046325684 3.799999952316284 4.0 4.199999809265137 4.599999904632568 4.800000190734863 6.900000095367432 9.199999809265137 10.399999618530273 12.100000381469727 14.199999809265137 15.399999618530273  micromols per liter	17 options
salinity2	= (ANY) -99.0  PSU	2 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	PSU	milliliters per liter	micromols per liter	micromols	micromols per liter	micromols per liter	PSU
5.0	25.667600631713867	36.35660171508789	4.6579999923706055	-99.0	0.0	0.1899999976158142	1.600000023841858	-99.0	0.0
6.0	25.670900344848633	36.35660171508789	4.665999889373779	-99.0	0.0	0.17000000178813934	2.0	-99.0	0.0
7.0	25.66939926147461	36.3568000793457	4.6570000648498535	-99.0	0.0	0.09000000357627869	1.899999976158142	-99.0	0.0
8.0	25.670000076293945	36.3567008972168	4.664000034332275	-99.0	0.0	0.05000000074505806	2.0999999046325684	-99.0	0.0
9.0	25.66939926147461	36.356998443603516	4.301000118255615	-99.0	0.4000000059604645	0.10000000149011612	1.899999976158142	-99.0	0.0
10.0	25.669700622558594	36.356300354003906	3.7119998931884766	-99.0	3.299999952316284	0.18000000715255737	2.5999999046325684	-99.0	0.0
11.0	25.67020034790039	36.3567008972168	3.384999990463257	-99.0	7.0	0.3700000047683716	3.799999952316284	-99.0	0.0
12.0	25.671499252319336	36.35649871826172	3.249000072479248	-99.0	9.399999618530273	0.5099999904632568	4.0	-99.0	0.0
13.0	25.670400619506836	36.356300354003906	3.382999897003174	-99.0	10.399999618530273	0.6000000238418579	4.199999809265137	-99.0	0.0
14.0	25.666000366210938	36.3567008972168	3.177000045776367	-99.0	12.399999618530273	0.7099999785423279	4.599999904632568	-99.0	0.0
15.0	25.665700912475586	36.3567008972168	3.4649999141693115	-99.0	11.699999809265137	0.699999988079071	4.800000190734863	-99.0	0.0
16.0	25.672399520874023	36.3567008972168	2.9719998836517334	-99.0	17.100000381469727	1.2999999523162842	6.900000095367432	-99.0	0.0
17.0	25.67140007019043	36.3572998046875	2.7860000133514404	-99.0	20.799999237060547	1.3300000429153442	9.199999809265137	-99.0	0.0
18.0	25.672300338745117	36.356300354003906	2.809999942779541	-99.0	23.0	1.4800000190734863	10.399999618530273	-99.0	0.0
20.0	25.667400360107422	36.35639953613281	2.7160000801086426	-99.0	25.200000762939453	1.5800000429153442	12.100000381469727	-99.0	0.0
21.0	25.66670036315918	36.35639953613281	2.671999931335449	-99.0	27.299999237060547	1.7300000190734863	14.199999809265137	-99.0	0.0
22.0	25.666799545288086	36.3568000793457	2.7090001106262207	-99.0	28.700000762939453	2.0899999141693115	15.399999618530273	-99.0	0.0
23.0	25.666900634765625	36.35689926147461							0.0
24.0	25.667600631713867	36.35660171508789							0.0
25.0	25.667800903320312	36.35710144042969							0.0
26.0	25.66819953918457	36.3583984375							0.0
27.0	25.668399810791016	36.358699798583984							0.0
28.0	25.66830062866211	36.358001708984375							0.0
29.0	25.669099807739258	36.35749816894531							0.0
30.0	25.669300079345703	36.357601165771484							0.0
31.0	25.66950035095215	36.357601165771484							0.0
32.0	25.668399810791016	36.359901428222656							0.0
33.0	25.66790008544922	36.360599517822266							0.0
34.0	25.667800903320312	36.36149978637695							0.0
35.0	25.66790008544922	36.36249923706055							0.0
36.0	25.666200637817383	36.36539840698242							0.0
37.0	25.658000946044922	36.37110137939453							0.0
38.0	25.65239906311035	36.3745002746582							0.0
39.0	25.65180015563965	36.374900817871094							0.0
40.0	25.647899627685547	36.37739944458008							0.0
41.0	25.642200469970703	36.37919998168945							0.0
42.0	25.635900497436523	36.38100051879883							0.0
43.0	25.624399185180664	36.38349914550781							0.0
44.0	25.579700469970703	36.390499114990234							0.0
45.0	25.530799865722656	36.39569854736328							0.0
46.0	25.481000900268555	36.39870071411133							0.0
47.0	25.478700637817383	36.397499084472656							0.0
48.0	25.474300384521484	36.39680099487305							0.0
49.0	25.469200134277344	36.39870071411133							0.0
50.0	25.470800399780273	36.400901794433594							0.0
51.0	25.472400665283203	36.40299987792969							0.0
52.0	25.473100662231445	36.40380096435547							0.0
53.0	25.474300384521484	36.407798767089844							0.0
54.0	25.47410011291504	36.409000396728516							0.0
55.0	25.47410011291504	36.40919876098633							0.0
56.0	25.47319984436035	36.4109992980957							0.0
57.0	25.46660041809082	36.41569900512695							0.0
58.0	25.45009994506836	36.41279983520508							0.0
59.0	25.445100784301758	36.41740036010742							0.0
60.0	25.437000274658203	36.41899871826172							0.0
61.0	25.37579917907715	36.423301696777344							0.0
62.0	25.313499450683594	36.427799224853516							0.0
63.0	25.228200912475586	36.43230056762695							0.0
64.0	25.194900512695312	36.432498931884766							0.0
65.0	25.20159912109375	36.43050003051758							0.0
66.0	25.165300369262695	36.43109893798828							0.0
67.0	25.13719940185547	36.43230056762695							0.0
68.0	25.10260009765625	36.43360137939453							0.0
69.0	25.014400482177734	36.43119812011719							0.0
70.0	24.846599578857422	36.473201751708984							0.0
71.0	24.497400283813477	36.51729965209961							0.0
72.0	24.21109962463379	36.5526008605957							0.0
73.0	23.995399475097656	36.56290054321289							0.0
74.0	24.042400360107422	36.55350112915039							0.0
75.0	23.74880027770996	36.563499450683594							0.0
76.0	23.556499481201172	36.56549835205078							0.0
77.0	23.41830062866211	36.563899993896484							0.0
78.0	23.396299362182617	36.56890106201172							0.0
79.0	23.29840087890625	36.57310104370117							0.0
80.0	23.219499588012695	36.5994987487793							0.0
81.0	23.09630012512207	36.589599609375							0.0
82.0	23.098899841308594	36.58570098876953							0.0
83.0	22.836599349975586	36.554901123046875							0.0
84.0	22.749799728393555	36.56079864501953							0.0
85.0	22.72130012512207	36.563201904296875							0.0
86.0	22.710599899291992	36.5620002746582							0.0
87.0	22.62070083618164	36.5890007019043							0.0

In total, there are 82 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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