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Dataset Title:  "Deepwater CTD - 97g08_12.ctd.nc - 28.79N, -88.73W - 1997-00-21" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_97g08_12_ctd)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 850)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    depth ?  =  m   850 options
    temperature ?  =  degree_C   843 options
    salinity ?  =  PSU   708 options
    oxygen ?  =  milliliters per liter   798 options
    nitrite ?  =  micromols per liter   6 options
    nitrate ?  =  micromols   9 options
    phosphate ?  =  micromols per liter   10 options
    silicate ?  =  micromols per liter   11 options
    salinity2 ?  =  PSU   2 options
    qualityFlag ?  =  2 options

View:      Map of All Related Data ?      Distinct Data Counts ?     Distinct Data ?      Related Data Counts ?     Related Data ?

 
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.
 

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.
 

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
1.0 31.022499084472656 29.143299102783203 2.9437999725341797 0.009999999776482582 0.0 0.019999999552965164 1.5 -99.0 0.0
2.0 31.13409996032715 31.15130043029785 2.765399932861328 0.009999999776482582 0.0 0.019999999552965164 1.5 -99.0 0.0
3.0 30.979799270629883 31.928600311279297 2.767899990081787 0.009999999776482582 0.0 0.009999999776482582 1.2000000476837158 -99.0 0.0
4.0 30.997900009155273 32.03260040283203 3.1301000118255615 0.019999999552965164 0.0 0.019999999552965164 1.0 -99.0 0.0
5.0 30.92770004272461 32.566898345947266 3.214099884033203 0.10000000149011612 1.7000000476837158 0.09000000357627869 1.600000023841858 -99.0 0.0
6.0 30.949600219726562 32.486000061035156 3.336199998855591 0.03999999910593033 9.0 0.4099999964237213 3.0999999046325684 -99.0 0.0
7.0 30.773000717163086 32.90570068359375 3.4356000423431396 0.019999999552965164 11.100000381469727 0.550000011920929 3.5999999046325684 -99.0 0.0
8.0 30.785999298095703 33.02330017089844 3.5250000953674316 0.009999999776482582 22.0 1.2599999904632568 10.0 -99.0 0.0
9.0 30.799999237060547 32.94380187988281 3.658900022506714 0.0 30.5 1.8600000143051147 23.200000762939453 -99.0 0.0
10.0 30.79509925842285 33.244598388671875 3.69950008392334 0.009999999776482582 29.700000762939453 1.7999999523162842 24.799999237060547 -99.0 0.0
11.0 30.285400390625 34.160099029541016 3.7607998847961426 0.0 27.700000762939453 1.7400000095367432 25.299999237060547 -99.0 0.0
12.0 30.158300399780273 34.23210144042969 3.7888998985290527 0.0
13.0 29.90169906616211 34.28110122680664 3.849299907684326 0.0
14.0 29.792299270629883 34.333900451660156 3.8752999305725098 0.0
15.0 29.30769920349121 34.50519943237305 3.9326000213623047 0.0
16.0 29.422399520874023 35.10319900512695 3.9774999618530273 0.0
17.0 29.094900131225586 35.498199462890625 4.010000228881836 0.0
18.0 28.677000045776367 35.66310119628906 4.041299819946289 0.0
19.0 27.864700317382812 35.58919906616211 4.160099983215332 0.0
20.0 27.237300872802734 35.781700134277344 4.2032999992370605 0.0
21.0 27.431699752807617 36.15409851074219 4.171999931335449 0.0
22.0 27.291500091552734 36.232601165771484 4.184599876403809 0.0
23.0 27.01490020751953 36.3114013671875 4.188300132751465 0.0
24.0 26.921300888061523 36.363800048828125 4.178500175476074 0.0
25.0 26.804899215698242 36.3734016418457 4.1875 0.0
26.0 26.54520034790039 36.37459945678711 4.209000110626221 0.0
27.0 26.05299949645996 36.3291015625 4.2382001876831055 0.0
28.0 25.834999084472656 36.31990051269531 4.278800010681152 0.0
29.0 25.647499084472656 36.294700622558594 4.297100067138672 0.0
30.0 25.487499237060547 36.2859992980957 4.320099830627441 0.0
31.0 25.204099655151367 36.292701721191406 4.354000091552734 0.0
32.0 24.876699447631836 36.336299896240234 4.4008002281188965 0.0
33.0 24.870899200439453 36.36669921875 4.399600028991699 0.0
34.0 24.89080047607422 36.42789840698242 4.365099906921387 0.0
35.0 24.782800674438477 36.452301025390625 4.316999912261963 0.0
36.0 24.565200805664062 36.44670104980469 4.235099792480469 0.0
37.0 24.462600708007812 36.43009948730469 4.281199932098389 0.0
38.0 24.37380027770996 36.4193000793457 4.308700084686279 0.0
39.0 24.311399459838867 36.41619873046875 4.320700168609619 0.0
40.0 24.26140022277832 36.42679977416992 4.3221001625061035 0.0
41.0 24.10449981689453 36.4203987121582 4.318900108337402 0.0
42.0 23.85700035095215 36.403900146484375 4.331500053405762 0.0
43.0 23.71150016784668 36.40739822387695 4.360599994659424 0.0
44.0 23.479400634765625 36.38800048828125 4.354400157928467 0.0
45.0 23.31220054626465 36.37310028076172 4.379000186920166 0.0
46.0 23.212600708007812 36.365699768066406 4.396299839019775 0.0
47.0 23.119699478149414 36.382198333740234 4.396900177001953 0.0
48.0 23.045700073242188 36.39849853515625 4.349400043487549 0.0
49.0 22.92650032043457 36.382301330566406 4.340799808502197 0.0
50.0 22.760799407958984 36.36880111694336 4.376299858093262 0.0
51.0 22.634300231933594 36.35649871826172 4.4257001876831055 0.0
52.0 22.579500198364258 36.35060119628906 4.440400123596191 0.0
53.0 22.540300369262695 36.35150146484375 4.458899974822998 0.0
54.0 22.489700317382812 36.35279846191406 4.459499835968018 0.0
55.0 22.441099166870117 36.35350036621094 4.457099914550781 0.0
56.0 22.35650062561035 36.351200103759766 4.44320011138916 0.0
57.0 22.244199752807617 36.34389877319336 4.429900169372559 0.0
58.0 22.164600372314453 36.33890151977539 4.428100109100342 0.0
59.0 22.10810089111328 36.33340072631836 4.417900085449219 0.0
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61.0 22.007600784301758 36.33380126953125 4.404399871826172 0.0
62.0 21.957500457763672 36.332298278808594 4.3856000900268555 0.0
63.0 21.863300323486328 36.330501556396484 4.352499961853027 0.0
64.0 21.811500549316406 36.32870101928711 4.324699878692627 0.0
65.0 21.773300170898438 36.33660125732422 4.310800075531006 0.0
66.0 21.750200271606445 36.37969970703125 4.245200157165527 0.0
67.0 21.69409942626953 36.39419937133789 4.22160005569458 0.0
68.0 21.658700942993164 36.39619827270508 4.2093000411987305 0.0
69.0 21.593799591064453 36.404998779296875 4.19980001449585 0.0
70.0 21.558399200439453 36.40629959106445 4.177199840545654 0.0
71.0 21.456300735473633 36.40409851074219 4.163700103759766 0.0
72.0 21.387500762939453 36.39509963989258 4.144999980926514 0.0
73.0 21.25629997253418 36.392799377441406 4.147299766540527 0.0
74.0 21.24679946899414 36.40330123901367 4.07420015335083 0.0
75.0 21.12070083618164 36.39799880981445 4.054500102996826 0.0
76.0 21.052099227905273 36.395198822021484 4.0131001472473145 0.0
77.0 20.99250030517578 36.39039993286133 3.986799955368042 0.0
78.0 20.968799591064453 36.38909912109375 3.986799955368042 0.0
79.0 20.92930030822754 36.38420104980469 3.963399887084961 0.0
80.0 20.849000930786133 36.380001068115234 3.9442999362945557 0.0
81.0 20.834199905395508 36.37860107421875 3.9256999492645264 0.0
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83.0 20.723499298095703 36.37189865112305 3.892699956893921 0.0
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85.0 20.601900100708008 36.36989974975586 3.8187999725341797 0.0
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87.0 20.435100555419922 36.379398345947266 3.744800090789795 0.0
88.0 20.390399932861328 36.38959884643555 3.6709001064300537 0.0
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91.0 20.17970085144043 36.381099700927734 3.5975000858306885 0.0
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95.0 19.788000106811523 36.39339828491211 3.3989999294281006 0.0
96.0 19.675100326538086 36.40660095214844 3.3304998874664307 0.0
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98.0 19.428499221801758 36.4375 3.23009991645813 0.0
99.0 19.36400032043457 36.446998596191406 3.2009999752044678 0.0
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101.0 19.34149932861328 36.46200180053711 3.15910005569458 0.0
102.0 19.32699966430664 36.470001220703125 3.134399890899658 0.0
103.0 19.276599884033203 36.47330093383789 3.114300012588501 0.0
104.0 19.207500457763672 36.462501525878906 3.1089999675750732 0.0
105.0 19.177200317382812 36.46179962158203 3.0987000465393066 0.0
106.0 18.990100860595703 36.458900451660156 3.091399908065796 0.0
107.0 18.876399993896484 36.466400146484375 3.0745999813079834 0.0
108.0 18.75309944152832 36.44969940185547 3.0404000282287598 0.0
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110.0 18.51259994506836 36.45429992675781 3.0306999683380127 0.0
111.0 18.49839973449707 36.451698303222656 3.015399932861328 0.0
112.0 18.437700271606445 36.452598571777344 3.0209999084472656 0.0
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114.0 18.143199920654297 36.4276008605957 3.0318000316619873 0.0
115.0 18.085899353027344 36.42290115356445 3.022200107574463 0.0
116.0 18.06060028076172 36.41849899291992 3.023400068283081 0.0
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119.0 18.01729965209961 36.426998138427734 3.06850004196167 0.0
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761.0 5.630099773406982 34.905799865722656 3.382200002670288 0.0
762.0 5.626100063323975 34.905799865722656 3.3889000415802 0.0
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765.0 5.613699913024902 34.90589904785156 3.3968000411987305 0.0
766.0 5.600299835205078 34.90650177001953 3.3984999656677246 0.0
767.0 5.594099998474121 34.906898498535156 3.4045000076293945 0.0
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770.0 5.581399917602539 34.906700134277344 3.413100004196167 0.0
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772.0 5.555300235748291 34.90810012817383 3.4203999042510986 0.0
773.0 5.5518999099731445 34.90810012817383 3.4221999645233154 0.0
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776.0 5.543900012969971 34.90800094604492 3.438999891281128 0.0
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778.0 5.533699989318848 34.90850067138672 3.441800117492676 0.0
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785.0 5.503600120544434 34.9093017578125 3.4646999835968018 0.0
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788.0 5.501100063323975 34.90919876098633 3.469599962234497 0.0
789.0 5.499199867248535 34.909400939941406 3.469599962234497 0.0
790.0 5.495999813079834 34.9093017578125 3.471100091934204 0.0
791.0 5.493100166320801 34.90959930419922 3.4725000858306885 0.0
792.0 5.492099761962891 34.90950012207031 3.4693000316619873 0.0
793.0 5.491000175476074 34.90950012207031 3.4744999408721924 0.0
794.0 5.488500118255615 34.90950012207031 3.4793999195098877 0.0
795.0 5.48799991607666 34.909698486328125 3.4779000282287598 0.0
796.0 5.488100051879883 34.90959930419922 3.4716999530792236 0.0
797.0 5.488800048828125 34.90959930419922 3.4781999588012695 0.0
798.0 5.489799976348877 34.909400939941406 3.4816999435424805 0.0
799.0 5.489500045776367 34.909400939941406 3.4837000370025635 0.0
800.0 5.489299774169922 34.9093017578125 3.477299928665161 0.0
801.0 5.489699840545654 34.909400939941406 3.481100082397461 0.0
802.0 5.489699840545654 34.909400939941406 3.482800006866455 0.0
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804.0 5.488500118255615 34.9093017578125 3.4863998889923096 0.0
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806.0 5.4882001876831055 34.9093017578125 3.487600088119507 0.0
807.0 5.488399982452393 34.90919876098633 3.48799991607666 0.0
808.0 5.48769998550415 34.90919876098633 3.4907000064849854 0.0
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810.0 5.484600067138672 34.909400939941406 3.4876999855041504 0.0
811.0 5.482500076293945 34.909400939941406 3.4911999702453613 0.0
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815.0 5.479899883270264 34.909400939941406 3.4962000846862793 0.0
816.0 5.476200103759766 34.90959930419922 3.490299940109253 0.0
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818.0 5.469099998474121 34.90999984741211 3.498300075531006 0.0
819.0 5.468200206756592 34.90999984741211 3.498699903488159 0.0
820.0 5.467700004577637 34.90999984741211 3.4953999519348145 0.0
821.0 5.465799808502197 34.90999984741211 3.4983999729156494 0.0
822.0 5.465099811553955 34.910099029541016 3.4969000816345215 0.0
823.0 5.464600086212158 34.91019821166992 3.4988999366760254 0.0
824.0 5.464200019836426 34.90999984741211 3.502000093460083 0.0
825.0 5.462800025939941 34.90999984741211 3.5035998821258545 0.0
826.0 5.460599899291992 34.910099029541016 3.5051000118255615 0.0
827.0 5.460400104522705 34.91019821166992 3.5060999393463135 0.0
828.0 5.458700180053711 34.910099029541016 3.50819993019104 0.0
829.0 5.454899787902832 34.910400390625 3.503499984741211 0.0
830.0 5.452899932861328 34.910499572753906 3.504699945449829 0.0
831.0 5.4517998695373535 34.910400390625 3.5097999572753906 0.0
832.0 5.450699806213379 34.91059875488281 3.511199951171875 0.0
833.0 5.44950008392334 34.910400390625 3.512399911880493 0.0
834.0 5.446400165557861 34.910499572753906 3.5106000900268555 0.0
835.0 5.44189977645874 34.91080093383789 3.5139999389648438 0.0
836.0 5.440499782562256 34.910701751708984 3.516900062561035 0.0
837.0 5.438499927520752 34.91080093383789 3.51990008354187 0.0
838.0 5.438700199127197 34.910701751708984 3.516200065612793 0.0
839.0 5.438000202178955 34.91080093383789 3.51990008354187 0.0
840.0 5.434899806976318 34.9109992980957 3.5225000381469727 0.0
841.0 5.436200141906738 34.91080093383789 3.5223000049591064 0.0
842.0 5.434599876403809 34.9109001159668 3.521899938583374 0.0
843.0 5.433800220489502 34.9109001159668 3.519700050354004 0.0
844.0 5.433300018310547 34.91080093383789 3.5213000774383545 0.0
845.0 5.431700229644775 34.9109001159668 3.520900011062622 0.0
846.0 5.428899765014648 34.9109992980957 3.523400068283081 0.0
847.0 5.424900054931641 34.91130065917969 3.5227999687194824 0.0
848.0 5.418399810791016 34.911598205566406 3.527100086212158 0.0
849.0 5.4156999588012695 34.9114990234375 3.5246999263763428 0.0
850.0 5.411799907684326 34.91170120239258 3.530100107192993 0.0

In total, there are 850 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.
 

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.
 

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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