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Dataset Title:  "Deepwater CTD - 90g10029.ctd.nc - 27.99N, -93.0W - 1990-07-14" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_90g10029_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: 102)
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   102 options
    temperature ?  =  degree_C   102 options
    salinity ?  =  PSU   98 options
    oxygen ?  =  milliliters per liter   12 options
    nitrite ?  =  micromols   5 options
    nitrate ?  =  micromols   10 options
    phosphate ?  =  micromols   10 options
    silicate ?  =  micromols   12 options
    salinity2 ?  =  PSU   2 options
    qualityFlag ?  =  1 option: 0.0

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 micromols micromols micromols PSU
1.0 29.0226993560791 31.716299057006836 4.519000053405762 0.009999999776482582 0.0 0.009999999776482582 2.5 -99.0 0.0
2.0 29.015100479125977 31.7052001953125 4.567999839782715 0.009999999776482582 0.10000000149011612 0.009999999776482582 2.799999952316284 -99.0 0.0
3.0 29.016700744628906 31.70599937438965 5.197000026702881 0.009999999776482582 0.10000000149011612 0.029999999329447746 2.200000047683716 -99.0 0.0
4.0 29.024700164794922 31.719900131225586 4.789000034332275 0.009999999776482582 0.10000000149011612 0.009999999776482582 2.5999999046325684 -99.0 0.0
5.0 29.023300170898438 31.7185001373291 3.311000108718872 0.07000000029802322 9.5 0.09000000357627869 4.900000095367432 -99.0 0.0
6.0 29.030899047851562 31.738399505615234 3.263000011444092 0.019999999552965164 13.0 0.7699999809265137 6.599999904632568 -99.0 0.0
7.0 29.041900634765625 31.765499114990234 3.0799999237060547 0.009999999776482582 16.0 1.059999942779541 8.600000381469727 -99.0 0.0
8.0 29.226499557495117 32.16780090332031 2.861999988555908 0.0 20.0 1.2999999523162842 11.199999809265137 -99.0 0.0
9.0 29.63599967956543 32.94329833984375 2.7039999961853027 0.009999999776482582 24.100000381469727 1.5199999809265137 14.100000381469727 -99.0 0.0
10.0 29.837400436401367 33.33599853515625 2.890000104904175 0.009999999776482582 28.799999237060547 1.7899999618530273 18.0 -99.0 0.0
11.0 29.96660041809082 33.64400100708008 2.7869999408721924 0.009999999776482582 31.700000762939453 1.9700000286102295 22.299999237060547 -99.0 0.0
12.0 29.94809913635254 33.733699798583984 0.0
13.0 29.94230079650879 33.762901306152344 0.0
14.0 29.934499740600586 33.799198150634766 0.0
15.0 29.903499603271484 33.82619857788086 0.0
16.0 29.88409996032715 33.83639907836914 0.0
17.0 29.845500946044922 33.851200103759766 0.0
18.0 29.832300186157227 33.886600494384766 0.0
19.0 29.820899963378906 33.900299072265625 0.0
20.0 29.798200607299805 33.91450119018555 0.0
21.0 29.758399963378906 33.95949935913086 0.0
22.0 29.66200065612793 34.012298583984375 0.0
23.0 29.53849983215332 34.14659881591797 0.0
24.0 29.46969985961914 34.427799224853516 0.0
25.0 29.460100173950195 34.604000091552734 0.0
26.0 29.45680046081543 34.72050094604492 0.0
27.0 29.445999145507812 34.820899963378906 0.0
28.0 29.42729949951172 34.897098541259766 0.0
29.0 29.39259910583496 34.95500183105469 0.0
30.0 29.176599502563477 35.11589813232422 0.0
31.0 28.711599349975586 35.1349983215332 0.0
32.0 28.292600631713867 35.221500396728516 0.0
33.0 27.499799728393555 35.27410125732422 0.0
34.0 26.939300537109375 35.482601165771484 0.0
35.0 26.402799606323242 35.63869857788086 0.0
36.0 25.988500595092773 35.79819869995117 0.0
37.0 25.634599685668945 35.9109992980957 0.0
38.0 25.434900283813477 35.92789840698242 0.0
39.0 25.383499145507812 35.94390106201172 0.0
40.0 25.361000061035156 35.96419906616211 0.0
41.0 25.17140007019043 36.042198181152344 0.0
42.0 24.975500106811523 36.122798919677734 0.0
43.0 24.73539924621582 36.21080017089844 0.0
44.0 24.597299575805664 36.22380065917969 0.0
45.0 24.42620086669922 36.23979949951172 0.0
46.0 24.217100143432617 36.245201110839844 0.0
47.0 24.110200881958008 36.24700164794922 0.0
48.0 23.975099563598633 36.2671012878418 0.0
49.0 23.848600387573242 36.27199935913086 0.0
50.0 23.780099868774414 36.278499603271484 0.0
51.0 23.5580997467041 36.27349853515625 0.0
52.0 23.296600341796875 36.27259826660156 0.0
53.0 23.023300170898438 36.262298583984375 0.0
54.0 22.80069923400879 36.25859832763672 0.0
55.0 22.59079933166504 36.257999420166016 0.0
56.0 22.47249984741211 36.26679992675781 0.0
57.0 22.442800521850586 36.275001525878906 0.0
58.0 22.35449981689453 36.276100158691406 0.0
59.0 22.266799926757812 36.279598236083984 0.0
60.0 22.181400299072266 36.285301208496094 0.0
61.0 22.088300704956055 36.29130172729492 0.0
62.0 21.950000762939453 36.30329895019531 0.0
63.0 21.8617000579834 36.31209945678711 0.0
64.0 21.759899139404297 36.319698333740234 0.0
65.0 21.7268009185791 36.320701599121094 0.0
66.0 21.702499389648438 36.322898864746094 0.0
67.0 21.66200065612793 36.32440185546875 0.0
68.0 21.604400634765625 36.32789993286133 0.0
69.0 21.574199676513672 36.330101013183594 0.0
70.0 21.548500061035156 36.331199645996094 0.0
71.0 21.538799285888672 36.332401275634766 0.0
72.0 21.52199935913086 36.33359909057617 0.0
73.0 21.498199462890625 36.335601806640625 0.0
74.0 21.475900650024414 36.336700439453125 0.0
75.0 21.459800720214844 36.339298248291016 0.0
76.0 21.419599533081055 36.343101501464844 0.0
77.0 21.359500885009766 36.3468017578125 0.0
78.0 21.21380043029785 36.34700012207031 0.0
79.0 21.13479995727539 36.34980010986328 0.0
80.0 21.079099655151367 36.352298736572266 0.0
81.0 21.044099807739258 36.353599548339844 0.0
82.0 21.01490020751953 36.35449981689453 0.0
83.0 20.986400604248047 36.354400634765625 0.0
84.0 20.92449951171875 36.356998443603516 0.0
85.0 20.803600311279297 36.362098693847656 0.0
86.0 20.70829963684082 36.36479949951172 0.0
87.0 20.647300720214844 36.36240005493164 0.0
88.0 20.522600173950195 36.36800003051758 0.0
89.0 20.49690055847168 36.367801666259766 0.0
90.0 20.364900588989258 36.37120056152344 0.0
91.0 20.230600357055664 36.37300109863281 0.0
92.0 19.944700241088867 36.371700286865234 0.0
93.0 19.652700424194336 36.37300109863281 0.0
94.0 19.513599395751953 36.36949920654297 0.0
95.0 19.299999237060547 36.371700286865234 0.0
96.0 19.242599487304688 36.37099838256836 0.0
97.0 19.1875 36.369598388671875 0.0
98.0 19.095699310302734 36.371700286865234 0.0
99.0 19.02669906616211 36.37200164794922 0.0
100.0 18.89299964904785 36.37030029296875 0.0
101.0 18.767000198364258 36.37099838256836 0.0
102.0 18.75349998474121 36.370399475097656 0.0

In total, there are 102 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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