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Dataset Title:  "Deepwater CTD - 03260924.ctd.nc - 26.19N, -85.99W - 1979-04-28" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_03260924_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: 478)
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   478 options
    temperature ?  =  degree_C   473 options
    salinity ?  =  PSU   325 options
    oxygen ?  =  milliliters per liter   13 options
    nitrite ?  =  micromols   7 options
    nitrate ?  =  micromols   12 options
    phosphate ?  =  micromols   13 options
    silicate ?  =  micromols   13 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 micromols micromols micromols PSU
0.0 25.698999404907227 36.209999084472656 4.579999923706055 -99.98999786376953 -99.98999786376953 -99.98999786376953 0.20000000298023224 -99.0 0.0
2.0 25.698999404907227 36.209999084472656 4.670000076293945 -99.98999786376953 0.10000000149011612 0.009999999776482582 0.699999988079071 -99.0 0.0
4.0 25.701000213623047 36.21099853515625 4.980000019073486 -99.98999786376953 -99.98999786376953 0.019999999552965164 0.8999999761581421 -99.0 0.0
6.0 25.700000762939453 36.2130012512207 4.840000152587891 0.3199999928474426 0.30000001192092896 0.05000000074505806 1.2000000476837158 -99.0 0.0
8.0 25.695999145507812 36.2140007019043 3.640000104904175 0.5199999809265137 3.799999952316284 0.20000000298023224 1.5 -99.0 0.0
10.0 25.695999145507812 36.21500015258789 3.3499999046325684 0.3199999928474426 6.300000190734863 0.3199999928474426 1.7999999523162842 -99.0 0.0
12.0 25.69099998474121 36.21699905395508 3.1500000953674316 0.2199999988079071 9.600000381469727 0.5 2.5 -99.0 0.0
14.0 25.68199920654297 36.220001220703125 2.9800000190734863 0.11999999731779099 15.399999618530273 0.7900000214576721 4.0 -99.0 0.0
16.0 25.66900062561035 36.2239990234375 2.940000057220459 0.11999999731779099 20.399999618530273 1.090000033378601 6.400000095367432 -99.0 0.0
18.0 25.650999069213867 36.231998443603516 2.7899999618530273 0.7200000286102295 24.600000381469727 1.440000057220459 13.5 -99.0 0.0
20.0 25.638999938964844 36.23899841308594 2.609999895095825 -99.98999786376953 27.200000762939453 1.590000033378601 12.5 -99.0 0.0
22.0 25.631999969482422 36.24300003051758 2.7699999809265137 0.2199999988079071 25.899999618530273 1.5499999523162842 13.0 -99.0 0.0
24.0 25.614999771118164 36.237998962402344 0.0
26.0 25.59600067138672 36.233001708984375 0.0
28.0 25.582000732421875 36.233001708984375 0.0
30.0 25.56100082397461 36.23400115966797 0.0
32.0 25.530000686645508 36.23500061035156 0.0
34.0 25.44499969482422 36.21799850463867 0.0
36.0 25.368999481201172 36.202999114990234 0.0
38.0 25.34600067138672 36.202999114990234 0.0
40.0 25.33300018310547 36.20199966430664 0.0
42.0 25.322999954223633 36.20000076293945 0.0
44.0 25.31100082397461 36.198001861572266 0.0
46.0 25.29800033569336 36.196998596191406 0.0
48.0 25.288000106811523 36.19599914550781 0.0
50.0 25.275999069213867 36.19599914550781 0.0
52.0 25.266000747680664 36.196998596191406 0.0
54.0 25.246999740600586 36.202999114990234 0.0
56.0 25.208999633789062 36.2130012512207 0.0
58.0 25.184999465942383 36.21799850463867 0.0
60.0 25.174999237060547 36.220001220703125 0.0
62.0 25.167999267578125 36.220001220703125 0.0
64.0 25.177000045776367 36.25299835205078 0.0
66.0 25.170000076293945 36.290000915527344 0.0
68.0 25.125999450683594 36.32899856567383 0.0
70.0 25.06100082397461 36.36199951171875 0.0
72.0 24.979999542236328 36.37900161743164 0.0
74.0 24.930999755859375 36.39699935913086 0.0
76.0 24.948999404907227 36.452999114990234 0.0
78.0 24.92799949645996 36.4900016784668 0.0
80.0 24.860000610351562 36.50299835205078 0.0
82.0 24.76799964904785 36.512001037597656 0.0
84.0 24.670000076293945 36.55400085449219 0.0
86.0 24.593000411987305 36.597999572753906 0.0
88.0 24.520999908447266 36.62699890136719 0.0
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106.0 23.091999053955078 36.61399841308594 0.0
108.0 22.891000747680664 36.64400100708008 0.0
110.0 22.770000457763672 36.70399856567383 0.0
112.0 22.570999145507812 36.685001373291016 0.0
114.0 22.312000274658203 36.63600158691406 0.0
116.0 21.952999114990234 36.5359992980957 0.0
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128.0 21.06599998474121 36.39899826049805 0.0
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714.0 7.007999897003174 34.87900161743164 0.0
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720.0 6.934000015258789 34.88100051879883 0.0
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744.0 6.6620001792907715 34.875999450683594 0.0
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756.0 6.5 34.86899948120117 0.0
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782.0 6.334000110626221 34.875 0.0
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798.0 6.248000144958496 34.87900161743164 0.0
800.0 6.24399995803833 34.87900161743164 0.0
802.0 6.238999843597412 34.880001068115234 0.0
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810.0 6.202000141143799 34.88100051879883 0.0
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820.0 6.11299991607666 34.87799835205078 0.0
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838.0 6.021999835968018 34.8849983215332 0.0
840.0 6.01200008392334 34.88600158691406 0.0
842.0 6.0 34.887001037597656 0.0
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846.0 5.955999851226807 34.888999938964844 0.0
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856.0 5.88700008392334 34.888999938964844 0.0
858.0 5.875 34.89099884033203 0.0
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882.0 5.7820000648498535 34.89899826049805 0.0
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886.0 5.7729997634887695 34.89699935913086 0.0
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892.0 5.711999893188477 34.89699935913086 0.0
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896.0 5.670000076293945 34.900001525878906 0.0
898.0 5.660999774932861 34.90299987792969 0.0
900.0 5.6570000648498535 34.90299987792969 0.0
902.0 5.6539998054504395 34.90299987792969 0.0
904.0 5.646999835968018 34.90399932861328 0.0
906.0 5.636000156402588 34.904998779296875 0.0
908.0 5.626999855041504 34.904998779296875 0.0
910.0 5.625 34.90599822998047 0.0
912.0 5.622000217437744 34.90599822998047 0.0
914.0 5.603000164031982 34.90599822998047 0.0
916.0 5.578000068664551 34.90599822998047 0.0
918.0 5.560999870300293 34.90700149536133 0.0
920.0 5.553999900817871 34.90800094604492 0.0
922.0 5.551000118255615 34.909000396728516 0.0
924.0 5.550000190734863 34.90999984741211 0.0
926.0 5.544000148773193 34.909000396728516 0.0
928.0 5.535999774932861 34.909000396728516 0.0
930.0 5.5289998054504395 34.9109992980957 0.0
932.0 5.521999835968018 34.9109992980957 0.0
934.0 5.513999938964844 34.9109992980957 0.0
936.0 5.50600004196167 34.9119987487793 0.0
938.0 5.499000072479248 34.9109992980957 0.0
940.0 5.492000102996826 34.9109992980957 0.0
942.0 5.480999946594238 34.9119987487793 0.0
944.0 5.4730000495910645 34.91400146484375 0.0
946.0 5.466000080108643 34.91400146484375 0.0
948.0 5.459000110626221 34.91400146484375 0.0
950.0 5.451000213623047 34.91400146484375 0.0
952.0 5.440999984741211 34.915000915527344 0.0
954.0 5.433000087738037 34.915000915527344 0.0

In total, there are 478 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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