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Dataset Title:  "Deepwater CTD - d94h140.ctd.nc - 27.11N, -96.28W - 1994-05-04" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94h140_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: 617)
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   309 options
    temperature ?  =  degree_C   612 options
    salinity ?  =  PSU   585 options
    oxygen ?  =  milliliters per liter   13 options
    pressure ?  =  decibars   617 options
    nitrite ?  =  micromols   9 options
    nitrate ?  =  micromols   13 options
    phosphate ?  =  micromols   12 options
    silicate ?  =  micromols   13 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 pressure nitrite nitrate phosphate silicate salinity2 qualityFlag
m degree_C PSU milliliters per liter decibars micromols micromols micromols micromols PSU
3.0 24.631500244140625 34.29119873046875 4.960000038146973 3.0199999809265137 0.019999999552965164 0.05000000074505806 0.0 2.25 -9.0 0.0
3.0 24.64069938659668 34.28670120239258 5.099999904632568 3.5239999294281006 0.019999999552965164 0.029999999329447746 0.0 2.819999933242798 -9.0 0.0
4.0 24.643199920654297 34.28770065307617 4.989999771118164 4.53000020980835 0.3400000035762787 0.27000001072883606 0.25999999046325684 2.6600000858306885 -9.0 0.0
4.0 24.64349937438965 34.289100646972656 4.889999866485596 4.0269999504089355 0.12999999523162842 0.05999999865889549 0.029999999329447746 3.2899999618530273 -9.0 0.0
5.0 24.639799118041992 34.2849006652832 5.050000190734863 5.033999919891357 0.17000000178813934 0.03999999910593033 0.03999999910593033 2.200000047683716 -9.0 0.0
5.0 24.642099380493164 34.28310012817383 4.710000038146973 5.5370001792907715 0.1899999976158142 1.5199999809265137 0.10999999940395355 2.509999990463257 -9.0 0.0
6.0 24.61549949645996 34.29750061035156 2.940000057220459 6.544000148773193 0.029999999329447746 11.050000190734863 0.6100000143051147 4.889999866485596 -9.0 0.0
6.0 24.62150001525879 34.29560089111328 4.150000095367432 6.039999961853027 0.10999999940395355 4.260000228881836 0.25 3.440000057220459 -9.0 0.0
7.0 24.57200050354004 34.32229995727539 2.9000000953674316 7.551000118255615 0.019999999552965164 14.460000038146973 0.8600000143051147 6.019999980926514 -9.0 0.0
7.0 24.58639907836914 34.31399917602539 2.990000009536743 7.046999931335449 0.019999999552965164 13.239999771118164 0.7699999809265137 5.519999980926514 -9.0 0.0
8.0 24.5039005279541 34.36759948730469 2.680000066757202 8.557000160217285 0.019999999552965164 22.350000381469727 1.440000057220459 11.890000343322754 -9.0 0.0
8.0 24.529600143432617 34.35049819946289 2.759999990463257 8.053999900817871 0.009999999776482582 18.639999389648438 1.1399999856948853 8.4399995803833 -9.0 0.0
9.0 24.229000091552734 34.53889846801758 9.564000129699707 0.0
9.0 24.363800048828125 34.460601806640625 9.060999870300293 0.0
10.0 23.935300827026367 34.643699645996094 10.571000099182129 0.0
10.0 24.003799438476562 34.62689971923828 10.067999839782715 0.0
11.0 23.763500213623047 34.70000076293945 11.57800006866455 0.0
11.0 23.867799758911133 34.667598724365234 11.074000358581543 0.0
12.0 23.697099685668945 34.73540115356445 12.585000038146973 0.0
12.0 23.718399047851562 34.718299865722656 12.081000328063965 0.0
13.0 23.61870002746582 34.80270004272461 13.590999603271484 0.0
13.0 23.65329933166504 34.7661018371582 13.088000297546387 0.0
14.0 23.507400512695312 34.89979934692383 14.597999572753906 0.0
14.0 23.550100326538086 34.86360168457031 14.095000267028809 0.0
15.0 23.407100677490234 35.03950119018555 15.604999542236328 0.0
15.0 23.457199096679688 34.969600677490234 15.10200023651123 0.0
16.0 23.306699752807617 35.179901123046875 16.61199951171875 0.0
16.0 23.35689926147461 35.10969924926758 16.107999801635742 0.0
17.0 23.256500244140625 35.2239990234375 17.618999481201172 0.0
17.0 23.26959991455078 35.21329879760742 17.114999771118164 0.0
18.0 23.122499465942383 35.33259963989258 18.625 0.0
18.0 23.20549964904785 35.26679992675781 18.121999740600586 0.0
19.0 23.008699417114258 35.42539978027344 19.631999969482422 0.0
19.0 23.0575008392334 35.38909912109375 19.128999710083008 0.0
20.0 22.945100784301758 35.46379852294922 20.638999938964844 0.0
20.0 22.961200714111328 35.45690155029297 20.13599967956543 0.0
21.0 22.85740089416504 35.52000045776367 21.645999908447266 0.0
21.0 22.89780044555664 35.49140167236328 21.142000198364258 0.0
22.0 22.82859992980957 35.53990173339844 22.14900016784668 0.0
22.0 22.82859992980957 35.55080032348633 22.652999877929688 0.0
23.0 22.797500610351562 35.598899841308594 23.65999984741211 0.0
23.0 22.82379913330078 35.56700134277344 23.1560001373291 0.0
24.0 22.739900588989258 35.71580123901367 24.666000366210938 0.0
24.0 22.766599655151367 35.62969970703125 24.163000106811523 0.0
25.0 22.741899490356445 35.777099609375 25.170000076293945 0.0
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26.0 22.759199142456055 35.85940170288086 26.177000045776367 0.0
27.0 22.72100067138672 35.90739822387695 27.687000274658203 0.0
27.0 22.732900619506836 35.90250015258789 27.18400001525879 0.0
28.0 22.690500259399414 35.91239929199219 28.694000244140625 0.0
28.0 22.709299087524414 35.90959930419922 28.190000534057617 0.0
29.0 22.66069984436035 35.9359016418457 29.701000213623047 0.0
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32.0 22.712299346923828 36.049198150634766 32.72100067138672 0.0
33.0 22.680099487304688 36.055198669433594 33.224998474121094 0.0
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34.0 22.508800506591797 36.06880187988281 34.73500061035156 0.0
34.0 22.662900924682617 36.07170104980469 34.231998443603516 0.0
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38.0 21.38170051574707 35.909000396728516 38.76300048828125 0.0
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39.0 21.210599899291992 35.89699935913086 39.77000045776367 0.0
39.0 21.296199798583984 35.90299987792969 39.26599884033203 0.0
40.0 21.125099182128906 35.890899658203125 40.27299880981445 0.0
40.0 21.165000915527344 35.94070053100586 40.777000427246094 0.0
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41.0 21.292800903320312 36.00230026245117 41.784000396728516 0.0
42.0 21.300600051879883 36.01350021362305 42.2869987487793 0.0
42.0 21.314899444580078 36.05540084838867 42.79100036621094 0.0
43.0 20.84819984436035 35.97480010986328 43.79800033569336 0.0
43.0 21.131500244140625 36.022300720214844 43.29399871826172 0.0
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306.0 12.35420036315918 35.557899475097656 308.79400634765625 0.0
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307.0 12.361599922180176 35.558998107910156 309.8030090332031 0.0
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310.0 12.337800025939941 35.55670166015625 312.8269958496094 0.0
310.0 12.338000297546387 35.556800842285156 312.322998046875 0.0
311.0 12.336999893188477 35.55630111694336 313.3320007324219 0.0

In total, there are 617 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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