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Dataset Title:  "LATEX CTD - d94i063.nc - 28.86N, 93.0W - 1994-07-31" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: latex_d94i063)
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: 43)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    pressure ?  =  dBar   43 options
    depth ?  =  m   43 options
    temperature ?  =  degree_C   43 options
    potentialTemperature ?  =  degree_C   43 options
    conductivity ?  =  Siemens per meter   43 options
    salinity ?  =  PSU   42 options
    sigmat ?  =  kg m-3   43 options
    descentRate ?  =  meters per second   42 options
    transmission ?  =  percent   33 options
    par ?  =  umol m-2 s-1   43 options
    parv ?  =  volts   43 options
    fluorescence ?  =  volts   36 options
    backscattering ?  =  volts   11 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)  

pressure depth temperature potentialTemperature conductivity salinity sigmat descentRate transmission par parv fluorescence backscattering
dBar m degree_C degree_C Siemens per meter PSU kg m-3 meters per second percent umol m-2 s-1 volts volts volts
2.5 2.5 29.001699447631836 29.001100540161133 5.361700057983398 32.48820114135742 20.181100845336914 -6.322999954223633 4.369999885559082 58.20000076293945 1.9040000438690186 1.3559999465942383 0.024000000208616257
3.0 3.0 28.904600143432617 28.903900146484375 5.341899871826172 32.4193000793457 20.161699295043945 0.4970000088214874 4.372000217437744 53.099998474121094 1.8639999628067017 1.3509999513626099 0.024000000208616257
3.5 3.5 29.014699935913086 29.013900756835938 5.36299991607666 32.48849868774414 20.177099227905273 -0.33799999952316284 4.375999927520752 51.400001525878906 1.850000023841858 1.3589999675750732 0.024000000208616257
4.0 4.0 28.995500564575195 28.99449920654297 5.3607001304626465 32.48569869995117 20.181400299072266 0.10000000149011612 4.375999927520752 45.5 1.7970000505447388 1.3519999980926514 0.024000000208616257
4.5 4.5 29.081199645996094 29.08009910583496 5.38070011138916 32.56290054321289 20.210800170898438 0.04399999976158142 4.376999855041504 42.29999923706055 1.7649999856948853 1.350000023841858 0.023000000044703484
5.0 5.0 29.166400909423828 29.165199279785156 5.4008002281188965 32.64179992675781 20.24169921875 -0.004000000189989805 4.377999782562256 39.20000076293945 1.7319999933242798 1.3580000400543213 0.024000000208616257
5.5 5.5 29.098400115966797 29.09709930419922 5.383900165557861 32.573001861572266 20.21269989013672 -0.1599999964237213 4.379000186920166 35.29999923706055 1.687000036239624 1.3329999446868896 0.024000000208616257
6.0 6.0 29.042299270629883 29.040800094604492 5.370699882507324 32.520999908447266 20.192399978637695 -0.06499999761581421 4.381999969482422 34.099998474121094 1.6720000505447388 1.3270000219345093 0.024000000208616257
6.5 6.5 29.102399826049805 29.100799560546875 5.387800216674805 32.59640121459961 20.228900909423828 0.0430000014603138 4.380000114440918 33.79999923706055 1.6679999828338623 1.3300000429153442 0.024000000208616257
7.0 7.0 29.27280044555664 29.271099090576172 5.430200099945068 32.768001556396484 20.300800323486328 0.35199999809265137 4.374000072479248 30.399999618530273 1.621999979019165 1.3229999542236328 0.024000000208616257
7.599999904632568 7.5 29.351699829101562 29.349899291992188 5.447199821472168 32.829200744628906 20.32029914855957 -0.6800000071525574 4.380000114440918 27.799999237060547 1.5829999446868896 1.3270000219345093 0.024000000208616257
8.100000381469727 8.0 29.37420082092285 29.37220001220703 5.45419979095459 32.86090087890625 20.33650016784668 0.08100000023841858 4.386000156402588 27.700000762939453 1.5820000171661377 1.3350000381469727 0.027000000700354576
8.600000381469727 8.5 29.38450050354004 29.382400512695312 5.455900192260742 32.865699768066406 20.33690071105957 -0.4749999940395355 4.38700008392334 25.600000381469727 1.5470000505447388 1.3339999914169312 0.024000000208616257
9.100000381469727 9.0 29.322999954223633 29.32080078125 5.440400123596191 32.80220031738281 20.309799194335938 1.0119999647140503 4.386000156402588 24.0 1.5199999809265137 1.3289999961853027 0.023000000044703484
9.600000381469727 9.5 29.346799850463867 29.344499588012695 5.448299884796143 32.83940124511719 20.329700469970703 -0.414000004529953 4.385000228881836 23.200000762939453 1.503999948501587 1.3359999656677246 0.02199999988079071
10.100000381469727 10.0 29.486600875854492 29.484100341796875 5.479599952697754 32.955299377441406 20.369800567626953 -0.382999986410141 4.386000156402588 22.399999618530273 1.4889999628067017 1.3589999675750732 0.023000000044703484
10.600000381469727 10.5 29.5132999420166 29.510700225830078 5.4980998039245605 33.06209945678711 20.440900802612305 0.12600000202655792 4.390999794006348 21.299999237060547 1.468000054359436 1.3680000305175781 0.023000000044703484
11.100000381469727 11.0 29.526500701904297 29.523799896240234 5.5106000900268555 33.13759994506836 20.493000030517578 0.0010000000474974513 4.3979997634887695 20.5 1.4500000476837158 1.371000051498413 0.023000000044703484
11.600000381469727 11.5 29.522899627685547 29.520099639892578 5.514999866485596 33.169898986816406 20.518400192260742 0.19099999964237213 4.39900016784668 19.5 1.4290000200271606 1.36899995803833 0.024000000208616257
12.100000381469727 12.0 29.51799964904785 29.515100479125977 5.51639986038208 33.182701110839844 20.529600143432617 -0.10499999672174454 4.4039998054504395 18.600000381469727 1.409000039100647 1.3639999628067017 0.023000000044703484
12.600000381469727 12.5 29.513099670410156 29.510000228881836 5.514100074768066 33.169898986816406 20.521699905395508 0.3319999873638153 4.4029998779296875 18.100000381469727 1.3960000276565552 1.3580000400543213 0.02199999988079071
13.100000381469727 13.0 29.504899978637695 29.501699447631836 5.517600059509277 33.19940185546875 20.546600341796875 -0.14300000667572021 4.3979997634887695 17.5 1.3830000162124634 1.3650000095367432 0.02199999988079071
13.600000381469727 13.5 29.47949981689453 29.476200103759766 5.5208001136779785 33.23830032348633 20.584199905395508 -0.23600000143051147 4.39900016784668 16.799999237060547 1.3650000095367432 1.3589999675750732 0.02199999988079071
14.100000381469727 14.0 29.476699829101562 29.47330093383789 5.521999835968018 33.24800109863281 20.592500686645508 -0.07199999690055847 4.400000095367432 16.100000381469727 1.3459999561309814 1.3589999675750732 0.02199999988079071
14.600000381469727 14.5 29.47610092163086 29.47249984741211 5.524400234222412 33.26459884643555 20.604999542236328 -0.09300000220537186 4.401000022888184 15.399999618530273 1.3270000219345093 1.371000051498413 0.023000000044703484
15.100000381469727 15.0 29.477100372314453 29.473400115966797 5.5258002281188965 33.27320098876953 20.611099243164062 -0.33799999952316284 4.401000022888184 14.699999809265137 1.3070000410079956 1.371999979019165 0.02199999988079071
15.600000381469727 15.5 29.480600357055664 29.4768009185791 5.52869987487793 33.29029846191406 20.622800827026367 -0.017999999225139618 4.394999980926514 14.199999809265137 1.2910000085830688 1.3980000019073486 0.02199999988079071
16.100000381469727 16.0 29.486900329589844 29.482999801635742 5.539700031280518 33.36029815673828 20.673099517822266 0.09000000357627869 4.389999866485596 14.0 1.284999966621399 1.409000039100647 0.02199999988079071
16.600000381469727 16.5 29.426799774169922 29.422800064086914 5.543799877166748 33.43000030517578 20.7455997467041 -2.1519999504089355 4.392000198364258 13.600000381469727 1.2719999551773071 1.4190000295639038 0.02199999988079071
17.100000381469727 17.0 29.346099853515625 29.341899871826172 5.54010009765625 33.46049880981445 20.79560089111328 0.2370000034570694 4.385000228881836 13.0 1.2519999742507935 1.4329999685287476 0.023000000044703484
17.600000381469727 17.5 29.219200134277344 29.21489906311035 5.550899982452393 33.62260055541992 20.9596004486084 -0.8339999914169312 4.367000102996826 12.300000190734863 1.2300000190734863 1.465000033378601 0.024000000208616257
18.100000381469727 18.0 29.151500701904297 29.1471004486084 5.560200214385986 33.7333984375 21.06529998779297 0.503000020980835 4.361999988555908 11.800000190734863 1.2100000381469727 1.5069999694824219 0.024000000208616257
18.600000381469727 18.5 28.870100021362305 28.8656005859375 5.561600208282471 33.94240188598633 21.31570053100586 0.057999998331069946 4.334000110626221 11.399999618530273 1.1959999799728394 1.569000005722046 0.024000000208616257
19.100000381469727 19.0 28.588600158691406 28.583999633789062 5.5630998611450195 34.15340042114258 21.56730079650879 -0.6449999809265137 4.322000026702881 11.100000381469727 1.1859999895095825 1.7109999656677246 0.02500000037252903
19.600000381469727 19.5 28.29010009765625 28.285499572753906 5.557700157165527 34.33190155029297 21.79960060119629 0.15299999713897705 4.326000213623047 10.699999809265137 1.1670000553131104 1.8229999542236328 0.027000000700354576
20.100000381469727 20.0 27.99169921875 27.986900329589844 5.5524001121521 34.51210021972656 22.032699584960938 -0.04500000178813934 4.326000213623047 10.0 1.1399999856948853 1.8480000495910645 0.03099999949336052
20.600000381469727 20.5 27.693199157714844 27.688400268554688 5.547100067138672 34.69430160522461 22.266700744628906 -0.13600000739097595 4.335000038146973 9.25 1.1050000190734863 1.809000015258789 0.029999999329447746
21.100000381469727 21.0 27.548900604248047 27.54400062561035 5.537099838256836 34.73040008544922 22.340599060058594 -2.575000047683716 4.339000225067139 8.609999656677246 1.0740000009536743 1.7740000486373901 0.028999999165534973
21.600000381469727 21.5 27.366300582885742 27.361299514770508 5.519599914550781 34.7421989440918 22.408300399780273 1.8279999494552612 4.335000038146973 8.069999694824219 1.0460000038146973 1.7519999742507935 0.028999999165534973
22.100000381469727 22.0 27.04669952392578 27.04159927368164 5.502500057220459 34.8588981628418 22.598600387573242 -0.18799999356269836 4.289999961853027 7.5 1.0140000581741333 1.875 0.029999999329447746
22.700000762939453 22.5 26.727100372314453 26.721900939941406 5.485300064086914 34.97669982910156 22.789100646972656 0.24799999594688416 4.300000190734863 7.050000190734863 0.9869999885559082 1.8170000314712524 0.035999998450279236
23.200000762939453 23.0 26.496700286865234 26.491500854492188 5.4629998207092285 34.990501403808594 22.872400283813477 0.05900000035762787 4.27400016784668 6.5 0.9520000219345093 1.875 0.039000000804662704
23.700000762939453 23.5 26.42329978942871 26.417999267578125 5.459199905395508 35.018798828125 22.91670036315918 -0.22100000083446503 4.204999923706055 6.039999961853027 0.9200000166893005 1.909000039100647 0.04699999839067459

In total, there are 43 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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