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Dataset Title:  "LATEX CTD - d92c036.nc - 28.84N, 92.0W - 1992-11-07" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: latex_d92c036)
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: 46)
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   46 options
    depth ?  =  m   46 options
    temperature ?  =  degree_C   41 options
    potentialTemperature ?  =  degree_C   37 options
    conductivity ?  =  Siemens per meter   21 options
    salinity ?  =  PSU   19 options
    sigmat ?  =  kg m-3   18 options
    descentRate ?  =  meters per second   46 options
    transmission ?  =  percent   35 options
    par ?  =  umol m-2 s-1   46 options
    parv ?  =  volts   46 options
    fluorescence ?  =  volts   35 options
    backscattering ?  =  volts   1 option: -9.0

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)  

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
3.5 3.5 22.512399673461914 22.511699676513672 4.891900062561035 33.78300094604492 23.151399612426758 0.11900000274181366 3.49399995803833 679.0 3.861999988555908 0.546999990940094 -9.0
4.0 4.0 22.513700485229492 22.51289939880371 4.892099857330322 33.783199310302734 23.151100158691406 0.6069999933242798 3.49399995803833 582.0 3.7950000762939453 0.5910000205039978 -9.0
4.5 4.5 22.514799118041992 22.513900756835938 4.892199993133545 33.78310012817383 23.15089988708496 0.5839999914169312 3.50600004196167 420.0 3.6530001163482666 0.6129999756813049 -9.0
5.0 5.0 22.516599655151367 22.515499114990234 4.892399787902832 33.78340148925781 23.15060043334961 0.6639999747276306 3.497999906539917 346.0 3.569000005722046 0.6349999904632568 -9.0
5.5 5.5 22.51689910888672 22.51580047607422 4.892499923706055 33.78350067138672 23.15060043334961 0.6990000009536743 3.486999988555908 290.0 3.493000030517578 0.6549999713897705 -9.0
6.0 6.0 22.516399383544922 22.515199661254883 4.892499923706055 33.78340148925781 23.150699615478516 0.7020000219345093 3.499000072479248 237.0 3.4040000438690186 0.6769999861717224 -9.0
6.5 6.5 22.515300750732422 22.513999938964844 4.892300128936768 33.78310012817383 23.150800704956055 0.7369999885559082 3.492000102996826 199.0 3.3299999237060547 0.6759999990463257 -9.0
7.0 7.0 22.51490020751953 22.513500213623047 4.892300128936768 33.783199310302734 23.150999069213867 0.800000011920929 3.500999927520752 166.0 3.25 0.6740000247955322 -9.0
7.599999904632568 7.5 22.515600204467773 22.51409912109375 4.892399787902832 33.78340148925781 23.150999069213867 0.8550000190734863 3.4860000610351562 136.0 3.1630001068115234 0.6679999828338623 -9.0
8.100000381469727 8.0 22.514400482177734 22.512800216674805 4.892300128936768 33.78310012817383 23.151199340820312 0.875 3.4820001125335693 111.0 3.075000047683716 0.6620000004768372 -9.0
8.600000381469727 8.5 22.513399124145508 22.511699676513672 4.892199993133545 33.78310012817383 23.151399612426758 0.8489999771118164 3.4739999771118164 89.5 2.9820001125335693 0.671999990940094 -9.0
9.100000381469727 9.0 22.514299392700195 22.512500762939453 4.892300128936768 33.783199310302734 23.15130043029785 0.7730000019073486 3.506999969482422 73.0999984741211 2.8940000534057617 0.6620000004768372 -9.0
9.600000381469727 9.5 22.5137996673584 22.511899948120117 4.892300128936768 33.782901763916016 23.151199340820312 0.6710000038146973 3.509999990463257 62.70000076293945 2.8269999027252197 0.6520000100135803 -9.0
10.100000381469727 10.0 22.512500762939453 22.510499954223633 4.892199993133545 33.78300094604492 23.15169906616211 0.656000018119812 3.486999988555908 54.400001525878906 2.7660000324249268 0.6650000214576721 -9.0
10.600000381469727 10.5 22.51219940185547 22.510099411010742 4.892199993133545 33.78300094604492 23.15180015563965 0.7749999761581421 3.503000020980835 45.20000076293945 2.684999942779541 0.6579999923706055 -9.0
11.100000381469727 11.0 22.51020050048828 22.507999420166016 4.892000198364258 33.78300094604492 23.15239906311035 0.8960000276565552 3.492000102996826 37.099998474121094 2.5989999771118164 0.6489999890327454 -9.0
11.600000381469727 11.5 22.51099967956543 22.508699417114258 4.892099857330322 33.78300094604492 23.15220069885254 0.9620000123977661 3.486999988555908 30.200000762939453 2.509999990463257 0.6660000085830688 -9.0
12.100000381469727 12.0 22.51110076904297 22.508699417114258 4.892099857330322 33.78300094604492 23.15220069885254 0.9549999833106995 3.490000009536743 25.100000381469727 2.428999900817871 0.6499999761581421 -9.0
12.600000381469727 12.5 22.511999130249023 22.50950050354004 4.892199993133545 33.782901763916016 23.151899337768555 0.8740000128746033 3.51200008392334 21.5 2.36299991607666 0.6389999985694885 -9.0
13.100000381469727 13.0 22.512500762939453 22.509899139404297 4.892300128936768 33.782798767089844 23.15169906616211 0.7350000143051147 3.5250000953674316 19.0 2.309000015258789 0.6439999938011169 -9.0
13.600000381469727 13.5 22.51219940185547 22.50950050354004 4.892300128936768 33.782798767089844 23.15180015563965 0.6159999966621399 3.5280001163482666 17.100000381469727 2.26200008392334 0.6489999890327454 -9.0
14.100000381469727 14.0 22.511699676513672 22.508899688720703 4.892300128936768 33.78300094604492 23.15220069885254 0.6370000243186951 3.5329999923706055 14.699999809265137 2.197000026702881 0.671999990940094 -9.0
14.600000381469727 14.5 22.51300048828125 22.510099411010742 4.892499923706055 33.783199310302734 23.152000427246094 0.7789999842643738 3.5250000953674316 12.100000381469727 2.11299991607666 0.6589999794960022 -9.0
15.100000381469727 15.0 22.5132999420166 22.510299682617188 4.892499923706055 33.78310012817383 23.15180015563965 0.8939999938011169 3.494999885559082 9.949999809265137 2.0280001163482666 0.6389999985694885 -9.0
15.600000381469727 15.5 22.51420021057129 22.51110076904297 4.892600059509277 33.78340148925781 23.15180015563965 0.9480000138282776 3.4649999141693115 8.319999694824219 1.9500000476837158 0.6359999775886536 -9.0
16.100000381469727 16.0 22.513700485229492 22.510499954223633 4.892600059509277 33.78329849243164 23.151899337768555 0.9459999799728394 3.4600000381469727 7.179999828338623 1.8860000371932983 0.6499999761581421 -9.0
16.600000381469727 16.5 22.51409912109375 22.510799407958984 4.8927001953125 33.78369903564453 23.152099609375 0.8949999809265137 3.4739999771118164 6.380000114440918 1.8350000381469727 0.6520000100135803 -9.0
17.100000381469727 17.0 22.515300750732422 22.511899948120117 4.8927998542785645 33.78310012817383 23.15130043029785 0.8180000185966492 3.494999885559082 5.820000171661377 1.7949999570846558 0.6449999809265137 -9.0
17.600000381469727 17.5 22.516300201416016 22.512800216674805 4.892899990081787 33.78340148925781 23.151399612426758 0.7639999985694885 3.497999906539917 5.320000171661377 1.75600004196167 0.6230000257492065 -9.0
18.100000381469727 18.0 22.517799377441406 22.51420021057129 4.893199920654297 33.7843017578125 23.151599884033203 0.7390000224113464 3.4830000400543213 4.699999809265137 1.7020000219345093 0.6380000114440918 -9.0
18.600000381469727 18.5 22.51799964904785 22.514299392700195 4.8933000564575195 33.784400939941406 23.151599884033203 0.7089999914169312 3.4690001010894775 3.950000047683716 1.6269999742507935 0.6660000085830688 -9.0
19.100000381469727 19.0 22.51849937438965 22.514699935913086 4.893400192260742 33.78450012207031 23.151599884033203 0.6819999814033508 3.4649999141693115 3.240000009536743 1.5399999618530273 0.6539999842643738 -9.0
19.600000381469727 19.5 22.519399642944336 22.515499114990234 4.893499851226807 33.7848014831543 23.15169906616211 0.7239999771118164 3.4519999027252197 2.680000066757202 1.4579999446868896 0.6359999775886536 -9.0
20.100000381469727 20.0 22.519699096679688 22.515600204467773 4.893599987030029 33.78519821166992 23.151899337768555 0.8479999899864197 3.437999963760376 2.309999942779541 1.3930000066757202 0.6320000290870667 -9.0
20.600000381469727 20.5 22.519500732421875 22.515300750732422 4.893599987030029 33.78499984741211 23.151899337768555 0.968999981880188 3.427999973297119 2.049999952316284 1.3420000076293945 0.6340000033378601 -9.0
21.100000381469727 21.0 22.520299911499023 22.516000747680664 4.893700122833252 33.785099029541016 23.15169906616211 1.0329999923706055 3.4159998893737793 1.8200000524520874 1.2910000085830688 0.6269999742507935 -9.0
21.600000381469727 21.5 22.52039909362793 22.51609992980957 4.893799781799316 33.78519821166992 23.15180015563965 1.0099999904632568 3.4079999923706055 1.6100000143051147 1.2380000352859497 0.6259999871253967 -9.0
22.100000381469727 22.0 22.52090072631836 22.51650047302246 4.893799781799316 33.785301208496094 23.15169906616211 0.8669999837875366 3.4140000343322754 1.409999966621399 1.1799999475479126 0.6150000095367432 -9.0
22.700000762939453 22.5 22.520700454711914 22.516199111938477 4.893799781799316 33.785099029541016 23.15169906616211 0.5370000004768372 3.437999963760376 1.190000057220459 1.1059999465942383 0.6110000014305115 -9.0
23.200000762939453 23.0 22.520999908447266 22.516399383544922 4.893799781799316 33.7849006652832 23.151500701904297 0.2840000092983246 3.447000026702881 0.9399999976158142 1.003999948501587 0.6110000014305115 -9.0
23.700000762939453 23.5 22.5216007232666 22.516799926757812 4.893899917602539 33.785099029541016 23.151500701904297 0.4560000002384186 3.444000005722046 0.8299999833106995 0.9480000138282776 0.6129999756813049 -9.0
24.200000762939453 24.0 22.5216007232666 22.516799926757812 4.894000053405762 33.785400390625 23.15169906616211 0.5979999899864197 3.4240000247955322 0.7400000095367432 0.9010000228881836 0.6010000109672546 -9.0
24.700000762939453 24.5 22.521799087524414 22.51689910888672 4.894000053405762 33.785301208496094 23.151599884033203 0.5590000152587891 3.4240000247955322 0.6299999952316284 0.8320000171661377 0.6039999723434448 -9.0
25.200000762939453 25.0 22.5221004486084 22.517099380493164 4.894000053405762 33.78499984741211 23.151399612426758 0.33399999141693115 3.437000036239624 0.5299999713897705 0.7540000081062317 0.5870000123977661 -9.0
25.700000762939453 25.5 22.52239990234375 22.517200469970703 4.894100189208984 33.785099029541016 23.151399612426758 0.2409999966621399 3.3889999389648438 0.4699999988079071 0.6990000009536743 0.6150000095367432 -9.0
26.200000762939453 26.0 22.522600173950195 22.51729965209961 4.894100189208984 33.78499984741211 23.15130043029785 0.29100000858306885 3.4119999408721924 0.38999998569488525 0.6259999871253967 0.6179999709129333 -9.0

In total, there are 46 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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