Metocean: Historical collections
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Dataset Title: | "LATEX CTD - d92c032.nc - 29.04N, 92.0W - 1992-11-07" |
Institution: | Texas A&M University, Department of Oceanography (Dataset ID: latex_d92c032) |
Information: | Summary | License | FGDC | ISO 19115 | Metadata | Background | Data Access Form | Files | Make a graph |
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.
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 | 20.62820053100586 | 20.627700805664062 | 4.329500198364258 | 30.78510093688965 | 21.3882999420166 | -0.17499999701976776 | 3.635999917984009 | 1210.0 | 4.11299991607666 | 1.003999948501587 | -9.0 |
3.0 | 3.0 | 20.625600814819336 | 20.625 | 4.3292999267578125 | 30.785200119018555 | 21.38909912109375 | 0.28299999237060547 | 3.6600000858306885 | 893.0 | 3.9809999465942383 | 1.0160000324249268 | -9.0 |
3.5 | 3.5 | 20.62350082397461 | 20.622800827026367 | 4.329100131988525 | 30.785200119018555 | 21.389699935913086 | 0.6700000166893005 | 3.6579999923706055 | 718.0 | 3.885999917984009 | 1.184000015258789 | -9.0 |
4.0 | 4.0 | 20.625 | 20.624300003051758 | 4.3292999267578125 | 30.785900115966797 | 21.389799118041992 | 0.5120000243186951 | 3.6640000343322754 | 631.0 | 3.8299999237060547 | 1.2039999961853027 | -9.0 |
4.5 | 4.5 | 20.62540054321289 | 20.62459945678711 | 4.329500198364258 | 30.786699295043945 | 21.390300750732422 | 0.3330000042915344 | 3.6679999828338623 | 494.0 | 3.7239999771118164 | 1.2489999532699585 | -9.0 |
5.0 | 5.0 | 20.618900299072266 | 20.618000030517578 | 4.328700065612793 | 30.784700393676758 | 21.390499114990234 | 0.5139999985694885 | 3.6600000858306885 | 378.0 | 3.6080000400543213 | 1.2769999504089355 | -9.0 |
5.5 | 5.5 | 20.616899490356445 | 20.61590003967285 | 4.328499794006348 | 30.784799575805664 | 21.391199111938477 | 0.6539999842643738 | 3.6559998989105225 | 334.0 | 3.553999900817871 | 1.1959999799728394 | -9.0 |
6.0 | 6.0 | 20.614500045776367 | 20.613399505615234 | 4.328100204467773 | 30.782899856567383 | 21.390300750732422 | 0.6629999876022339 | 3.6619999408721924 | 284.0 | 3.4839999675750732 | 1.1799999475479126 | -9.0 |
6.5 | 6.5 | 20.614099502563477 | 20.612899780273438 | 4.328000068664551 | 30.782499313354492 | 21.390199661254883 | 0.5440000295639038 | 3.6640000343322754 | 241.0 | 3.4119999408721924 | 1.4529999494552612 | -9.0 |
7.0 | 7.0 | 20.61639976501465 | 20.615100860595703 | 4.328400135040283 | 30.783599853515625 | 21.390499114990234 | 0.37299999594688416 | 3.6610000133514404 | 197.0 | 3.3239998817443848 | 1.3200000524520874 | -9.0 |
7.599999904632568 | 7.5 | 20.61590003967285 | 20.614500045776367 | 4.328400135040283 | 30.78420066833496 | 21.39109992980957 | 0.5049999952316284 | 3.6640000343322754 | 156.0 | 3.2219998836517334 | 1.4390000104904175 | -9.0 |
8.100000381469727 | 8.0 | 20.62649917602539 | 20.625 | 4.33050012588501 | 30.793100357055664 | 21.395099639892578 | 0.6499999761581421 | 3.6630001068115234 | 133.0 | 3.1549999713897705 | 1.4240000247955322 | -9.0 |
8.600000381469727 | 8.5 | 20.63319969177246 | 20.63159942626953 | 4.331699848175049 | 30.797199249267578 | 21.396499633789062 | 0.671999990940094 | 3.6640000343322754 | 114.0 | 3.0859999656677246 | 1.409000039100647 | -9.0 |
9.100000381469727 | 9.0 | 20.631900787353516 | 20.630199432373047 | 4.331600189208984 | 30.797100067138672 | 21.396699905395508 | 0.5709999799728394 | 3.671999931335449 | 95.9000015258789 | 3.01200008392334 | 1.465000033378601 | -9.0 |
9.600000381469727 | 9.5 | 20.632699966430664 | 20.63089942932129 | 4.331699848175049 | 30.797399520874023 | 21.396799087524414 | 0.421999990940094 | 3.6740000247955322 | 79.19999694824219 | 2.928999900817871 | 1.3650000095367432 | -9.0 |
10.100000381469727 | 10.0 | 20.65290069580078 | 20.650999069213867 | 4.335400104522705 | 30.81220054626465 | 21.402799606323242 | 0.5130000114440918 | 3.680000066757202 | 65.30000305175781 | 2.8450000286102295 | 1.3029999732971191 | -9.0 |
10.600000381469727 | 10.5 | 20.66900062561035 | 20.66699981689453 | 4.338699817657471 | 30.826400756835938 | 21.409299850463867 | 0.656000018119812 | 3.671999931335449 | 56.900001525878906 | 2.7850000858306885 | 1.4290000200271606 | -9.0 |
11.100000381469727 | 11.0 | 20.682100296020508 | 20.680099487304688 | 4.341100215911865 | 30.83609962463379 | 21.413299560546875 | 0.6840000152587891 | 3.677000045776367 | 49.099998474121094 | 2.7209999561309814 | 1.600000023841858 | -9.0 |
11.600000381469727 | 11.5 | 20.68079948425293 | 20.678699493408203 | 4.340799808502197 | 30.8341007232666 | 21.412200927734375 | 0.5929999947547913 | 3.680999994277954 | 41.5 | 2.6480000019073486 | 1.5490000247955322 | -9.0 |
12.100000381469727 | 12.0 | 20.699399948120117 | 20.697200775146484 | 4.3445000648498535 | 30.849700927734375 | 21.419099807739258 | 0.3330000042915344 | 3.684000015258789 | 32.70000076293945 | 2.5439999103546143 | 1.4479999542236328 | -9.0 |
12.600000381469727 | 12.5 | 20.73780059814453 | 20.73550033569336 | 4.3516998291015625 | 30.879100799560547 | 21.431400299072266 | 0.26600000262260437 | 3.674999952316284 | 28.5 | 2.484999895095825 | 1.246000051498413 | -9.0 |
13.100000381469727 | 13.0 | 20.755599975585938 | 20.75320053100586 | 4.355500221252441 | 30.896099090576172 | 21.439699172973633 | 0.414000004529953 | 3.6740000247955322 | 26.100000381469727 | 2.447000026702881 | 1.2999999523162842 | -9.0 |
13.600000381469727 | 13.5 | 21.25320053100586 | 21.250600814819336 | 4.455699920654297 | 31.322399139404297 | 21.630599975585938 | 0.1889999955892563 | 3.6519999504089355 | 21.700000762939453 | 2.367000102996826 | 1.194000005722046 | -9.0 |
14.100000381469727 | 14.0 | 22.71339988708496 | 22.710599899291992 | 4.771100044250488 | 32.6869010925293 | 22.26180076599121 | 0.3230000138282776 | 3.4660000801086426 | 18.899999618530273 | 2.306999921798706 | 1.0779999494552612 | -9.0 |
14.600000381469727 | 14.5 | 23.84749984741211 | 23.84440040588379 | 5.011099815368652 | 33.66790008544922 | 22.680400848388672 | 0.3149999976158142 | 2.507999897003174 | 17.100000381469727 | 2.26200008392334 | 0.949999988079071 | -9.0 |
15.100000381469727 | 15.0 | 23.946800231933594 | 23.943599700927734 | 5.0329999923706055 | 33.758201599121094 | 22.71980094909668 | 0.16899999976158142 | 1.9470000267028809 | 15.100000381469727 | 2.2090001106262207 | 0.7419999837875366 | -9.0 |
15.600000381469727 | 15.5 | 23.957300186157227 | 23.95400047302246 | 5.033100128173828 | 33.75080108642578 | 22.711200714111328 | 0.42399999499320984 | 1.9160000085830688 | 12.300000190734863 | 2.121000051498413 | 0.7139999866485596 | -9.0 |
16.100000381469727 | 16.0 | 23.960599899291992 | 23.957199096679688 | 5.033599853515625 | 33.75199890136719 | 22.71109962463379 | 0.1860000044107437 | 1.9040000438690186 | 10.199999809265137 | 2.0380001068115234 | 0.6930000185966492 | -9.0 |
In total, there are 28 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.
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.