Metocean: Historical collections
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Dataset Title: | "LATEX CTD - d94j080.nc - 28.66N, 94.0W - 1994-11-07" |
Institution: | Texas A&M University, Department of Oceanography (Dataset ID: latex_d94j080) |
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 |
2.0 | 2.0 | 24.61709976196289 | 24.61669921875 | 5.081099987030029 | 33.617401123046875 | 22.413799285888672 | 0.12399999797344208 | 4.326000213623047 | 1450.0 | 3.3010001182556152 | 1.2130000591278076 | -9.0 |
2.5 | 2.5 | 24.62540054321289 | 24.624799728393555 | 5.082200050354004 | 33.619300842285156 | 22.412700653076172 | 0.3700000047683716 | 4.331999778747559 | 1140.0 | 3.194999933242798 | 1.2209999561309814 | 0.003000000026077032 |
3.0 | 3.0 | 24.62649917602539 | 24.625900268554688 | 5.082399845123291 | 33.62009811401367 | 22.413000106811523 | 0.5669999718666077 | 4.333000183105469 | 1050.0 | 3.1610000133514404 | 1.225000023841858 | 0.014999999664723873 |
3.5 | 3.5 | 24.626100540161133 | 24.62529945373535 | 5.082399845123291 | 33.620399475097656 | 22.413400650024414 | 0.35899999737739563 | 4.335000038146973 | 944.0 | 3.114000082015991 | 1.222000002861023 | 0.026000000536441803 |
4.0 | 4.0 | 24.62540054321289 | 24.624500274658203 | 5.082300186157227 | 33.61980056762695 | 22.41320037841797 | 0.3319999873638153 | 4.333000183105469 | 910.0 | 3.0980000495910645 | 1.2410000562667847 | 0.02800000086426735 |
4.5 | 4.5 | 24.622100830078125 | 24.6210994720459 | 5.081999778747559 | 33.619598388671875 | 22.414100646972656 | 0.414000004529953 | 4.331999778747559 | 901.0 | 3.0940001010894775 | 1.2790000438690186 | 0.027000000700354576 |
5.0 | 5.0 | 24.618600845336914 | 24.61750030517578 | 5.081600189208984 | 33.61940002441406 | 22.415000915527344 | 0.3799999952316284 | 4.327000141143799 | 678.0 | 2.9700000286102295 | 1.2949999570846558 | 0.027000000700354576 |
5.5 | 5.5 | 24.59320068359375 | 24.591999053955078 | 5.079100131988525 | 33.61949920654297 | 22.422700881958008 | 0.796999990940094 | 4.324999809265137 | 697.0 | 2.9820001125335693 | 1.3029999732971191 | 0.026000000536441803 |
6.0 | 6.0 | 24.577999114990234 | 24.57670021057129 | 5.078100204467773 | 33.62289810180664 | 22.429899215698242 | 0.8349999785423279 | 4.326000213623047 | 452.0 | 2.7939999103546143 | 1.3240000009536743 | 0.027000000700354576 |
6.5 | 6.5 | 24.592500686645508 | 24.591100692749023 | 5.081699848175049 | 33.63869857788086 | 22.4375 | 0.6029999852180481 | 4.323999881744385 | 508.0 | 2.8450000286102295 | 1.3359999656677246 | 0.028999999165534973 |
7.0 | 7.0 | 24.624000549316406 | 24.622499465942383 | 5.087800025939941 | 33.660400390625 | 22.444599151611328 | 0.7379999756813049 | 4.321000099182129 | 557.0 | 2.884999990463257 | 1.3609999418258667 | 0.03200000151991844 |
7.599999904632568 | 7.5 | 24.65180015563965 | 24.65019989013672 | 5.093900203704834 | 33.684600830078125 | 22.454500198364258 | 0.9470000267028809 | 4.315999984741211 | 454.0 | 2.7960000038146973 | 1.3769999742507935 | 0.0430000014603138 |
8.100000381469727 | 8.0 | 24.692899703979492 | 24.691200256347656 | 5.1020002365112305 | 33.71379852294922 | 22.46430015563965 | 0.8989999890327454 | 4.315000057220459 | 479.0 | 2.819000005722046 | 1.3940000534057617 | 0.03500000014901161 |
8.600000381469727 | 8.5 | 24.747100830078125 | 24.74519920349121 | 5.11359977722168 | 33.759700775146484 | 22.482799530029297 | 0.6309999823570251 | 4.307000160217285 | 448.0 | 2.7899999618530273 | 1.409999966621399 | 0.03099999949336052 |
9.100000381469727 | 9.0 | 24.82539939880371 | 24.82349967956543 | 5.13040018081665 | 33.824798583984375 | 22.508399963378906 | 0.6890000104904175 | 4.308000087738037 | 407.0 | 2.749000072479248 | 1.4789999723434448 | 0.02800000086426735 |
9.600000381469727 | 9.5 | 24.86750030517578 | 24.865400314331055 | 5.138700008392334 | 33.85449981689453 | 22.518199920654297 | 0.8209999799728394 | 4.304999828338623 | 388.0 | 2.7279999256134033 | 1.4730000495910645 | 0.02800000086426735 |
10.100000381469727 | 10.0 | 24.909799575805664 | 24.90760040283203 | 5.14709997177124 | 33.885101318359375 | 22.52869987487793 | 0.7360000014305115 | 4.302999973297119 | 371.0 | 2.7079999446868896 | 1.472000002861023 | 0.03400000184774399 |
10.600000381469727 | 10.5 | 24.93000030517578 | 24.92770004272461 | 5.151100158691406 | 33.899200439453125 | 22.533199310302734 | 0.45500001311302185 | 4.302000045776367 | 339.0 | 2.6689999103546143 | 1.4819999933242798 | 0.03200000151991844 |
11.100000381469727 | 11.0 | 24.957300186157227 | 24.95490074157715 | 5.156499862670898 | 33.918800354003906 | 22.5398006439209 | 0.36399999260902405 | 4.301000118255615 | 308.0 | 2.628000020980835 | 1.5149999856948853 | 0.02800000086426735 |
11.600000381469727 | 11.5 | 24.997299194335938 | 24.994800567626953 | 5.164899826049805 | 33.95029830932617 | 22.551599502563477 | 0.4259999990463257 | 4.301000118255615 | 285.0 | 2.5940001010894775 | 1.531999945640564 | 0.029999999329447746 |
12.100000381469727 | 12.0 | 25.041099548339844 | 25.03849983215332 | 5.175899982452393 | 33.99850082397461 | 22.574800491333008 | 0.3230000138282776 | 4.297999858856201 | 301.0 | 2.618000030517578 | 1.5410000085830688 | 0.03200000151991844 |
12.600000381469727 | 12.5 | 25.071199417114258 | 25.068500518798828 | 5.187699794769287 | 34.06290054321289 | 22.614200592041016 | 0.4560000002384186 | 4.294000148773193 | 264.0 | 2.559999942779541 | 1.555999994277954 | 0.029999999329447746 |
13.100000381469727 | 13.0 | 25.03070068359375 | 25.02790069580078 | 5.186100006103516 | 34.08100128173828 | 22.640199661254883 | 0.6039999723434448 | 4.2820000648498535 | 268.0 | 2.568000078201294 | 1.559000015258789 | 0.035999998450279236 |
13.600000381469727 | 13.5 | 25.03030014038086 | 25.02739906311035 | 5.190400123596191 | 34.11330032348633 | 22.6648006439209 | 0.5170000195503235 | 4.2729997634887695 | 235.0 | 2.510999917984009 | 1.569000005722046 | 0.039000000804662704 |
14.100000381469727 | 14.0 | 25.06450080871582 | 25.061399459838867 | 5.1981000900268555 | 34.14419937133789 | 22.677799224853516 | 0.3479999899864197 | 4.269999980926514 | 242.0 | 2.5220000743865967 | 1.5789999961853027 | 0.035999998450279236 |
14.600000381469727 | 14.5 | 25.168399810791016 | 25.165300369262695 | 5.218500137329102 | 34.21620178222656 | 22.700700759887695 | 0.5789999961853027 | 4.2729997634887695 | 197.0 | 2.433000087738037 | 1.600000023841858 | 0.03500000014901161 |
15.100000381469727 | 15.0 | 25.284799575805664 | 25.2814998626709 | 5.245999813079834 | 34.330299377441406 | 22.751399993896484 | 0.6700000166893005 | 4.264999866485596 | 199.0 | 2.437000036239624 | 1.6150000095367432 | 0.03700000047683716 |
15.600000381469727 | 15.5 | 25.34040069580078 | 25.336999893188477 | 5.270599842071533 | 34.469200134277344 | 22.83930015563965 | 0.5770000219345093 | 4.2170000076293945 | 210.0 | 2.4609999656677246 | 1.6380000114440918 | 0.04100000113248825 |
16.100000381469727 | 16.0 | 25.339599609375 | 25.33609962463379 | 5.275000095367432 | 34.5015983581543 | 22.864099502563477 | 0.32600000500679016 | 4.190000057220459 | 177.0 | 2.388000011444092 | 1.6690000295639038 | 0.04699999839067459 |
16.600000381469727 | 16.5 | 25.356199264526367 | 25.352500915527344 | 5.282599925994873 | 34.54460144042969 | 22.89150047302246 | 0.44200000166893005 | 4.144999980926514 | 169.0 | 2.367000102996826 | 1.7020000219345093 | 0.04399999976158142 |
17.100000381469727 | 17.0 | 25.364099502563477 | 25.36039924621582 | 5.286300182342529 | 34.56610107421875 | 22.90530014038086 | 0.3930000066757202 | 4.085000038146973 | 171.0 | 2.371000051498413 | 1.74399995803833 | 0.04800000041723251 |
17.600000381469727 | 17.5 | 25.381500244140625 | 25.377700805664062 | 5.292500019073486 | 34.59830093383789 | 22.924299240112305 | 0.4129999876022339 | 4.072000026702881 | 149.0 | 2.312000036239624 | 1.8209999799728394 | 0.06499999761581421 |
18.100000381469727 | 18.0 | 25.42169952392578 | 25.417699813842773 | 5.3028998374938965 | 34.643699645996094 | 22.946300506591797 | 0.675000011920929 | 4.061999797821045 | 154.0 | 2.3259999752044678 | 1.8370000123977661 | 0.06400000303983688 |
18.600000381469727 | 18.5 | 25.447599411010742 | 25.443500518798828 | 5.309299945831299 | 34.670799255371094 | 22.958900451660156 | 0.7009999752044678 | 4.014999866485596 | 150.0 | 2.313999891281128 | 1.843000054359436 | 0.07100000232458115 |
19.100000381469727 | 19.0 | 25.46150016784668 | 25.457300186157227 | 5.3125 | 34.68389892578125 | 22.964599609375 | 0.460999995470047 | 3.99399995803833 | 134.0 | 2.2669999599456787 | 1.8509999513626099 | 0.07900000363588333 |
19.600000381469727 | 19.5 | 25.485200881958008 | 25.480899810791016 | 5.317599773406982 | 34.70249938964844 | 22.971399307250977 | 0.640999972820282 | 3.9660000801086426 | 130.0 | 2.253999948501587 | 1.8609999418258667 | 0.07500000298023224 |
20.100000381469727 | 20.0 | 25.507600784301758 | 25.50309944152832 | 5.322299957275391 | 34.72050094604492 | 22.978099822998047 | 0.7160000205039978 | 3.8940000534057617 | 116.0 | 2.2039999961853027 | 1.9320000410079956 | 0.07599999755620956 |
20.600000381469727 | 20.5 | 25.526399612426758 | 25.521799087524414 | 5.3267998695373535 | 34.73889923095703 | 22.9862003326416 | 0.5260000228881836 | 3.8359999656677246 | 105.0 | 2.1589999198913574 | 1.965999960899353 | 0.09300000220537186 |
21.100000381469727 | 21.0 | 25.532499313354492 | 25.52790069580078 | 5.329699993133545 | 34.75519943237305 | 22.996700286865234 | 0.3919999897480011 | 3.802000045776367 | 97.9000015258789 | 2.130000114440918 | 1.8799999952316284 | 0.10700000077486038 |
21.600000381469727 | 21.5 | 25.561399459838867 | 25.55660057067871 | 5.339099884033203 | 34.80160140991211 | 23.022899627685547 | 0.6309999823570251 | 3.743000030517578 | 86.9000015258789 | 2.078000068664551 | 1.8509999513626099 | 0.1080000028014183 |
22.100000381469727 | 22.0 | 25.577199935913086 | 25.57229995727539 | 5.344900131225586 | 34.83190155029297 | 23.0408992767334 | 0.6140000224113464 | 3.7699999809265137 | 82.4000015258789 | 2.055000066757202 | 1.8350000381469727 | 0.12200000137090683 |
22.700000762939453 | 22.5 | 25.58930015563965 | 25.584299087524414 | 5.350100040435791 | 34.86109924316406 | 23.05929946899414 | 0.39500001072883606 | 3.815000057220459 | 78.69999694824219 | 2.0350000858306885 | 1.7829999923706055 | 0.1340000033378601 |
23.200000762939453 | 23.0 | 25.61440086364746 | 25.60930061340332 | 5.359000205993652 | 34.906700134277344 | 23.086000442504883 | 0.6449999809265137 | 3.8940000534057617 | 71.4000015258789 | 1.9930000305175781 | 1.75 | 0.1289999932050705 |
23.700000762939453 | 23.5 | 25.627399444580078 | 25.62220001220703 | 5.363399982452393 | 34.92890167236328 | 23.098800659179688 | 0.7089999914169312 | 3.9709999561309814 | 64.4000015258789 | 1.9479999542236328 | 1.7300000190734863 | 0.12600000202655792 |
24.200000762939453 | 24.0 | 25.637300491333008 | 25.631999969482422 | 5.366499900817871 | 34.94390106201172 | 23.107099533081055 | 0.47600001096725464 | 3.9809999465942383 | 59.099998474121094 | 1.9110000133514404 | 1.7039999961853027 | 0.10899999737739563 |
24.700000762939453 | 24.5 | 25.630300521850586 | 25.624900817871094 | 5.364299774169922 | 34.932498931884766 | 23.10070037841797 | 0.49799999594688416 | 3.941999912261963 | 52.400001525878906 | 1.8580000400543213 | 1.6959999799728394 | 0.10599999874830246 |
25.200000762939453 | 25.0 | 25.680500030517578 | 25.674999237060547 | 5.3796000480651855 | 35.00640106201172 | 23.141000747680664 | 0.4779999852180481 | 3.878999948501587 | 49.099998474121094 | 1.8300000429153442 | 1.7059999704360962 | 0.10100000351667404 |
25.700000762939453 | 25.5 | 25.704599380493164 | 25.69890022277832 | 5.38730001449585 | 35.0443000793457 | 23.162200927734375 | 0.4059999883174896 | 3.822000026702881 | 44.79999923706055 | 1.7899999618530273 | 1.6859999895095825 | 0.11299999803304672 |
26.200000762939453 | 26.0 | 25.716400146484375 | 25.710599899291992 | 5.3907999992370605 | 35.060699462890625 | 23.17099952697754 | 0.3869999945163727 | 3.7260000705718994 | 40.79999923706055 | 1.75 | 1.6740000247955322 | 0.11299999803304672 |
26.700000762939453 | 26.5 | 25.714099884033203 | 25.708200454711914 | 5.390200138092041 | 35.05799865722656 | 23.169599533081055 | 0.4359999895095825 | 3.74399995803833 | 37.599998474121094 | 1.7139999866485596 | 1.6480000019073486 | 0.11999999731779099 |
27.200000762939453 | 27.0 | 25.715499877929688 | 25.70949935913086 | 5.390600204467773 | 35.059600830078125 | 23.170499801635742 | 0.35899999737739563 | 3.6519999504089355 | 34.70000076293945 | 1.6790000200271606 | 1.6330000162124634 | 0.14399999380111694 |
27.700000762939453 | 27.5 | 25.715299606323242 | 25.709199905395508 | 5.390699863433838 | 35.05979919433594 | 23.170799255371094 | 0.20100000500679016 | 3.5799999237060547 | 30.700000762939453 | 1.6260000467300415 | 1.628000020980835 | 0.164000004529953 |
In total, there are 52 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.