Metocean: Historical collections
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Dataset Title: | "LATEX CTD - d94i030.nc - 28.83N, 90.51W - 1994-07-29" |
Institution: | Texas A&M University, Department of Oceanography (Dataset ID: latex_d94i030) |
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 | 28.208599090576172 | 28.208099365234375 | 3.4969000816345215 | 20.52869987487793 | 11.490699768066406 | -0.09600000083446503 | 3.0929999351501465 | 578.0 | 2.9010000228881836 | 1.9579999446868896 | 0.20200000703334808 |
2.5 | 2.5 | 28.223100662231445 | 28.22249984741211 | 3.502500057220459 | 20.558799743652344 | 11.508700370788574 | -0.3479999899864197 | 3.0959999561309814 | 473.0 | 2.813999891281128 | 1.9550000429153442 | 0.20200000703334808 |
3.0 | 3.0 | 28.273099899291992 | 28.27239990234375 | 3.5167999267578125 | 20.629899978637695 | 11.546099662780762 | -0.013000000268220901 | 3.0989999771118164 | 340.0 | 2.6700000762939453 | 1.965999960899353 | 0.20100000500679016 |
3.5 | 3.5 | 28.39419937133789 | 28.393400192260742 | 3.570499897003174 | 20.92460060119629 | 11.728300094604492 | 0.12800000607967377 | 3.1089999675750732 | 273.0 | 2.5759999752044678 | 1.975000023841858 | 0.20100000500679016 |
4.0 | 4.0 | 28.63360023498535 | 28.632699966430664 | 3.7237000465393066 | 21.81049919128418 | 12.31410026550293 | -0.003000000026077032 | 3.0920000076293945 | 208.0 | 2.4579999446868896 | 1.9989999532699585 | 0.20100000500679016 |
4.5 | 4.5 | 28.805200576782227 | 28.804100036621094 | 3.980299949645996 | 23.397199630737305 | 13.444100379943848 | -0.020999999716877937 | 3.2079999446868896 | 157.0 | 2.3340001106262207 | 2.0369999408721924 | 0.20000000298023224 |
5.0 | 5.0 | 28.962099075317383 | 28.960899353027344 | 4.172599792480469 | 24.574499130249023 | 14.27280044555664 | -0.1720000058412552 | 3.5 | 112.0 | 2.187999963760376 | 2.0179998874664307 | 0.16300000250339508 |
5.5 | 5.5 | 29.164199829101562 | 29.162900924682617 | 4.3566999435424805 | 25.674699783325195 | 15.029199600219727 | 0.1080000028014183 | 3.75600004196167 | 82.19999694824219 | 2.053999900817871 | 1.9780000448226929 | 0.13600000739097595 |
6.0 | 6.0 | 29.26580047607422 | 29.264400482177734 | 4.538700103759766 | 26.815200805664062 | 15.848199844360352 | -0.4790000021457672 | 3.8910000324249268 | 62.70000076293945 | 1.9359999895095825 | 1.9210000038146973 | 0.10599999874830246 |
6.5 | 6.5 | 29.155000686645508 | 29.153400421142578 | 4.749100208282471 | 28.269800186157227 | 16.971900939941406 | -0.3019999861717224 | 3.9779999256134033 | 48.29999923706055 | 1.8229999542236328 | 1.8539999723434448 | 0.08699999749660492 |
7.0 | 7.0 | 28.89739990234375 | 28.895700454711914 | 4.776299953460693 | 28.604000091552734 | 17.306100845336914 | -0.17299999296665192 | 3.9590001106262207 | 38.29999923706055 | 1.722000002861023 | 1.7970000505447388 | 0.08699999749660492 |
7.599999904632568 | 7.5 | 28.385400772094727 | 28.38360023498535 | 4.951900005340576 | 30.1028995513916 | 18.594900131225586 | 1.0429999828338623 | 3.690000057220459 | 30.799999237060547 | 1.628000020980835 | 1.7549999952316284 | 0.09399999678134918 |
8.100000381469727 | 8.0 | 27.19420051574707 | 27.192399978637695 | 5.333600044250488 | 33.55569839477539 | 21.570600509643555 | 2.7320001125335693 | 3.7790000438690186 | 25.200000762939453 | 1.5410000085830688 | 1.6929999589920044 | 0.10100000351667404 |
8.600000381469727 | 8.5 | 26.82270050048828 | 26.82080078125 | 5.4039998054504395 | 34.32659912109375 | 22.268999099731445 | -0.1720000058412552 | 4.203000068664551 | 21.0 | 1.4620000123977661 | 1.5789999961853027 | 0.07400000095367432 |
9.100000381469727 | 9.0 | 26.548099517822266 | 26.546100616455078 | 5.429100036621094 | 34.711700439453125 | 22.645999908447266 | 0.5260000228881836 | 4.25600004196167 | 17.799999237060547 | 1.3890000581741333 | 1.4709999561309814 | 0.06199999898672104 |
9.600000381469727 | 9.5 | 26.417299270629883 | 26.41510009765625 | 5.428999900817871 | 34.809200286865234 | 22.760700225830078 | -0.0010000000474974513 | 4.275000095367432 | 15.0 | 1.315000057220459 | 1.409999966621399 | 0.061000000685453415 |
10.100000381469727 | 10.0 | 26.311399459838867 | 26.309099197387695 | 5.426300048828125 | 34.86949920654297 | 22.839500427246094 | 0.0949999988079071 | 4.242000102996826 | 12.899999618530273 | 1.25 | 1.3969999551773071 | 0.06400000303983688 |
10.600000381469727 | 10.5 | 26.213300704956055 | 26.210899353027344 | 5.422599792480469 | 34.916900634765625 | 22.9060001373291 | -0.10599999874830246 | 4.1579999923706055 | 11.5 | 1.1990000009536743 | 1.4299999475479126 | 0.07199999690055847 |
11.100000381469727 | 11.0 | 26.157699584960938 | 26.15519905090332 | 5.418399810791016 | 34.92879867553711 | 22.93239974975586 | 0.06499999761581421 | 4.139999866485596 | 10.399999618530273 | 1.1549999713897705 | 1.465000033378601 | 0.0820000022649765 |
11.600000381469727 | 11.5 | 26.0585994720459 | 26.055999755859375 | 5.410200119018555 | 34.94459915161133 | 22.975299835205078 | 0.004000000189989805 | 4.107999801635742 | 9.399999618530273 | 1.1119999885559082 | 1.4839999675750732 | 0.08500000089406967 |
12.100000381469727 | 12.0 | 25.96660041809082 | 25.963899612426758 | 5.406099796295166 | 34.985198974609375 | 23.034500122070312 | 0.14000000059604645 | 4.026000022888184 | 8.350000381469727 | 1.0609999895095825 | 1.4570000171661377 | 0.09099999815225601 |
12.600000381469727 | 12.5 | 25.902099609375 | 25.89929962158203 | 5.409299850463867 | 35.057098388671875 | 23.10890007019043 | -0.07599999755620956 | 4.117000102996826 | 7.179999828338623 | 0.9950000047683716 | 1.4320000410079956 | 0.07800000160932541 |
13.100000381469727 | 13.0 | 25.881399154663086 | 25.87849998474121 | 5.42080020904541 | 35.15700149536133 | 23.19059944152832 | 0.32100000977516174 | 4.131999969482422 | 6.210000038146973 | 0.9319999814033508 | 1.4119999408721924 | 0.07999999821186066 |
13.600000381469727 | 13.5 | 25.85700035095215 | 25.854000091552734 | 5.426199913024902 | 35.2150993347168 | 23.24209976196289 | -0.06400000303983688 | 4.052000045776367 | 5.340000152587891 | 0.8669999837875366 | 1.4190000295639038 | 0.09700000286102295 |
14.100000381469727 | 14.0 | 25.821699142456055 | 25.818599700927734 | 5.424699783325195 | 35.231201171875 | 23.265199661254883 | -0.10000000149011612 | 4.047999858856201 | 4.710000038146973 | 0.8119999766349792 | 1.4429999589920044 | 0.10499999672174454 |
14.600000381469727 | 14.5 | 25.786399841308594 | 25.783199310302734 | 5.4232001304626465 | 35.24729919433594 | 23.288299560546875 | -0.17000000178813934 | 3.9549999237060547 | 4.210000038146973 | 0.7630000114440918 | 1.4789999723434448 | 0.11100000143051147 |
In total, there are 26 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.