Metocean: Historical collections
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Dataset Title: | "LATEX CTD - d93d072.nc - 28.88N, 90.51W - 1993-02-09" |
Institution: | Texas A&M University, Department of Oceanography (Dataset ID: latex_d93d072) |
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 |
1.5 | 1.5 | 15.851400375366211 | 15.851200103759766 | 3.4428999423980713 | 26.804100036621094 | 19.486900329589844 | 0.15700000524520874 | 2.0139999389648438 | 955.0 | 4.010000228881836 | 3.558000087738037 | -9.0 |
2.0 | 2.0 | 15.871600151062012 | 15.871299743652344 | 3.4535000324249268 | 26.881500244140625 | 19.541900634765625 | 0.4959999918937683 | 2.1419999599456787 | 685.0 | 3.865999937057495 | 3.9260001182556152 | -9.0 |
2.5 | 2.5 | 15.890700340270996 | 15.890299797058105 | 3.4618000984191895 | 26.939899444580078 | 19.582599639892578 | 0.4959999918937683 | 2.2100000381469727 | 474.0 | 3.7060000896453857 | 3.9489998817443848 | -9.0 |
3.0 | 3.0 | 15.889800071716309 | 15.889399528503418 | 3.470599889755249 | 27.016399383544922 | 19.641399383544922 | 0.4169999957084656 | 2.2090001106262207 | 336.0 | 3.555999994277954 | 4.004000186920166 | -9.0 |
3.5 | 3.5 | 15.875200271606445 | 15.874699592590332 | 3.481100082397461 | 27.116300582885742 | 19.721099853515625 | 0.3799999952316284 | 2.312000036239624 | 237.0 | 3.4049999713897705 | 4.189000129699707 | -9.0 |
4.0 | 4.0 | 15.860699653625488 | 15.860099792480469 | 3.491499900817871 | 27.21619987487793 | 19.800800323486328 | 0.4690000116825104 | 2.430000066757202 | 166.0 | 3.250999927520752 | 4.321000099182129 | -9.0 |
4.5 | 4.5 | 15.843899726867676 | 15.843199729919434 | 3.4974000453948975 | 27.278799057006836 | 19.852500915527344 | 0.5059999823570251 | 2.4579999446868896 | 123.0 | 3.11899995803833 | 4.251999855041504 | -9.0 |
5.0 | 5.0 | 15.839900016784668 | 15.839200019836426 | 3.4976000785827637 | 27.282800674438477 | 19.856399536132812 | 0.4580000042915344 | 2.556999921798706 | 87.9000015258789 | 2.9739999771118164 | 4.110000133514404 | -9.0 |
5.5 | 5.5 | 15.88860034942627 | 15.887800216674805 | 3.510499954223633 | 27.360200881958008 | 19.90530014038086 | 0.367000013589859 | 2.5859999656677246 | 64.9000015258789 | 2.8420000076293945 | 3.9790000915527344 | -9.0 |
6.0 | 6.0 | 15.937399864196777 | 15.93649959564209 | 3.5232999324798584 | 27.437400817871094 | 19.954099655151367 | 0.44699999690055847 | 2.5950000286102295 | 47.900001525878906 | 2.7100000381469727 | 3.8889999389648438 | -9.0 |
6.5 | 6.5 | 15.91819953918457 | 15.917200088500977 | 3.5253000259399414 | 27.46769905090332 | 19.98150062561035 | 0.515999972820282 | 2.6040000915527344 | 36.20000076293945 | 2.5889999866485596 | 3.9619998931884766 | -9.0 |
7.0 | 7.0 | 15.89900016784668 | 15.89799976348877 | 3.5272998809814453 | 27.49810028076172 | 20.008899688720703 | 0.4880000054836273 | 2.7829999923706055 | 26.899999618530273 | 2.4600000381469727 | 3.7260000705718994 | -9.0 |
7.599999904632568 | 7.5 | 15.915499687194824 | 15.914400100708008 | 3.534600019454956 | 27.549699783325195 | 20.04490089416504 | 0.3930000066757202 | 2.940000057220459 | 19.700000762939453 | 2.3239998817443848 | 3.068000078201294 | -9.0 |
8.100000381469727 | 8.0 | 16.126300811767578 | 16.125099182128906 | 3.5689001083374023 | 27.699100494384766 | 20.11400032043457 | 0.3919999897480011 | 3.128000020980835 | 15.0 | 2.2070000171661377 | 2.436000108718872 | -9.0 |
8.600000381469727 | 8.5 | 16.59510040283203 | 16.593799591064453 | 3.6698999404907227 | 28.236900329589844 | 20.42300033569336 | 0.4880000054836273 | 3.763000011444092 | 11.800000190734863 | 2.1029999256134033 | 1.9550000429153442 | -9.0 |
9.100000381469727 | 9.0 | 17.063899993896484 | 17.0625 | 3.770900011062622 | 28.76409912109375 | 20.721099853515625 | 0.5379999876022339 | 4.060999870300293 | 9.329999923706055 | 2.0 | 1.1729999780654907 | -9.0 |
9.600000381469727 | 9.5 | 17.08099937438965 | 17.079500198364258 | 3.783900022506714 | 28.8617000579834 | 20.791900634765625 | 0.4779999852180481 | 4.126999855041504 | 7.289999961853027 | 1.8930000066757202 | 0.746999979019165 | -9.0 |
10.100000381469727 | 10.0 | 17.098100662231445 | 17.096500396728516 | 3.7969000339508057 | 28.959299087524414 | 20.862499237060547 | 0.35199999809265137 | 4.11899995803833 | 5.829999923706055 | 1.7960000038146973 | 0.5600000023841858 | -9.0 |
10.600000381469727 | 10.5 | 17.130699157714844 | 17.128999710083008 | 3.821199893951416 | 29.141700744628906 | 20.994800567626953 | 0.33799999952316284 | 4.131999969482422 | 4.829999923706055 | 1.7139999866485596 | 0.49300000071525574 | -9.0 |
11.100000381469727 | 11.0 | 17.16320037841797 | 17.161399841308594 | 3.8454999923706055 | 29.323999404907227 | 21.12689971923828 | 0.47200000286102295 | 4.119999885559082 | 4.260000228881836 | 1.659000039100647 | 0.4830000102519989 | -9.0 |
11.600000381469727 | 11.5 | 17.329599380493164 | 17.327699661254883 | 3.897700071334839 | 29.64539909362793 | 21.334400177001953 | 0.46399998664855957 | 4.243000030517578 | 3.7100000381469727 | 1.600000023841858 | 0.4269999861717224 | -9.0 |
12.100000381469727 | 12.0 | 17.595300674438477 | 17.593399047851562 | 3.9642999172210693 | 30.011899948120117 | 21.552900314331055 | 0.27000001072883606 | 4.2829999923706055 | 3.109999895095825 | 1.5230000019073486 | 0.35899999737739563 | -9.0 |
12.600000381469727 | 12.5 | 17.861099243164062 | 17.858999252319336 | 4.030799865722656 | 30.374500274658203 | 21.76729965209961 | 0.2150000035762787 | 4.308000087738037 | 2.759999990463257 | 1.4709999561309814 | 0.2639999985694885 | -9.0 |
13.100000381469727 | 13.0 | 18.277999877929688 | 18.275800704956055 | 4.148200035095215 | 31.04450035095215 | 22.17930030822754 | 0.328000009059906 | 4.302000045776367 | 2.4000000953674316 | 1.409999966621399 | 0.21199999749660492 | -9.0 |
13.600000381469727 | 13.5 | 18.436100006103516 | 18.433799743652344 | 4.204100131988525 | 31.389999389648438 | 22.404800415039062 | 0.21799999475479126 | 4.296999931335449 | 2.059999942779541 | 1.343000054359436 | 0.20399999618530273 | -9.0 |
14.100000381469727 | 14.0 | 18.704500198364258 | 18.70210075378418 | 4.271200180053711 | 31.742300033569336 | 22.607799530029297 | 0.10199999809265137 | 4.254000186920166 | 1.840000033378601 | 1.2949999570846558 | 0.1899999976158142 | -9.0 |
14.600000381469727 | 14.5 | 19.120899200439453 | 19.11829948425293 | 4.411799907684326 | 32.58340072631836 | 23.14590072631836 | 0.2460000067949295 | 4.210000038146973 | 1.5800000429153442 | 1.2300000190734863 | 0.19200000166893005 | -9.0 |
15.100000381469727 | 15.0 | 19.53730010986328 | 19.53459930419922 | 4.552499771118164 | 33.412200927734375 | 23.672199249267578 | 0.09399999678134918 | 4.015999794006348 | 1.3700000047683716 | 1.1670000553131104 | 0.2029999941587448 | -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.