Metocean: Historical collections
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Brought to you by NOAA NMFS SWFSC ERD |
Dataset Title: | "NEGOM CTD - n6l04s01.nc - 30.22N, 87.35W - 1999-00-20" |
Institution: | OCEAN.TAMU (Dataset ID: negom_n6l04s01) |
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 | 29.336299896240234 | 29.335800170898438 | 5.757900238037109 | 34.951900482177734 | 21.9153995513916 | 0.16200000047683716 | 3.9700000286102295 | -9.0 | -9.0 | 1.2890000343322754 | -9.0 |
2.5 | 2.5 | 29.335500717163086 | 29.33489990234375 | 5.757900238037109 | 34.95220184326172 | 21.915800094604492 | 0.17900000512599945 | 3.9730000495910645 | -9.0 | -9.0 | 1.3079999685287476 | -9.0 |
3.0 | 3.0 | 29.332799911499023 | 29.33209991455078 | 5.757599830627441 | 34.952301025390625 | 21.916900634765625 | 0.24199999868869781 | 3.9790000915527344 | -9.0 | -9.0 | 1.309000015258789 | -9.0 |
3.5 | 3.5 | 29.333200454711914 | 29.332300186157227 | 5.757699966430664 | 34.952598571777344 | 21.91699981689453 | 0.3499999940395355 | 3.9800000190734863 | -9.0 | -9.0 | 1.3250000476837158 | -9.0 |
4.0 | 4.0 | 29.3351993560791 | 29.334199905395508 | 5.757999897003174 | 34.95280075073242 | 21.916500091552734 | 0.24400000274181366 | 3.9790000915527344 | -9.0 | -9.0 | 1.3170000314712524 | -9.0 |
4.5 | 4.5 | 29.334400177001953 | 29.33329963684082 | 5.757999897003174 | 34.952999114990234 | 21.91699981689453 | 0.3109999895095825 | 3.9800000190734863 | -9.0 | -9.0 | 1.315999984741211 | -9.0 |
5.0 | 5.0 | 29.339399337768555 | 29.338199615478516 | 5.758500099182129 | 34.95309829711914 | 21.91550064086914 | 0.4230000078678131 | 3.9769999980926514 | -9.0 | -9.0 | 1.3229999542236328 | -9.0 |
5.5 | 5.5 | 29.337799072265625 | 29.33639907836914 | 5.758299827575684 | 34.95289993286133 | 21.915800094604492 | 0.4580000042915344 | 3.9820001125335693 | -9.0 | -9.0 | 1.309000015258789 | -9.0 |
6.0 | 6.0 | 29.340099334716797 | 29.338600158691406 | 5.758500099182129 | 34.95240020751953 | 21.91469955444336 | 0.3659999966621399 | 3.9790000915527344 | -9.0 | -9.0 | 1.3170000314712524 | -9.0 |
6.5 | 6.5 | 29.338600158691406 | 29.336999893188477 | 5.758399963378906 | 34.95249938964844 | 21.9153995513916 | 0.27799999713897705 | 3.9690001010894775 | -9.0 | -9.0 | 1.3109999895095825 | -9.0 |
7.0 | 7.0 | 29.23699951171875 | 29.235300064086914 | 5.748000144958496 | 34.95479965209961 | 21.9512996673584 | 0.43799999356269836 | 3.931999921798706 | -9.0 | -9.0 | 1.3140000104904175 | -9.0 |
7.599999904632568 | 7.5 | 28.985700607299805 | 28.98390007019043 | 5.725900173187256 | 34.986900329589844 | 22.059600830078125 | 0.5 | 3.9119999408721924 | -9.0 | -9.0 | 1.340000033378601 | -9.0 |
8.100000381469727 | 8.0 | 28.744199752807617 | 28.742300033569336 | 5.708399772644043 | 35.0432014465332 | 22.18239974975586 | 0.4300000071525574 | 3.8610000610351562 | -9.0 | -9.0 | 1.3899999856948853 | -9.0 |
8.600000381469727 | 8.5 | 28.667400360107422 | 28.665300369262695 | 5.703800201416016 | 35.06809997558594 | 22.226699829101562 | 0.2930000126361847 | 3.8550000190734863 | -9.0 | -9.0 | 1.4509999752044678 | -9.0 |
9.100000381469727 | 9.0 | 28.38599967956543 | 28.383800506591797 | 5.685800075531006 | 35.150901794433594 | 22.381999969482422 | 0.33399999141693115 | 3.8580000400543213 | -9.0 | -9.0 | 1.4500000476837158 | -9.0 |
9.600000381469727 | 9.5 | 28.251300811767578 | 28.249000549316406 | 5.677499771118164 | 35.19309997558594 | 22.458200454711914 | 0.4399999976158142 | 3.8399999141693115 | -9.0 | -9.0 | 1.465999960899353 | -9.0 |
10.100000381469727 | 10.0 | 27.793100357055664 | 27.790700912475586 | 5.656799793243408 | 35.39080047607422 | 22.756900787353516 | 0.40799999237060547 | 3.884000062942505 | -9.0 | -9.0 | 1.4809999465942383 | -9.0 |
10.600000381469727 | 10.5 | 27.50160026550293 | 27.499099731445312 | 5.638400077819824 | 35.481201171875 | 22.919599533081055 | 0.21299999952316284 | 3.9489998817443848 | -9.0 | -9.0 | 1.4910000562667847 | -9.0 |
11.100000381469727 | 11.0 | 27.337299346923828 | 27.334699630737305 | 5.628200054168701 | 35.53390121459961 | 23.012399673461914 | 0.328000009059906 | 3.9839999675750732 | -9.0 | -9.0 | 1.4880000352859497 | -9.0 |
11.600000381469727 | 11.5 | 27.29990005493164 | 27.297199249267578 | 5.626999855041504 | 35.55329895019531 | 23.039100646972656 | 0.3240000009536743 | 3.9839999675750732 | -9.0 | -9.0 | 1.5019999742507935 | -9.0 |
12.100000381469727 | 12.0 | 27.219900131225586 | 27.217100143432617 | 5.621200084686279 | 35.57279968261719 | 23.079599380493164 | 0.1899999976158142 | 3.9839999675750732 | -9.0 | -9.0 | 1.5 | -9.0 |
12.600000381469727 | 12.5 | 27.1481990814209 | 27.145299911499023 | 5.615099906921387 | 35.583900451660156 | 23.111099243164062 | 0.32899999618530273 | 3.984999895095825 | -9.0 | -9.0 | 1.5230000019073486 | -9.0 |
13.100000381469727 | 13.0 | 27.094499588012695 | 27.09149932861328 | 5.6107001304626465 | 35.59379959106445 | 23.135799407958984 | 0.2770000100135803 | 3.9860000610351562 | -9.0 | -9.0 | 1.5230000019073486 | -9.0 |
13.600000381469727 | 13.5 | 27.075000762939453 | 27.0718994140625 | 5.609099864959717 | 35.59700012207031 | 23.144500732421875 | 0.2549999952316284 | 3.9839999675750732 | -9.0 | -9.0 | 1.5360000133514404 | -9.0 |
14.100000381469727 | 14.0 | 27.03070068359375 | 27.02750015258789 | 5.605500221252441 | 35.604698181152344 | 23.164499282836914 | 0.27900001406669617 | 3.9830000400543213 | -9.0 | -9.0 | 1.5499999523162842 | -9.0 |
14.600000381469727 | 14.5 | 26.95210075378418 | 26.94879913330078 | 5.599100112915039 | 35.61920166015625 | 23.200599670410156 | 0.25600001215934753 | 4.011000156402588 | -9.0 | -9.0 | 1.5410000085830688 | -9.0 |
15.100000381469727 | 15.0 | 26.872299194335938 | 26.868799209594727 | 5.592100143432617 | 35.63019943237305 | 23.234399795532227 | 0.25999999046325684 | 3.986999988555908 | -9.0 | -9.0 | 1.5399999618530273 | -9.0 |
15.600000381469727 | 15.5 | 26.70400047302246 | 26.70039939880371 | 5.5782999992370605 | 35.660099029541016 | 23.310699462890625 | 0.22100000083446503 | 4.077000141143799 | -9.0 | -9.0 | 1.5069999694824219 | -9.0 |
16.100000381469727 | 16.0 | 26.587900161743164 | 26.584199905395508 | 5.56689977645874 | 35.667301177978516 | 23.35300064086914 | 0.1899999976158142 | 4.019000053405762 | -9.0 | -9.0 | 1.534000039100647 | -9.0 |
16.600000381469727 | 16.5 | 26.487499237060547 | 26.483699798583984 | 5.55620002746582 | 35.66790008544922 | 23.38520050048828 | 0.15399999916553497 | 3.8550000190734863 | -9.0 | -9.0 | 1.7580000162124634 | -9.0 |
17.100000381469727 | 17.0 | 26.416000366210938 | 26.412099838256836 | 5.548600196838379 | 35.667598724365234 | 23.40760040283203 | 0.15700000524520874 | 3.7690000534057617 | -9.0 | -9.0 | 1.8240000009536743 | -9.0 |
In total, there are 31 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.