Metocean: Historical collections
|
Brought to you by NOAA NMFS SWFSC ERD |
Dataset Title: | "LATEX CTD - d94h102.nc - 28.98N, 94.74W - 1994-05-02" |
Institution: | Texas A&M University, Department of Oceanography (Dataset ID: latex_d94h102) |
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 | 23.448699951171875 | 23.448200225830078 | 4.193999767303467 | 27.846500396728516 | 18.394500732421875 | 0.4790000021457672 | 3.7720000743865967 | 0.7099999785423279 | 0.1850000023841858 | 0.3140000104904175 | 0.15600000321865082 |
3.0 | 3.0 | 23.446699142456055 | 23.44610023498535 | 4.193900108337402 | 27.847000122070312 | 18.39550018310547 | 0.4519999921321869 | 3.7790000438690186 | 0.6200000047683716 | 0.125 | 0.31299999356269836 | 0.15700000524520874 |
3.5 | 3.5 | 23.440500259399414 | 23.439800262451172 | 4.19290018081665 | 27.8435001373291 | 18.39459991455078 | 0.46000000834465027 | 3.7880001068115234 | 0.550000011920929 | 0.0689999982714653 | 0.3409999907016754 | 0.15800000727176666 |
4.0 | 4.0 | 23.439699172973633 | 23.438899993896484 | 4.19290018081665 | 27.843399047851562 | 18.394800186157227 | 0.7300000190734863 | 3.7809998989105225 | 0.4699999988079071 | 0.0020000000949949026 | 0.3050000071525574 | 0.15800000727176666 |
4.5 | 4.5 | 23.438800811767578 | 23.43790054321289 | 4.192699909210205 | 27.84280014038086 | 18.39459991455078 | 0.7139999866485596 | 3.7899999618530273 | 0.4699999988079071 | 0.0 | 0.29499998688697815 | 0.1550000011920929 |
5.0 | 5.0 | 23.43939971923828 | 23.438400268554688 | 4.192800045013428 | 27.842899322509766 | 18.394500732421875 | 0.4480000138282776 | 3.7860000133514404 | 0.4699999988079071 | 0.0 | 0.2939999997615814 | 0.1550000011920929 |
5.5 | 5.5 | 23.44070053100586 | 23.439599990844727 | 4.192999839782715 | 27.8435001373291 | 18.394699096679688 | 0.4129999876022339 | 3.7869999408721924 | 0.4699999988079071 | 0.0 | 0.3330000042915344 | 0.1550000011920929 |
6.0 | 6.0 | 23.4414005279541 | 23.440200805664062 | 4.19320011138916 | 27.843900680541992 | 18.394800186157227 | 0.4560000002384186 | 3.7839999198913574 | 0.4699999988079071 | 0.0 | 0.3100000023841858 | 0.1589999943971634 |
6.5 | 6.5 | 23.439300537109375 | 23.437999725341797 | 4.192800045013428 | 27.842300415039062 | 18.39419937133789 | 0.48500001430511475 | 3.7829999923706055 | 0.4699999988079071 | 0.0 | 0.3100000023841858 | 0.15700000524520874 |
7.0 | 7.0 | 23.43869972229004 | 23.437299728393555 | 4.192699909210205 | 27.841899871826172 | 18.394100189208984 | 0.3610000014305115 | 3.796999931335449 | 0.4699999988079071 | 0.0 | 0.3070000112056732 | 0.15800000727176666 |
7.599999904632568 | 7.5 | 23.439199447631836 | 23.437700271606445 | 4.192800045013428 | 27.84239959716797 | 18.394399642944336 | 0.2919999957084656 | 3.796999931335449 | 0.4699999988079071 | 0.0 | 0.30799999833106995 | 0.15399999916553497 |
8.100000381469727 | 8.0 | 23.438499450683594 | 23.436800003051758 | 4.192800045013428 | 27.842199325561523 | 18.394500732421875 | 0.25999999046325684 | 3.796999931335449 | 0.4699999988079071 | 0.0 | 0.3140000104904175 | 0.14900000393390656 |
8.600000381469727 | 8.5 | 23.43950080871582 | 23.43779945373535 | 4.192599773406982 | 27.840099334716797 | 18.39259910583496 | 0.3919999897480011 | 3.7980000972747803 | 0.4699999988079071 | 0.0 | 0.3089999854564667 | 0.1550000011920929 |
9.100000381469727 | 9.0 | 23.438899993896484 | 23.43709945678711 | 4.192599773406982 | 27.840700149536133 | 18.393299102783203 | 0.5210000276565552 | 3.7980000972747803 | 0.4699999988079071 | 0.0 | 0.3019999861717224 | 0.15299999713897705 |
9.600000381469727 | 9.5 | 23.43899917602539 | 23.437000274658203 | 4.192699909210205 | 27.841299057006836 | 18.393699645996094 | 0.4490000009536743 | 3.796999931335449 | 0.4699999988079071 | 0.0 | 0.3070000112056732 | 0.1550000011920929 |
10.100000381469727 | 10.0 | 23.4375 | 23.43549919128418 | 4.192599773406982 | 27.841100692749023 | 18.393999099731445 | 0.6230000257492065 | 3.7960000038146973 | 0.4699999988079071 | 0.0 | 0.3160000145435333 | 0.15600000321865082 |
10.600000381469727 | 10.5 | 23.440200805664062 | 23.438100814819336 | 4.1940999031066895 | 27.85070037841797 | 18.40060043334961 | 0.7799999713897705 | 3.796999931335449 | 0.4699999988079071 | 0.0 | 0.3179999887943268 | 0.15399999916553497 |
11.100000381469727 | 11.0 | 23.449199676513672 | 23.4468994140625 | 4.201700210571289 | 27.900999069213867 | 18.43600082397461 | 0.531000018119812 | 3.802000045776367 | 0.4699999988079071 | 0.0 | 0.3199999928474426 | 0.1509999930858612 |
11.600000381469727 | 11.5 | 23.456499099731445 | 23.454200744628906 | 4.206399917602539 | 27.931100845336914 | 18.456600189208984 | 0.44699999690055847 | 3.7980000972747803 | 0.4699999988079071 | 0.0 | 0.3409999907016754 | 0.15399999916553497 |
12.100000381469727 | 12.0 | 23.460399627685547 | 23.45789909362793 | 4.214300155639648 | 27.986600875854492 | 18.497499465942383 | 0.1509999930858612 | 3.7880001068115234 | 0.4699999988079071 | 0.0 | 0.32899999618530273 | 0.16099999845027924 |
12.600000381469727 | 12.5 | 23.45840072631836 | 23.455900192260742 | 4.2382001876831055 | 28.164499282836914 | 18.632400512695312 | 0.3610000014305115 | 3.815000057220459 | 0.4699999988079071 | 0.0 | 0.3179999887943268 | 0.1509999930858612 |
13.100000381469727 | 13.0 | 23.450899124145508 | 23.448299407958984 | 4.258200168609619 | 28.31760025024414 | 18.750200271606445 | 0.47200000286102295 | 3.8529999256134033 | 0.4699999988079071 | 0.0 | 0.3310000002384186 | 0.1509999930858612 |
13.600000381469727 | 13.5 | 23.43600082397461 | 23.433300018310547 | 4.283299922943115 | 28.51300048828125 | 18.902000427246094 | 0.5460000038146973 | 3.8589999675750732 | 0.4699999988079071 | 0.0 | 0.33899998664855957 | 0.1550000011920929 |
14.100000381469727 | 14.0 | 23.425199508666992 | 23.422399520874023 | 4.30649995803833 | 28.6919002532959 | 19.040199279785156 | 0.6579999923706055 | 3.930999994277954 | 0.4699999988079071 | 0.0 | 0.3529999852180481 | 0.14000000059604645 |
14.600000381469727 | 14.5 | 23.406999588012695 | 23.40410041809082 | 4.3414998054504395 | 28.964000701904297 | 19.250900268554688 | 0.3709999918937683 | 3.9769999980926514 | 0.4699999988079071 | 0.0 | 0.38100001215934753 | 0.1340000033378601 |
15.100000381469727 | 15.0 | 23.39699935913086 | 23.393999099731445 | 4.35860013961792 | 29.09749984741211 | 19.35460090637207 | 0.41499999165534973 | 3.934000015258789 | 0.4699999988079071 | 0.0 | 0.382999986410141 | 0.12700000405311584 |
15.600000381469727 | 15.5 | 23.349000930786133 | 23.34589958190918 | 4.404699802398682 | 29.47279930114746 | 19.65180015563965 | 0.1509999930858612 | 3.7790000438690186 | 0.4699999988079071 | 0.0 | 0.37700000405311584 | 0.13899999856948853 |
In total, there are 27 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.