Metocean: Historical collections
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Brought to you by NOAA NMFS SWFSC ERD |
Dataset Title: | "LATEX CTD - d93f115.nc - 29.12N, 94.0W - 1993-08-01" |
Institution: | Texas A&M University, Department of Oceanography (Dataset ID: latex_d93f115) |
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 | 30.234899520874023 | 30.234500885009766 | 5.418000221252441 | 32.04309844970703 | 19.434200286865234 | 0.08799999952316284 | 4.353000164031982 | 567.0 | 3.0420000553131104 | 1.0839999914169312 | -9.0 |
2.0 | 2.0 | 30.10379981994629 | 30.103300094604492 | 5.407800197601318 | 32.06129837036133 | 19.492300033569336 | 0.4059999883174896 | 4.354000091552734 | 647.0 | 3.0989999771118164 | 1.0839999914169312 | -9.0 |
2.5 | 2.5 | 30.09670066833496 | 30.096099853515625 | 5.408599853515625 | 32.070899963378906 | 19.50200080871582 | 0.4580000042915344 | 4.3470001220703125 | 389.0 | 2.878000020980835 | 1.1069999933242798 | -9.0 |
3.0 | 3.0 | 30.100500106811523 | 30.099700927734375 | 5.411399841308594 | 32.08700180053711 | 19.512800216674805 | 0.4959999918937683 | 4.3429999351501465 | 243.0 | 2.6730000972747803 | 1.125 | -9.0 |
3.5 | 3.5 | 30.11280059814453 | 30.111900329589844 | 5.41540002822876 | 32.10540008544922 | 19.522499084472656 | 0.5 | 4.336999893188477 | 253.0 | 2.690999984741211 | 1.1480000019073486 | -9.0 |
4.0 | 4.0 | 30.127700805664062 | 30.126800537109375 | 5.419400215148926 | 32.12179946899414 | 19.529699325561523 | 0.46399998664855957 | 4.3379998207092285 | 206.0 | 2.6019999980926514 | 1.1510000228881836 | -9.0 |
4.5 | 4.5 | 30.15410041809082 | 30.15290069580078 | 5.425000190734863 | 32.141998291015625 | 19.535900115966797 | 0.46399998664855957 | 4.334000110626221 | 181.0 | 2.546999931335449 | 1.1549999713897705 | -9.0 |
5.0 | 5.0 | 30.161500930786133 | 30.16029930114746 | 5.426799774169922 | 32.14899826049805 | 19.53860092163086 | 0.46799999475479126 | 4.328999996185303 | 187.0 | 2.561000108718872 | 1.156000018119812 | -9.0 |
5.5 | 5.5 | 30.159000396728516 | 30.15760040283203 | 5.427199840545654 | 32.15299987792969 | 19.542499542236328 | 0.5149999856948853 | 4.327000141143799 | 166.0 | 2.507999897003174 | 1.184000015258789 | -9.0 |
6.0 | 6.0 | 30.158899307250977 | 30.157400131225586 | 5.428500175476074 | 32.16189956665039 | 19.549299240112305 | 0.531000018119812 | 4.320000171661377 | 160.0 | 2.490999937057495 | 1.2289999723434448 | -9.0 |
6.5 | 6.5 | 30.16790008544922 | 30.16629981994629 | 5.43149995803833 | 32.17559814453125 | 19.55660057067871 | 0.4620000123977661 | 4.331999778747559 | 154.0 | 2.4749999046325684 | 1.2330000400543213 | -9.0 |
7.0 | 7.0 | 30.175399780273438 | 30.1737003326416 | 5.434299945831299 | 32.18920135498047 | 19.564199447631836 | 0.4399999976158142 | 4.333000183105469 | 142.0 | 2.440000057220459 | 1.2710000276565552 | -9.0 |
7.599999904632568 | 7.5 | 30.18280029296875 | 30.18090057373047 | 5.437300205230713 | 32.204200744628906 | 19.572999954223633 | 0.5049999952316284 | 4.330999851226807 | 140.0 | 2.434000015258789 | 1.2619999647140503 | -9.0 |
8.100000381469727 | 8.0 | 30.17650032043457 | 30.17449951171875 | 5.438000202178955 | 32.21260070800781 | 19.58139991760254 | 0.5289999842643738 | 4.331999778747559 | 131.0 | 2.4049999713897705 | 1.2309999465942383 | -9.0 |
8.600000381469727 | 8.5 | 30.152299880981445 | 30.15019989013672 | 5.436600208282471 | 32.21910095214844 | 19.594600677490234 | 0.4880000054836273 | 4.335999965667725 | 130.0 | 2.4019999504089355 | 1.2350000143051147 | -9.0 |
9.100000381469727 | 9.0 | 30.128299713134766 | 30.126100540161133 | 5.4334001541137695 | 32.2140007019043 | 19.598899841308594 | 0.4560000002384186 | 4.3379998207092285 | 124.0 | 2.38100004196167 | 1.25600004196167 | -9.0 |
9.600000381469727 | 9.5 | 30.104799270629883 | 30.102399826049805 | 5.433300018310547 | 32.22819900512695 | 19.617599487304688 | 0.47999998927116394 | 4.3379998207092285 | 121.0 | 2.369999885559082 | 1.2719999551773071 | -9.0 |
10.100000381469727 | 10.0 | 30.103200912475586 | 30.10070037841797 | 5.440700054168701 | 32.27870178222656 | 19.655899047851562 | 0.4950000047683716 | 4.324999809265137 | 116.0 | 2.3529999256134033 | 1.2710000276565552 | -9.0 |
10.600000381469727 | 10.5 | 30.12689971923828 | 30.124300003051758 | 5.458399772644043 | 32.38100051879883 | 19.72450065612793 | 0.49900001287460327 | 4.339000225067139 | 110.0 | 2.3310000896453857 | 1.2990000247955322 | -9.0 |
11.100000381469727 | 11.0 | 30.089099884033203 | 30.08639907836914 | 5.4745001792907715 | 32.51350021362305 | 19.83650016784668 | 0.48899999260902405 | 4.34499979019165 | 109.0 | 2.3269999027252197 | 1.281999945640564 | -9.0 |
11.600000381469727 | 11.5 | 30.039499282836914 | 30.036699295043945 | 5.482600212097168 | 32.60020065307617 | 19.91830062866211 | 0.4729999899864197 | 4.355000019073486 | 105.0 | 2.311000108718872 | 1.3029999732971191 | -9.0 |
12.100000381469727 | 12.0 | 30.007999420166016 | 30.0049991607666 | 5.485899925231934 | 32.64360046386719 | 19.96150016784668 | 0.48899999260902405 | 4.355999946594238 | 103.0 | 2.302000045776367 | 1.3270000219345093 | -9.0 |
12.600000381469727 | 12.5 | 29.958200454711914 | 29.95509910583496 | 5.483699798583984 | 32.66239929199219 | 19.99250030517578 | 0.5 | 4.361999988555908 | 102.0 | 2.2950000762939453 | 1.3250000476837158 | -9.0 |
13.100000381469727 | 13.0 | 29.869400024414062 | 29.866199493408203 | 5.479800224304199 | 32.69599914550781 | 20.047700881958008 | 0.4819999933242798 | 4.373000144958496 | 99.0 | 2.2839999198913574 | 1.312999963760376 | -9.0 |
13.600000381469727 | 13.5 | 29.825000762939453 | 29.821699142456055 | 5.483500003814697 | 32.75040054321289 | 20.103500366210938 | 0.4729999899864197 | 4.382999897003174 | 100.0 | 2.2890000343322754 | 1.2910000085830688 | -9.0 |
14.100000381469727 | 14.0 | 29.778799057006836 | 29.775400161743164 | 5.482800006866455 | 32.77730178833008 | 20.139299392700195 | 0.5149999856948853 | 4.388999938964844 | 96.80000305175781 | 2.2739999294281006 | 1.2929999828338623 | -9.0 |
14.600000381469727 | 14.5 | 29.519500732421875 | 29.516000747680664 | 5.47130012512207 | 32.875999450683594 | 20.300399780273438 | 0.4050000011920929 | 4.389999866485596 | 96.0999984741211 | 2.2709999084472656 | 1.3359999656677246 | -9.0 |
15.100000381469727 | 15.0 | 28.961599349975586 | 28.95800018310547 | 5.454699993133545 | 33.14690017700195 | 20.689699172973633 | 0.2800000011920929 | 4.341000080108643 | 94.0999984741211 | 2.26200008392334 | 1.406999945640564 | -9.0 |
15.600000381469727 | 15.5 | 28.653600692749023 | 28.649900436401367 | 5.460100173950195 | 33.39870071411133 | 20.980499267578125 | 0.3109999895095825 | 4.23199987411499 | 92.4000015258789 | 2.253999948501587 | 1.6349999904632568 | -9.0 |
In total, there are 29 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.