Metocean: Historical collections
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Brought to you by NOAA NMFS SWFSC ERD |
Dataset Title: | "LATEX CTD - d94h077.nc - 28.97N, 94.0W - 1994-04-30" |
Institution: | Texas A&M University, Department of Oceanography (Dataset ID: latex_d94h077) |
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 |
3.0 | 3.0 | 24.276500701904297 | 24.27589988708496 | 4.343599796295166 | 28.42329978942871 | 18.59309959411621 | 0.38199999928474426 | 4.3480000495910645 | 291.0 | 2.7950000762939453 | 0.4059999883174896 | 0.035999998450279236 |
3.5 | 3.5 | 24.280799865722656 | 24.280099868774414 | 4.373899936676025 | 28.641199111938477 | 18.756099700927734 | 0.3869999945163727 | 4.3460001945495605 | 249.0 | 2.7279999256134033 | 0.42399999499320984 | 0.039000000804662704 |
4.0 | 4.0 | 24.260299682617188 | 24.25950050354004 | 4.412399768829346 | 28.93600082397461 | 18.984500885009766 | 0.3449999988079071 | 4.3429999351501465 | 220.0 | 2.674999952316284 | 0.46799999475479126 | 0.03799999877810478 |
4.5 | 4.5 | 24.07080078125 | 24.069900512695312 | 4.477099895477295 | 29.534000396728516 | 19.4906005859375 | 0.3400000035762787 | 4.340000152587891 | 192.0 | 2.615000009536743 | 0.48500001430511475 | 0.03099999949336052 |
5.0 | 5.0 | 23.912099838256836 | 23.911100387573242 | 4.548600196838379 | 30.167600631713867 | 20.014799118041992 | 0.3190000057220459 | 4.3420000076293945 | 176.0 | 2.5759999752044678 | 0.5519999861717224 | 0.02800000086426735 |
5.5 | 5.5 | 23.701200485229492 | 23.70009994506836 | 4.602499961853027 | 30.712299346923828 | 20.487199783325195 | 0.34599998593330383 | 4.295000076293945 | 150.0 | 2.506999969482422 | 0.5329999923706055 | 0.029999999329447746 |
6.0 | 6.0 | 23.462299346923828 | 23.46109962463379 | 4.664899826049805 | 31.347000122070312 | 21.035499572753906 | 0.5040000081062317 | 4.3480000495910645 | 135.0 | 2.4609999656677246 | 0.5680000185966492 | 0.028999999165534973 |
6.5 | 6.5 | 23.223499298095703 | 23.222200393676758 | 4.727399826049805 | 31.98940086364746 | 21.58989906311035 | 0.37700000405311584 | 4.361000061035156 | 123.0 | 2.4200000762939453 | 0.6240000128746033 | 0.032999999821186066 |
7.0 | 7.0 | 23.13610076904297 | 23.134700775146484 | 4.726200103759766 | 32.0432014465332 | 21.65570068359375 | 0.6050000190734863 | 4.372000217437744 | 110.0 | 2.374000072479248 | 0.6759999990463257 | 0.029999999329447746 |
7.599999904632568 | 7.5 | 23.051300048828125 | 23.049800872802734 | 4.726600170135498 | 32.10770034790039 | 21.728599548339844 | 0.8410000205039978 | 4.361999988555908 | 96.69999694824219 | 2.316999912261963 | 0.6629999876022339 | 0.029999999329447746 |
8.100000381469727 | 8.0 | 23.02680015563965 | 23.02519989013672 | 4.742099761962891 | 32.24380111694336 | 21.838699340820312 | 0.8840000033378601 | 4.361000061035156 | 87.19999694824219 | 2.2720000743865967 | 0.6650000214576721 | 0.03200000151991844 |
8.600000381469727 | 8.5 | 22.55699920654297 | 22.555299758911133 | 4.724100112915039 | 32.45199966430664 | 22.129199981689453 | 0.6940000057220459 | 4.326000213623047 | 79.5 | 2.2320001125335693 | 0.6940000057220459 | 0.03500000014901161 |
9.100000381469727 | 9.0 | 22.129100799560547 | 22.127300262451172 | 4.695199966430664 | 32.54800033569336 | 22.321500778198242 | 0.6940000057220459 | 4.205999851226807 | 74.5 | 2.2039999961853027 | 0.7149999737739563 | 0.03799999877810478 |
9.600000381469727 | 9.5 | 21.999300003051758 | 21.997400283813477 | 4.679800033569336 | 32.525699615478516 | 22.340599060058594 | 0.9480000138282776 | 4.105999946594238 | 69.0999984741211 | 2.1710000038146973 | 0.699999988079071 | 0.061000000685453415 |
10.100000381469727 | 10.0 | 21.895700454711914 | 21.893699645996094 | 4.667600154876709 | 32.507598876953125 | 22.355499267578125 | 0.843999981880188 | 4.040999889373779 | 62.599998474121094 | 2.128000020980835 | 0.6959999799728394 | 0.0949999988079071 |
10.600000381469727 | 10.5 | 21.73069953918457 | 21.728700637817383 | 4.652599811553955 | 32.51470184326172 | 22.406299591064453 | 0.5059999823570251 | 3.9149999618530273 | 56.900001525878906 | 2.0869998931884766 | 0.6740000247955322 | 0.09099999815225601 |
11.100000381469727 | 11.0 | 21.19339942932129 | 21.191299438476562 | 4.6178998947143555 | 32.64870071411133 | 22.654300689697266 | 0.546999990940094 | 3.4059998989105225 | 52.599998474121094 | 2.052999973297119 | 0.6370000243186951 | 0.14399999380111694 |
11.600000381469727 | 11.5 | 21.145099639892578 | 21.142900466918945 | 4.656099796295166 | 32.98780059814453 | 22.924999237060547 | 0.7170000076293945 | 3.562000036239624 | 48.5 | 2.0169999599456787 | 0.6290000081062317 | 0.2460000067949295 |
12.100000381469727 | 12.0 | 21.1299991607666 | 21.127700805664062 | 4.715199947357178 | 33.46889877319336 | 23.295000076293945 | 0.7400000095367432 | 3.8259999752044678 | 44.900001525878906 | 1.9839999675750732 | 0.6320000290870667 | 0.21199999749660492 |
12.600000381469727 | 12.5 | 21.12689971923828 | 21.124500274658203 | 4.730599880218506 | 33.594200134277344 | 23.39109992980957 | 0.5690000057220459 | 3.694999933242798 | 40.599998474121094 | 1.940000057220459 | 0.652999997138977 | 0.16500000655651093 |
13.100000381469727 | 13.0 | 20.95989990234375 | 20.957399368286133 | 4.752299785614014 | 33.89899826049805 | 23.667999267578125 | 0.49799999594688416 | 3.384000062942505 | 34.5 | 1.86899995803833 | 0.7919999957084656 | 0.20900000631809235 |
13.600000381469727 | 13.5 | 20.79290008544922 | 20.790300369262695 | 4.77400016784668 | 34.20610046386719 | 23.94700050354004 | 0.765999972820282 | 3.431999921798706 | 31.899999618530273 | 1.8350000381469727 | 0.8140000104904175 | 0.23899999260902405 |
14.100000381469727 | 14.0 | 20.78219985961914 | 20.779499053955078 | 4.773200035095215 | 34.20759963989258 | 23.950899124145508 | 0.7929999828338623 | 3.559000015258789 | 28.399999618530273 | 1.784999966621399 | 0.8059999942779541 | 0.23600000143051147 |
14.600000381469727 | 14.5 | 20.75670051574707 | 20.7539005279541 | 4.771999835968018 | 34.21889877319336 | 23.966400146484375 | 0.5979999899864197 | 3.802000045776367 | 24.399999618530273 | 1.718999981880188 | 0.7820000052452087 | 0.2160000056028366 |
15.100000381469727 | 15.0 | 20.542600631713867 | 20.5398006439209 | 4.771999835968018 | 34.391300201416016 | 24.15489959716797 | 0.36899998784065247 | 3.9830000400543213 | 18.399999618530273 | 1.597000002861023 | 0.6850000023841858 | 0.1889999955892563 |
15.600000381469727 | 15.5 | 20.207300186157227 | 20.20439910888672 | 4.778500080108643 | 34.71770095825195 | 24.492900848388672 | 0.6190000176429749 | 3.9519999027252197 | 14.699999809265137 | 1.4980000257492065 | 0.7089999914169312 | 0.17800000309944153 |
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.