Metocean: Historical collections
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Brought to you by NOAA NMFS SWFSC ERD |
Dataset Title: | "LATEX CTD - d94h065.nc - 29.07N, 93.0W - 1994-04-30" |
Institution: | Texas A&M University, Department of Oceanography (Dataset ID: latex_d94h065) |
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 | 23.126100540161133 | 23.125499725341797 | 5.138299942016602 | 35.20370101928711 | 24.05340003967285 | 0.6359999775886536 | 4.230999946594238 | 0.8700000047683716 | 0.2720000147819519 | 0.5239999890327454 | 0.03700000047683716 |
3.5 | 3.5 | 23.126399993896484 | 23.125699996948242 | 5.138400077819824 | 35.204200744628906 | 24.053699493408203 | 0.671999990940094 | 4.236999988555908 | 0.7200000286102295 | 0.18799999356269836 | 0.5220000147819519 | 0.035999998450279236 |
4.0 | 4.0 | 23.12649917602539 | 23.125699996948242 | 5.138400077819824 | 35.20370101928711 | 24.05340003967285 | 0.4050000011920929 | 4.23799991607666 | 0.6800000071525574 | 0.16599999368190765 | 0.5239999890327454 | 0.035999998450279236 |
4.5 | 4.5 | 23.12689971923828 | 23.125999450683594 | 5.138400077819824 | 35.20320129394531 | 24.052900314331055 | 0.45100000500679016 | 4.23799991607666 | 0.5400000214576721 | 0.05999999865889549 | 0.5289999842643738 | 0.03700000047683716 |
5.0 | 5.0 | 23.126800537109375 | 23.12579917907715 | 5.138400077819824 | 35.202999114990234 | 24.052900314331055 | 0.6830000281333923 | 4.238999843597412 | 0.47999998927116394 | 0.014000000432133675 | 0.5479999780654907 | 0.03500000014901161 |
5.5 | 5.5 | 23.126699447631836 | 23.125600814819336 | 5.138400077819824 | 35.20280075073242 | 24.05270004272461 | 0.7480000257492065 | 4.241000175476074 | 0.4699999988079071 | 0.0020000000949949026 | 0.546999990940094 | 0.035999998450279236 |
6.0 | 6.0 | 23.126699447631836 | 23.12540054321289 | 5.138500213623047 | 35.203800201416016 | 24.053499221801758 | 0.671999990940094 | 4.236000061035156 | 0.4699999988079071 | 0.0 | 0.5350000262260437 | 0.03500000014901161 |
6.5 | 6.5 | 23.124799728393555 | 23.12350082397461 | 5.138899803161621 | 35.207801818847656 | 24.057199478149414 | 0.4909999966621399 | 4.235000133514404 | 0.4699999988079071 | 0.0 | 0.546999990940094 | 0.03500000014901161 |
7.0 | 7.0 | 23.119199752807617 | 23.117700576782227 | 5.139599800109863 | 35.21739959716797 | 24.066099166870117 | 0.8859999775886536 | 4.230999946594238 | 0.4699999988079071 | 0.0 | 0.5630000233650208 | 0.03500000014901161 |
7.599999904632568 | 7.5 | 23.114099502563477 | 23.112600326538086 | 5.140100002288818 | 35.225799560546875 | 24.07390022277832 | 0.9639999866485596 | 4.223999977111816 | 0.4699999988079071 | 0.0 | 0.5600000023841858 | 0.05400000140070915 |
8.100000381469727 | 8.0 | 23.111299514770508 | 23.109600067138672 | 5.140699863433838 | 35.232398986816406 | 24.07979965209961 | 0.8889999985694885 | 4.2179999351501465 | 0.4699999988079071 | 0.0 | 0.5659999847412109 | 0.04800000041723251 |
8.600000381469727 | 8.5 | 23.104700088500977 | 23.10300064086914 | 5.14109992980957 | 35.24020004272461 | 24.087600708007812 | 0.597000002861023 | 4.202000141143799 | 0.4699999988079071 | 0.0 | 0.5849999785423279 | 0.039000000804662704 |
9.100000381469727 | 9.0 | 23.06439971923828 | 23.0625 | 5.142399787902832 | 35.282798767089844 | 24.13170051574707 | 0.8080000281333923 | 4.193999767303467 | 0.4699999988079071 | 0.0 | 0.6299999952316284 | 0.03700000047683716 |
9.600000381469727 | 9.5 | 23.010799407958984 | 23.008800506591797 | 5.140699863433838 | 35.31230163574219 | 24.16950035095215 | 0.9380000233650208 | 4.1570000648498535 | 0.4699999988079071 | 0.0 | 0.6330000162124634 | 0.03700000047683716 |
10.100000381469727 | 10.0 | 22.9060001373291 | 22.903900146484375 | 5.134399890899658 | 35.347900390625 | 24.2268009185791 | 0.8920000195503235 | 4.077000141143799 | 0.4699999988079071 | 0.0 | 0.7089999914169312 | 0.04500000178813934 |
10.600000381469727 | 10.5 | 22.87849998474121 | 22.876300811767578 | 5.135900020599365 | 35.381500244140625 | 24.26020050048828 | 0.6330000162124634 | 4.066999912261963 | 0.4699999988079071 | 0.0 | 1.246999979019165 | 0.057999998331069946 |
11.100000381469727 | 11.0 | 22.83530044555664 | 22.833099365234375 | 5.133299827575684 | 35.39609909057617 | 24.283700942993164 | 0.5519999861717224 | 4.084000110626221 | 0.4699999988079071 | 0.0 | 1.031999945640564 | 0.041999999433755875 |
11.600000381469727 | 11.5 | 22.78380012512207 | 22.781400680541992 | 5.127299785614014 | 35.39139938354492 | 24.295000076293945 | 0.8629999756813049 | 4.085000038146973 | 0.4699999988079071 | 0.0 | 1.0119999647140503 | 0.04899999871850014 |
12.100000381469727 | 12.0 | 22.695199966430664 | 22.692800521850586 | 5.11460018157959 | 35.363399505615234 | 24.2992000579834 | 0.9309999942779541 | 4.001999855041504 | 0.4699999988079071 | 0.0 | 1.0240000486373901 | 0.054999999701976776 |
12.600000381469727 | 12.5 | 22.503700256347656 | 22.50119972229004 | 5.09060001373291 | 35.331600189208984 | 24.329700469970703 | 0.8090000152587891 | 3.984999895095825 | 0.4699999988079071 | 0.0 | 1.0759999752044678 | 0.05900000035762787 |
13.100000381469727 | 13.0 | 22.37070083618164 | 22.368099212646484 | 5.087399959564209 | 35.41490173339844 | 24.430700302124023 | 0.5550000071525574 | 4.017000198364258 | 0.4699999988079071 | 0.0 | 1.2359999418258667 | 0.06800000369548798 |
13.600000381469727 | 13.5 | 22.25779914855957 | 22.25510025024414 | 5.089600086212158 | 35.52360153198242 | 24.545299530029297 | 0.800000011920929 | 4.122000217437744 | 0.4699999988079071 | 0.0 | 1.25600004196167 | 0.054999999701976776 |
14.100000381469727 | 14.0 | 22.260000228881836 | 22.257200241088867 | 5.1072001457214355 | 35.660499572753906 | 24.648700714111328 | 0.7820000052452087 | 4.169000148773193 | 0.4699999988079071 | 0.0 | 1.1690000295639038 | 0.06599999964237213 |
14.600000381469727 | 14.5 | 22.29170036315918 | 22.288799285888672 | 5.114099979400635 | 35.688201904296875 | 24.660900115966797 | 0.5770000219345093 | 4.190000057220459 | 0.4699999988079071 | 0.0 | 1.0670000314712524 | 0.05700000002980232 |
15.100000381469727 | 15.0 | 22.271400451660156 | 22.268400192260742 | 5.114299774169922 | 35.70650100708008 | 24.680500030517578 | 0.3179999887943268 | 4.184999942779541 | 0.4699999988079071 | 0.0 | 0.9649999737739563 | 0.05900000035762787 |
15.600000381469727 | 15.5 | 22.222900390625 | 22.21980094909668 | 5.114200115203857 | 35.74549865722656 | 24.723899841308594 | 0.46000000834465027 | 4.160999774932861 | 0.4699999988079071 | 0.0 | 1.027999997138977 | 0.05000000074505806 |
16.100000381469727 | 16.0 | 22.097400665283203 | 22.094200134277344 | 5.101500034332275 | 35.7484016418457 | 24.761600494384766 | 0.6669999957084656 | 4.129000186920166 | 0.4699999988079071 | 0.0 | 1.1799999475479126 | 0.04899999871850014 |
16.600000381469727 | 16.5 | 21.994800567626953 | 21.991500854492188 | 5.091700077056885 | 35.75600051879883 | 24.796300888061523 | 0.6909999847412109 | 4.111999988555908 | 0.4699999988079071 | 0.0 | 1.312000036239624 | 0.050999999046325684 |
17.100000381469727 | 17.0 | 21.95560073852539 | 21.952199935913086 | 5.087800025939941 | 35.756900787353516 | 24.808000564575195 | 0.42899999022483826 | 4.089000225067139 | 0.4699999988079071 | 0.0 | 1.5069999694824219 | 0.054999999701976776 |
17.600000381469727 | 17.5 | 21.835599899291992 | 21.83209991455078 | 5.074900150299072 | 35.75410079956055 | 24.839500427246094 | 0.20399999618530273 | 4.060999870300293 | 0.4699999988079071 | 0.0 | 1.805999994277954 | 0.054999999701976776 |
18.100000381469727 | 18.0 | 21.837600708007812 | 21.833999633789062 | 5.0746002197265625 | 35.750301361083984 | 24.83609962463379 | 0.34700000286102295 | 4.039000034332275 | 0.4699999988079071 | 0.0 | 1.7619999647140503 | 0.06400000303983688 |
18.600000381469727 | 18.5 | 21.78190040588379 | 21.778200149536133 | 5.066999912261963 | 35.735801696777344 | 24.840599060058594 | 0.33799999952316284 | 4.0 | 0.4699999988079071 | 0.0 | 1.7300000190734863 | 0.09000000357627869 |
19.100000381469727 | 19.0 | 21.50670051574707 | 21.503000259399414 | 5.030300140380859 | 35.67179870605469 | 24.868499755859375 | 0.29899999499320984 | 3.8489999771118164 | 0.4699999988079071 | 0.0 | 1.7719999551773071 | 0.06400000303983688 |
19.600000381469727 | 19.5 | 21.31329917907715 | 21.309499740600586 | 5.007699966430664 | 35.651798248291016 | 24.90679931640625 | 0.25600001215934753 | 3.734999895095825 | 0.4699999988079071 | 0.0 | 1.6970000267028809 | 0.09600000083446503 |
20.100000381469727 | 20.0 | 21.287099838256836 | 21.283199310302734 | 5.006400108337402 | 35.66299819946289 | 24.92259979248047 | 0.22200000286102295 | 3.7260000705718994 | 0.4699999988079071 | 0.0 | 1.815000057220459 | 0.13300000131130219 |
In total, there are 35 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.