Metocean: Historical collections
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Dataset Title: | "LATEX CTD - d93g204.nc - 27.26N, 97.27W - 1993-11-19" |
Institution: | Texas A&M University, Department of Oceanography (Dataset ID: latex_d93g204) |
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 | 18.80109977722168 | 18.800800323486328 | 3.880000114440918 | 28.4591007232666 | 20.079500198364258 | -0.15199999511241913 | 3.878999948501587 | 0.5099999904632568 | 0.0 | 1.8029999732971191 | -9.0 |
2.0 | 2.0 | 18.797300338745117 | 18.797000885009766 | 3.8796000480651855 | 28.45789909362793 | 20.079500198364258 | 0.2160000056028366 | 3.8970000743865967 | 0.5099999904632568 | 0.0 | 1.7970000505447388 | -9.0 |
2.5 | 2.5 | 18.792299270629883 | 18.791900634765625 | 3.879199981689453 | 28.457799911499023 | 20.080699920654297 | 0.421999990940094 | 3.9019999504089355 | 0.5099999904632568 | 0.0 | 1.805999994277954 | -9.0 |
3.0 | 3.0 | 18.79129981994629 | 18.790800094604492 | 3.8791000843048096 | 28.457799911499023 | 20.080900192260742 | 0.6240000128746033 | 3.9089999198913574 | 0.5099999904632568 | 0.0 | 1.819000005722046 | -9.0 |
3.5 | 3.5 | 18.791000366210938 | 18.7903995513916 | 3.8791000843048096 | 28.457799911499023 | 20.08099937438965 | 0.6899999976158142 | 3.9110000133514404 | 0.5099999904632568 | 0.0 | 1.8179999589920044 | -9.0 |
4.0 | 4.0 | 18.790300369262695 | 18.789600372314453 | 3.8791000843048096 | 28.457700729370117 | 20.081199645996094 | 0.5329999923706055 | 3.9130001068115234 | 0.5099999904632568 | 0.0 | 1.8960000276565552 | -9.0 |
4.5 | 4.5 | 18.79199981689453 | 18.79129981994629 | 3.879199981689453 | 28.457799911499023 | 20.080900192260742 | 0.32100000977516174 | 3.9110000133514404 | 0.5099999904632568 | 0.0 | 1.8739999532699585 | -9.0 |
5.0 | 5.0 | 18.794599533081055 | 18.793699264526367 | 3.879499912261963 | 28.458200454711914 | 20.08060073852539 | 0.6179999709129333 | 3.9149999618530273 | 0.5099999904632568 | 0.0 | 1.8029999732971191 | -9.0 |
5.5 | 5.5 | 18.797100067138672 | 18.796199798583984 | 3.879699945449829 | 28.45800018310547 | 20.07979965209961 | 0.7710000276565552 | 3.9130001068115234 | 0.5099999904632568 | 0.0 | 1.7990000247955322 | -9.0 |
6.0 | 6.0 | 18.800100326538086 | 18.799100875854492 | 3.880000114440918 | 28.458200454711914 | 20.079200744628906 | 0.7519999742507935 | 3.8989999294281006 | 0.5099999904632568 | 0.0 | 1.8309999704360962 | -9.0 |
6.5 | 6.5 | 18.80419921875 | 18.8031005859375 | 3.880500078201294 | 28.458900451660156 | 20.078800201416016 | 0.5059999823570251 | 3.9000000953674316 | 0.5099999904632568 | 0.0 | 1.902999997138977 | -9.0 |
7.0 | 7.0 | 18.81730079650879 | 18.816099166870117 | 3.882699966430664 | 28.46780014038086 | 20.082399368286133 | 0.3869999945163727 | 3.8959999084472656 | 0.5099999904632568 | 0.0 | 1.8919999599456787 | -9.0 |
7.599999904632568 | 7.5 | 18.846599578857422 | 18.845399856567383 | 3.887200117111206 | 28.48430061340332 | 20.087900161743164 | 0.6449999809265137 | 3.881999969482422 | 0.5099999904632568 | 0.0 | 1.9170000553131104 | -9.0 |
8.100000381469727 | 8.0 | 18.8799991607666 | 18.878700256347656 | 3.892199993133545 | 28.502199172973633 | 20.093399047851562 | 0.7519999742507935 | 3.8480000495910645 | 0.5099999904632568 | 0.0 | 1.88100004196167 | -9.0 |
8.600000381469727 | 8.5 | 18.891799926757812 | 18.890300750732422 | 3.893899917602539 | 28.507200241088867 | 20.09440040588379 | 0.6769999861717224 | 3.8389999866485596 | 0.5099999904632568 | 0.0 | 1.843000054359436 | -9.0 |
9.100000381469727 | 9.0 | 18.88010025024414 | 18.878599166870117 | 3.8922998905181885 | 28.502599716186523 | 20.093700408935547 | 0.3569999933242798 | 3.8410000801086426 | 0.5099999904632568 | 0.0 | 1.7640000581741333 | -9.0 |
9.600000381469727 | 9.5 | 18.955699920654297 | 18.954099655151367 | 3.9137001037597656 | 28.62380027770996 | 20.167600631713867 | 0.414000004529953 | 3.8399999141693115 | 0.5099999904632568 | 0.0 | 1.7949999570846558 | -9.0 |
10.100000381469727 | 10.0 | 19.157800674438477 | 19.156099319458008 | 3.9697000980377197 | 28.938899993896484 | 20.35810089111328 | 0.6660000085830688 | 3.6050000190734863 | 0.5099999904632568 | 0.0 | 1.8960000276565552 | -9.0 |
10.600000381469727 | 10.5 | 19.18090057373047 | 19.179000854492188 | 3.9927000999450684 | 29.10930061340332 | 20.4822998046875 | 0.7369999885559082 | 3.6559998989105225 | 0.5099999904632568 | 0.0 | 1.8899999856948853 | -9.0 |
11.100000381469727 | 11.0 | 19.115299224853516 | 19.113399505615234 | 3.992799997329712 | 29.155899047851562 | 20.534000396728516 | 0.5889999866485596 | 3.8929998874664307 | 0.5099999904632568 | 0.0 | 1.7960000038146973 | -9.0 |
11.600000381469727 | 11.5 | 19.13719940185547 | 19.13520050048828 | 3.985100030899048 | 29.078100204467773 | 20.46940040588379 | 0.31299999356269836 | 3.8269999027252197 | 0.5099999904632568 | 0.0 | 1.7369999885559082 | -9.0 |
12.100000381469727 | 12.0 | 19.324100494384766 | 19.32200050354004 | 4.045300006866455 | 29.434999465942383 | 20.694900512695312 | 0.6449999809265137 | 3.984999895095825 | 0.5099999904632568 | 0.0 | 1.8990000486373901 | -9.0 |
12.600000381469727 | 12.5 | 19.281400680541992 | 19.279199600219727 | 4.049900054931641 | 29.502199172973633 | 20.75670051574707 | 0.8309999704360962 | 4.056000232696533 | 0.5099999904632568 | 0.0 | 1.9010000228881836 | -9.0 |
13.100000381469727 | 13.0 | 19.321399688720703 | 19.31909942626953 | 4.065800189971924 | 29.602699279785156 | 20.823299407958984 | 0.8100000023841858 | 3.930999994277954 | 0.5099999904632568 | 0.0 | 1.9210000038146973 | -9.0 |
13.600000381469727 | 13.5 | 19.36720085144043 | 19.36479949951172 | 4.082499980926514 | 29.70560073852539 | 20.890300750732422 | 0.5440000295639038 | 3.874000072479248 | 0.5099999904632568 | 0.0 | 1.8669999837875366 | -9.0 |
14.100000381469727 | 14.0 | 19.357900619506836 | 19.35540008544922 | 4.079599857330322 | 29.68829917907715 | 20.879499435424805 | 0.3499999940395355 | 3.9019999504089355 | 0.5099999904632568 | 0.0 | 1.7710000276565552 | -9.0 |
14.600000381469727 | 14.5 | 19.40239906311035 | 19.399900436401367 | 4.098100185394287 | 29.806400299072266 | 20.95840072631836 | 0.722000002861023 | 3.815999984741211 | 0.5099999904632568 | 0.0 | 1.7619999647140503 | -9.0 |
15.100000381469727 | 15.0 | 19.419300079345703 | 19.41659927368164 | 4.1066999435424805 | 29.86400032043457 | 20.99799919128418 | 0.8080000281333923 | 3.7890000343322754 | 0.5099999904632568 | 0.0 | 1.7450000047683716 | -9.0 |
15.600000381469727 | 15.5 | 19.565200805664062 | 19.5625 | 4.14900016784668 | 30.102100372314453 | 21.1427001953125 | 0.7269999980926514 | 3.690000057220459 | 0.5099999904632568 | 0.0 | 1.7289999723434448 | -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.