Metocean: Historical collections
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Brought to you by NOAA NMFS SWFSC ERD |
Dataset Title: | "LATEX CTD - d93g160.nc - 28.58N, 95.47W - 1993-11-17" |
Institution: | Texas A&M University, Department of Oceanography (Dataset ID: latex_d93g160) |
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 | 19.465200424194336 | 19.46489906311035 | 4.31820011138916 | 31.55430030822754 | 22.27389907836914 | 0.24699999392032623 | 2.5260000228881836 | 0.9700000286102295 | 0.27300000190734863 | 1.63100004196167 | -9.0 |
2.0 | 2.0 | 19.462400436401367 | 19.461999893188477 | 4.317299842834473 | 31.548999786376953 | 22.270599365234375 | 0.6190000176429749 | 2.503000020980835 | 0.6600000262260437 | 0.1080000028014183 | 1.625 | -9.0 |
2.5 | 2.5 | 19.460500717163086 | 19.459999084472656 | 4.316800117492676 | 31.546300888061523 | 22.269100189208984 | 0.3330000042915344 | 2.509000062942505 | 0.5699999928474426 | 0.04699999839067459 | 1.621999979019165 | -9.0 |
3.0 | 3.0 | 19.462099075317383 | 19.46150016784668 | 4.316999912261963 | 31.546499252319336 | 22.268800735473633 | 0.4390000104904175 | 2.5269999504089355 | 0.5199999809265137 | 0.0020000000949949026 | 1.6469999551773071 | -9.0 |
3.5 | 3.5 | 19.461000442504883 | 19.460399627685547 | 4.316999912261963 | 31.547199249267578 | 22.26959991455078 | 0.6039999723434448 | 2.5220000743865967 | 0.5099999904632568 | 0.0 | 1.621000051498413 | -9.0 |
4.0 | 4.0 | 19.46820068359375 | 19.467500686645508 | 4.318600177764893 | 31.55419921875 | 22.2731990814209 | 0.6269999742507935 | 2.5230000019073486 | 0.5099999904632568 | 0.0 | 1.6319999694824219 | -9.0 |
4.5 | 4.5 | 19.503400802612305 | 19.502599716186523 | 4.326200008392334 | 31.59000015258789 | 22.291500091552734 | 0.4959999918937683 | 2.5260000228881836 | 0.5099999904632568 | 0.0 | 1.6770000457763672 | -9.0 |
5.0 | 5.0 | 19.57200050354004 | 19.57110023498535 | 4.343500137329102 | 31.678600311279297 | 22.34160041809082 | 0.41200000047683716 | 2.5280001163482666 | 0.5099999904632568 | 0.0 | 1.680999994277954 | -9.0 |
5.5 | 5.5 | 19.649599075317383 | 19.64859962463379 | 4.3643999099731445 | 31.790199279785156 | 22.40690040588379 | 0.5370000004768372 | 2.5290000438690186 | 0.5099999904632568 | 0.0 | 1.6859999895095825 | -9.0 |
6.0 | 6.0 | 19.67289924621582 | 19.67180061340332 | 4.370800018310547 | 31.824199676513672 | 22.42690086364746 | 0.5899999737739563 | 2.5139999389648438 | 0.5099999904632568 | 0.0 | 1.652999997138977 | -9.0 |
6.5 | 6.5 | 19.694700241088867 | 19.693500518798828 | 4.3769001960754395 | 31.85740089416504 | 22.44659996032715 | 0.49399998784065247 | 2.51200008392334 | 0.5099999904632568 | 0.0 | 1.659999966621399 | -9.0 |
7.0 | 7.0 | 19.776899337768555 | 19.775699615478516 | 4.400899887084961 | 31.989500045776367 | 22.526199340820312 | 0.382999986410141 | 2.509000062942505 | 0.5099999904632568 | 0.0 | 1.6410000324249268 | -9.0 |
7.599999904632568 | 7.5 | 19.938600540161133 | 19.937299728393555 | 4.448999881744385 | 32.25619888305664 | 22.687700271606445 | 0.5230000019073486 | 2.503000020980835 | 0.5099999904632568 | 0.0 | 1.6430000066757202 | -9.0 |
8.100000381469727 | 8.0 | 20.0049991607666 | 20.003599166870117 | 4.466899871826172 | 32.34989929199219 | 22.741899490356445 | 0.6449999809265137 | 2.4649999141693115 | 0.5099999904632568 | 0.0 | 1.6330000162124634 | -9.0 |
8.600000381469727 | 8.5 | 20.05069923400879 | 20.049100875854492 | 4.481500148773193 | 32.43280029296875 | 22.79330062866211 | 0.6449999809265137 | 2.436000108718872 | 0.5099999904632568 | 0.0 | 1.6399999856948853 | -9.0 |
9.100000381469727 | 9.0 | 20.077199935913086 | 20.07550048828125 | 4.489699840545654 | 32.47850036621094 | 22.821199417114258 | 0.5339999794960022 | 2.427000045776367 | 0.5099999904632568 | 0.0 | 1.6100000143051147 | -9.0 |
9.600000381469727 | 9.5 | 20.124399185180664 | 20.122699737548828 | 4.504300117492676 | 32.56010055541992 | 22.871000289916992 | 0.335999995470047 | 2.437999963760376 | 0.5099999904632568 | 0.0 | 1.5950000286102295 | -9.0 |
10.100000381469727 | 10.0 | 20.193599700927734 | 20.19179916381836 | 4.524700164794922 | 32.671600341796875 | 22.937999725341797 | 0.4779999852180481 | 2.4509999752044678 | 0.5099999904632568 | 0.0 | 1.6009999513626099 | -9.0 |
10.600000381469727 | 10.5 | 20.216400146484375 | 20.214399337768555 | 4.531599998474121 | 32.708900451660156 | 22.960399627685547 | 0.6520000100135803 | 2.4489998817443848 | 0.5099999904632568 | 0.0 | 1.593999981880188 | -9.0 |
11.100000381469727 | 11.0 | 20.22260093688965 | 20.220600128173828 | 4.533299922943115 | 32.71820068359375 | 22.965900421142578 | 0.6710000038146973 | 2.4110000133514404 | 0.5099999904632568 | 0.0 | 1.5829999446868896 | -9.0 |
11.600000381469727 | 11.5 | 20.229999542236328 | 20.227800369262695 | 4.535299777984619 | 32.72819900512695 | 22.971599578857422 | 0.5509999990463257 | 2.38100004196167 | 0.5099999904632568 | 0.0 | 1.5779999494552612 | -9.0 |
12.100000381469727 | 12.0 | 20.234500885009766 | 20.2322998046875 | 4.536399841308594 | 32.733699798583984 | 22.974599838256836 | 0.4180000126361847 | 2.390000104904175 | 0.5099999904632568 | 0.0 | 1.5889999866485596 | -9.0 |
12.600000381469727 | 12.5 | 20.244199752807617 | 20.241899490356445 | 4.538899898529053 | 32.74610137939453 | 22.981599807739258 | 0.3790000081062317 | 2.4230000972747803 | 0.5099999904632568 | 0.0 | 1.6519999504089355 | -9.0 |
13.100000381469727 | 13.0 | 20.25320053100586 | 20.25079917907715 | 4.541200160980225 | 32.757301330566406 | 22.98780059814453 | 0.4560000002384186 | 2.430999994277954 | 0.5099999904632568 | 0.0 | 1.6360000371932983 | -9.0 |
13.600000381469727 | 13.5 | 20.270000457763672 | 20.267499923706055 | 4.545599937438965 | 32.77939987182617 | 23.000200271606445 | 0.5820000171661377 | 2.4140000343322754 | 0.5099999904632568 | 0.0 | 1.5850000381469727 | -9.0 |
14.100000381469727 | 14.0 | 20.271799087524414 | 20.26919937133789 | 4.546000003814697 | 32.78160095214844 | 23.001399993896484 | 0.6110000014305115 | 2.424999952316284 | 0.5099999904632568 | 0.0 | 1.593999981880188 | -9.0 |
14.600000381469727 | 14.5 | 20.2898006439209 | 20.287099838256836 | 4.55079984664917 | 32.80569839477539 | 23.014999389648438 | 0.5189999938011169 | 2.4070000648498535 | 0.5099999904632568 | 0.0 | 1.5809999704360962 | -9.0 |
15.100000381469727 | 15.0 | 20.306900024414062 | 20.304100036621094 | 4.555099964141846 | 32.826900482177734 | 23.02669906616211 | 0.4189999997615814 | 2.4130001068115234 | 0.5099999904632568 | 0.0 | 1.5789999961853027 | -9.0 |
15.600000381469727 | 15.5 | 20.324499130249023 | 20.321699142456055 | 4.559500217437744 | 32.84859848022461 | 23.038700103759766 | 0.4560000002384186 | 2.4140000343322754 | 0.5099999904632568 | 0.0 | 1.5859999656677246 | -9.0 |
16.100000381469727 | 16.0 | 20.336700439453125 | 20.333799362182617 | 4.562699794769287 | 32.864898681640625 | 23.04789924621582 | 0.5120000243186951 | 2.4149999618530273 | 0.5099999904632568 | 0.0 | 1.5609999895095825 | -9.0 |
16.600000381469727 | 16.5 | 20.354000091552734 | 20.35099983215332 | 4.566999912261963 | 32.88610076904297 | 23.059499740600586 | 0.46399998664855957 | 2.4159998893737793 | 0.5099999904632568 | 0.0 | 1.5920000076293945 | -9.0 |
17.100000381469727 | 17.0 | 20.37350082397461 | 20.37030029296875 | 4.572199821472168 | 32.912601470947266 | 23.074499130249023 | 0.40700000524520874 | 2.4210000038146973 | 0.5099999904632568 | 0.0 | 1.5959999561309814 | -9.0 |
17.600000381469727 | 17.5 | 20.380599975585938 | 20.377300262451172 | 4.573999881744385 | 32.92169952392578 | 23.079700469970703 | 0.5580000281333923 | 2.421999931335449 | 0.5099999904632568 | 0.0 | 1.6119999885559082 | -9.0 |
18.100000381469727 | 18.0 | 20.407499313354492 | 20.40410041809082 | 4.581099987030029 | 32.95790100097656 | 23.100200653076172 | 0.5680000185966492 | 2.4200000762939453 | 0.5099999904632568 | 0.0 | 1.5980000495910645 | -9.0 |
18.600000381469727 | 18.5 | 20.432600021362305 | 20.429100036621094 | 4.587900161743164 | 32.99300003051758 | 23.12019920349121 | 0.3630000054836273 | 2.3980000019073486 | 0.5099999904632568 | 0.0 | 1.625 | -9.0 |
19.100000381469727 | 19.0 | 20.446800231933594 | 20.443199157714844 | 4.591700077056885 | 33.01190185546875 | 23.13089942932129 | 0.515999972820282 | 2.4070000648498535 | 0.5099999904632568 | 0.0 | 1.5429999828338623 | -9.0 |
19.600000381469727 | 19.5 | 20.451000213623047 | 20.447399139404297 | 4.592800140380859 | 33.017398834228516 | 23.134000778198242 | 0.45899999141693115 | 2.3889999389648438 | 0.5099999904632568 | 0.0 | 1.5770000219345093 | -9.0 |
20.100000381469727 | 20.0 | 20.452800750732422 | 20.449100494384766 | 4.593299865722656 | 33.01940155029297 | 23.135099411010742 | 0.6019999980926514 | 2.367000102996826 | 0.5099999904632568 | 0.0 | 1.5440000295639038 | -9.0 |
In total, there are 38 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.