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Dataset Title:  "LATEX CTD - d94h062.nc - 28.75N, 93.0W - 1994-04-29" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: latex_d94h062)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 52)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    pressure ?  =  dBar   52 options
    depth ?  =  m   52 options
    temperature ?  =  degree_C   51 options
    potentialTemperature ?  =  degree_C   52 options
    conductivity ?  =  Siemens per meter   44 options
    salinity ?  =  PSU   48 options
    sigmat ?  =  kg m-3   52 options
    descentRate ?  =  meters per second   51 options
    transmission ?  =  percent   45 options
    par ?  =  umol m-2 s-1   52 options
    parv ?  =  volts   52 options
    fluorescence ?  =  volts   40 options
    backscattering ?  =  volts   28 options

View:      Map of All Related Data ?      Distinct Data Counts ?     Distinct Data ?      Related Data Counts ?     Related Data ?

 
Map of All Related Data ?   (Refine the map and/or download the image)

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.
 


Distinct Data Counts ?

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
2.0 2.0 22.662200927734375 22.661800384521484 5.11329984664917 35.38359832763672 24.323400497436523 0.37700000405311584 3.928999900817871 123.0 2.4230000972747803 0.9950000047683716 0.06400000303983688
2.5 2.5 22.66189956665039 22.661399841308594 5.11329984664917 35.38359832763672 24.32349967956543 0.3709999918937683 3.937000036239624 86.0 2.2660000324249268 0.9660000205039978 0.0560000017285347
3.0 3.0 22.659700393676758 22.659099578857422 5.113100051879883 35.38399887084961 24.324399948120117 0.4909999966621399 3.934999942779541 77.19999694824219 2.2190001010894775 1.5149999856948853 0.054999999701976776
3.5 3.5 22.644399642944336 22.643600463867188 5.111700057983398 35.38520050048828 24.329700469970703 0.44699999690055847 3.940999984741211 66.5999984741211 2.1549999713897705 1.0449999570846558 0.054999999701976776
4.0 4.0 22.607500076293945 22.606700897216797 5.108699798583984 35.39139938354492 24.344999313354492 0.3700000047683716 3.943000078201294 61.29999923706055 2.11899995803833 0.9940000176429749 0.054999999701976776
4.5 4.5 22.546600341796875 22.545700073242188 5.104100227355957 35.40520095825195 24.372900009155273 0.35100001096725464 3.938999891281128 53.0 2.055999994277954 0.9279999732971191 0.054999999701976776
5.0 5.0 22.472400665283203 22.471399307250977 5.105199813842773 35.4739990234375 24.446300506591797 0.5479999780654907 3.947999954223633 49.5 2.0260000228881836 0.8799999952316284 0.05700000002980232
5.5 5.5 22.32979965209961 22.328699111938477 5.108399868011475 35.61520004272461 24.594100952148438 0.5139999985694885 4.019000053405762 46.400001525878906 1.9980000257492065 0.8960000276565552 0.054999999701976776
6.0 6.0 22.318300247192383 22.317100524902344 5.114699840545654 35.67359924316406 24.641700744628906 0.7409999966621399 4.177000045776367 43.099998474121094 1.965999960899353 0.8510000109672546 0.05299999937415123
6.5 6.5 22.2637996673584 22.262500762939453 5.134500026702881 35.8739013671875 24.80940055847168 0.7049999833106995 4.348999977111816 38.099998474121094 1.9119999408721924 0.6330000162124634 0.05000000074505806
7.0 7.0 22.22599983215332 22.224599838256836 5.139500141143799 35.94449996948242 24.87380027770996 0.550000011920929 4.354000091552734 32.5 1.843999981880188 0.4650000035762787 0.03200000151991844
7.599999904632568 7.5 22.23150062561035 22.229999542236328 5.137800216674805 35.92620086669922 24.858299255371094 0.3799999952316284 4.3429999351501465 30.399999618530273 1.815000057220459 0.28700000047683716 0.02800000086426735
8.100000381469727 8.0 22.201000213623047 22.199399948120117 5.139800071716309 35.96739959716797 24.898399353027344 0.6790000200271606 4.388999938964844 28.5 1.7860000133514404 0.23899999260902405 0.03200000151991844
8.600000381469727 8.5 22.182199478149414 22.180500030517578 5.140200138092041 35.98550033569336 24.917400360107422 0.8270000219345093 4.39900016784668 27.100000381469727 1.7640000581741333 0.2240000069141388 0.032999999821186066
9.100000381469727 9.0 22.17449951171875 22.17259979248047 5.140900135040283 35.997501373291016 24.928800582885742 0.8429999947547913 4.401000022888184 25.799999237060547 1.7430000305175781 0.20999999344348907 0.024000000208616257
9.600000381469727 9.5 22.14889907836914 22.14699935913086 5.139800071716309 36.01020050048828 24.94569969177246 0.7179999947547913 4.401000022888184 24.5 1.7200000286102295 0.20900000631809235 0.02199999988079071
10.100000381469727 10.0 22.135700225830078 22.133699417114258 5.139999866485596 36.022701263427734 24.958900451660156 0.3889999985694885 4.4070000648498535 22.899999618530273 1.690999984741211 0.2029999941587448 0.024000000208616257
10.600000381469727 10.5 22.146900177001953 22.144800186157227 5.142099857330322 36.02909851074219 24.9606990814209 0.5180000066757202 4.3979997634887695 22.299999237060547 1.6799999475479126 0.19300000369548798 0.02199999988079071
11.100000381469727 11.0 22.125200271606445 22.12299919128418 5.143099784851074 36.055198669433594 24.986600875854492 0.7059999704360962 4.388999938964844 20.899999618530273 1.6519999504089355 0.1979999989271164 0.02199999988079071
11.600000381469727 11.5 22.097400665283203 22.09510040283203 5.142499923706055 36.07310104370117 25.008100509643555 0.6809999942779541 4.4070000648498535 19.399999618530273 1.6200000047683716 0.20100000500679016 0.020999999716877937
12.100000381469727 12.0 22.088199615478516 22.085800170898438 5.1427998542785645 36.08290100097656 25.018199920654297 0.5490000247955322 4.410999774932861 18.399999618530273 1.5959999561309814 0.20100000500679016 0.01899999938905239
12.600000381469727 12.5 22.061500549316406 22.05900001525879 5.1417999267578125 36.09709930419922 25.03660011291504 0.3370000123977661 4.418000221252441 18.0 1.5870000123977661 0.20900000631809235 0.017999999225139618
13.100000381469727 13.0 22.067800521850586 22.065200805664062 5.141200065612793 36.08700180053711 25.027099609375 0.3269999921321869 4.416999816894531 17.600000381469727 1.5770000219345093 0.20600000023841858 0.01899999938905239
13.600000381469727 13.5 22.02739906311035 22.024700164794922 5.141200065612793 36.12070083618164 25.064199447631836 0.4740000069141388 4.418000221252441 16.5 1.5490000247955322 0.21799999475479126 0.020999999716877937
14.100000381469727 14.0 22.024599075317383 22.021799087524414 5.14139986038208 36.12480163574219 25.068099975585938 0.6679999828338623 4.415999889373779 15.899999618530273 1.534000039100647 0.22499999403953552 0.020999999716877937
14.600000381469727 14.5 22.020700454711914 22.017799377441406 5.141600131988525 36.12929916381836 25.07270050048828 0.7210000157356262 4.410999774932861 15.5 1.5210000276565552 0.21699999272823334 0.020999999716877937
15.100000381469727 15.0 22.019899368286133 22.01689910888672 5.14169979095459 36.130401611328125 25.07379913330078 0.6200000047683716 4.4079999923706055 15.0 1.5069999694824219 0.21799999475479126 0.020999999716877937
15.600000381469727 15.5 22.019899368286133 22.016799926757812 5.1417999267578125 36.13100051879883 25.074199676513672 0.37599998712539673 4.406000137329102 14.5 1.4919999837875366 0.20999999344348907 0.020999999716877937
16.100000381469727 16.0 22.019399642944336 22.016199111938477 5.1417999267578125 36.131500244140625 25.074800491333008 0.3610000014305115 4.4070000648498535 14.300000190734863 1.4880000352859497 0.22300000488758087 0.024000000208616257
16.600000381469727 16.5 22.01959991455078 22.016300201416016 5.142099857330322 36.13309860229492 25.076000213623047 0.5379999876022339 4.4029998779296875 13.699999809265137 1.468999981880188 0.21899999678134918 0.02199999988079071
17.100000381469727 17.0 22.018199920654297 22.014799118041992 5.142199993133545 36.135398864746094 25.078100204467773 0.5849999785423279 4.388999938964844 13.100000381469727 1.4500000476837158 0.22100000083446503 0.02199999988079071
17.600000381469727 17.5 22.016300201416016 22.012800216674805 5.14169979095459 36.13290023803711 25.076900482177734 0.5099999904632568 4.382999897003174 12.600000381469727 1.4329999685287476 0.22499999403953552 0.024000000208616257
18.100000381469727 18.0 22.014699935913086 22.01110076904297 5.141900062561035 36.13570022583008 25.07939910888672 0.3840000033378601 4.377999782562256 12.399999618530273 1.4240000247955322 0.21899999678134918 0.02500000037252903
18.600000381469727 18.5 22.011899948120117 22.00819969177246 5.14169979095459 36.135799407958984 25.080299377441406 0.42500001192092896 4.379000186920166 12.100000381469727 1.4149999618530273 0.22499999403953552 0.026000000536441803
19.100000381469727 19.0 22.007999420166016 22.00429916381836 5.141300201416016 36.13560104370117 25.081300735473633 0.5709999799728394 4.372000217437744 11.699999809265137 1.4010000228881836 0.23899999260902405 0.027000000700354576
19.600000381469727 19.5 22.003299713134766 21.999399185180664 5.1407999992370605 36.13570022583008 25.082700729370117 0.6159999966621399 4.361999988555908 11.300000190734863 1.3839999437332153 0.2329999953508377 0.027000000700354576
20.100000381469727 20.0 22.00160026550293 21.997600555419922 5.140600204467773 36.13560104370117 25.083099365234375 0.4860000014305115 4.359000205993652 10.800000190734863 1.3660000562667847 0.22699999809265137 0.027000000700354576
20.600000381469727 20.5 22.00510025024414 22.000999450683594 5.140999794006348 36.135799407958984 25.082300186157227 0.328000009059906 4.361000061035156 10.699999809265137 1.3589999675750732 0.2280000001192093 0.02800000086426735
21.100000381469727 21.0 22.000600814819336 21.996400833129883 5.140500068664551 36.13479995727539 25.08289909362793 0.5540000200271606 4.355999946594238 10.5 1.3509999513626099 0.2280000001192093 0.028999999165534973
21.600000381469727 21.5 21.992599487304688 21.988300323486328 5.139699935913086 36.13529968261719 25.085599899291992 0.6930000185966492 4.343999862670898 10.0 1.3320000171661377 0.22300000488758087 0.028999999165534973
22.100000381469727 22.0 21.987899780273438 21.98349952697754 5.138999938964844 36.133399963378906 25.085500717163086 0.6140000224113464 4.3460001945495605 9.649999618530273 1.315999984741211 0.22300000488758087 0.029999999329447746
22.700000762939453 22.5 21.969999313354492 21.965499877929688 5.13700008392334 36.13240051269531 25.089799880981445 0.3160000145435333 4.35099983215332 9.319999694824219 1.3009999990463257 0.2329999953508377 0.029999999329447746
23.200000762939453 23.0 21.787399291992188 21.782899856567383 5.116000175476074 36.11869812011719 25.13050079345703 0.382999986410141 4.3379998207092285 9.34000015258789 1.3020000457763672 0.2290000021457672 0.029999999329447746
23.700000762939453 23.5 21.32270050048828 21.318099975585938 5.073400020599365 36.169498443603516 25.298500061035156 0.5839999914169312 4.00600004196167 8.979999542236328 1.284999966621399 0.26499998569488525 0.03099999949336052
24.200000762939453 24.0 21.16469955444336 21.15999984741211 5.0594000816345215 36.19060134887695 25.35810089111328 0.6650000214576721 3.696000099182129 8.640000343322754 1.2680000066757202 0.38499999046325684 0.09600000083446503
24.700000762939453 24.5 21.076099395751953 21.071399688720703 5.051199913024902 36.19929885864258 25.38909912109375 0.5809999704360962 3.5460000038146973 8.34000015258789 1.253000020980835 0.4950000047683716 0.16300000250339508
25.200000762939453 25.0 21.03179931640625 21.026899337768555 5.047900199890137 36.209800720214844 25.409299850463867 0.44999998807907104 3.6740000247955322 8.170000076293945 1.24399995803833 0.578000009059906 0.1599999964237213
25.700000762939453 25.5 21.056800842285156 21.05190086364746 5.050300121307373 36.207698822021484 25.400800704956055 0.3619999885559082 3.744999885559082 7.420000076293945 1.2020000219345093 0.6159999966621399 0.11100000143051147
26.200000762939453 26.0 21.024700164794922 21.019699096679688 5.047399997711182 36.211700439453125 25.412700653076172 0.6150000095367432 3.375999927520752 6.269999980926514 1.128999948501587 0.7170000076293945 0.22699999809265137
26.700000762939453 26.5 21.012100219726562 21.006999969482422 5.046299934387207 36.213199615478516 25.417299270629883 0.7099999785423279 3.3510000705718994 5.730000019073486 1.090000033378601 0.8059999942779541 0.23800000548362732
27.200000762939453 27.0 20.942800521850586 20.937599182128906 5.03879976272583 36.21099853515625 25.434600830078125 0.6620000004768372 3.319999933242798 5.179999828338623 1.0460000038146973 0.8399999737739563 0.2460000067949295
27.700000762939453 27.5 20.78380012512207 20.778499603271484 5.02370023727417 36.22439956665039 25.48819923400879 0.328000009059906 3.0910000801086426 4.539999961853027 0.9890000224113464 0.9169999957084656 0.2630000114440918

In total, there are 52 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.
 


Related Data Counts ?

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.


 
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