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Dataset Title:  "LATEX CTD - d92a072.nc - 28.88N, 90.51W - 1992-05-05" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: latex_d92a072)
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: 27)
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   27 options
    depth ?  =  m   27 options
    temperature ?  =  degree_C   27 options
    potentialTemperature ?  =  degree_C   27 options
    conductivity ?  =  Siemens per meter   27 options
    salinity ?  =  PSU   27 options
    sigmat ?  =  kg m-3   27 options
    descentRate ?  =  meters per second   27 options
    transmission ?  =  percent   27 options
    par ?  =  umol m-2 s-1   27 options
    parv ?  =  volts   27 options
    fluorescence ?  =  volts   25 options
    backscattering ?  =  volts   1 option: -9.0

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
1.5 1.5 23.81920051574707 23.818899154663086 4.275300025939941 28.212600708007812 18.56570053100586 -0.10999999940395355 2.9570000171661377 308.0 2.9739999771118164 1.628000020980835 -9.0
2.0 2.0 23.724300384521484 23.723899841308594 4.265699863433838 28.202199935913086 18.58489990234375 0.4230000078678131 2.953000068664551 723.0 3.3450000286102295 1.687000036239624 -9.0
2.5 2.5 23.628700256347656 23.62820053100586 4.256800174713135 28.1968994140625 18.60810089111328 0.5049999952316284 2.9260001182556152 260.0 2.9010000228881836 1.7630000114440918 -9.0
3.0 3.0 23.54789924621582 23.547300338745117 4.250500202178955 28.201200485229492 18.634300231933594 0.45899999141693115 2.9170000553131104 167.0 2.7079999446868896 1.9490000009536743 -9.0
3.5 3.5 23.501800537109375 23.501100540161133 4.250999927520752 28.23419952392578 18.672300338745117 0.4490000009536743 2.9059998989105225 134.0 2.611999988555908 2.061000108718872 -9.0
4.0 4.0 23.37619972229004 23.37540054321289 4.242599964141846 28.251699447631836 18.72100067138672 0.4880000054836273 2.888000011444092 114.0 2.5420000553131104 2.4200000762939453 -9.0
4.5 4.5 23.3080997467041 23.307199478149414 4.236800193786621 28.25189971923828 18.740299224853516 0.4690000116825104 2.8940000534057617 98.30000305175781 2.4779999256134033 2.7709999084472656 -9.0
5.0 5.0 23.27280044555664 23.271799087524414 4.235599994659424 28.26580047607422 18.760799407958984 0.41600000858306885 2.875 80.80000305175781 2.3929998874664307 2.947999954223633 -9.0
5.5 5.5 23.276100158691406 23.274999618530273 4.252099990844727 28.385799407958984 18.85059928894043 0.43799999356269836 2.8429999351501465 66.0 2.305000066757202 3.683000087738037 -9.0
6.0 6.0 23.29949951171875 23.29829978942871 4.273799896240234 28.532400131225586 18.954700469970703 0.5080000162124634 2.7660000324249268 56.5 2.23799991607666 4.178999900817871 -9.0
6.5 6.5 23.25429916381836 23.253000259399414 4.2820000648498535 28.622499465942383 19.035499572753906 0.5109999775886536 2.8010001182556152 48.20000076293945 2.1689999103546143 4.478000164031982 -9.0
7.0 7.0 23.0447998046875 23.043399810791016 4.3379998207092285 29.179899215698242 19.51580047607422 0.46299999952316284 2.803999900817871 42.099998474121094 2.109999895095825 4.99399995803833 -9.0
7.599999904632568 7.5 22.291099548339844 22.289600372314453 4.636099815368652 31.97100067138672 21.83930015563965 0.42500001192092896 2.753999948501587 35.900001525878906 2.0409998893737793 4.7789998054504395 -9.0
8.100000381469727 8.0 22.433000564575195 22.431400299072266 4.828999996185303 33.35530090332031 22.84950065612793 0.4269999861717224 2.7260000705718994 31.899999618530273 1.9900000095367432 2.4489998817443848 -9.0
8.600000381469727 8.5 22.570499420166016 22.56879997253418 4.9558000564575195 34.23109817504883 23.475200653076172 0.4099999964237213 2.9189999103546143 28.399999618530273 1.9390000104904175 1.13100004196167 -9.0
9.100000381469727 9.0 22.510000228881836 22.50819969177246 5.008600234985352 34.68899917602539 23.83989906311035 0.3840000033378601 3.5290000438690186 25.299999237060547 1.8880000114440918 0.6159999966621399 -9.0
9.600000381469727 9.5 22.366100311279297 22.364200592041016 5.002799987792969 34.7588005065918 23.933700561523438 0.3160000145435333 3.944999933242798 23.700000762939453 1.8609999418258667 0.453000009059906 -9.0
10.100000381469727 10.0 22.386999130249023 22.385000228881836 5.028200149536133 34.939998626708984 24.06529998779297 0.2770000100135803 4.1519999504089355 21.5 1.819000005722046 0.335999995470047 -9.0
10.600000381469727 10.5 22.375900268554688 22.37380027770996 5.053800106048584 35.148799896240234 24.226999282836914 0.23000000417232513 4.166999816894531 20.799999237060547 1.8029999732971191 0.34599998593330383 -9.0
11.100000381469727 11.0 22.253700256347656 22.25149917602539 5.055300235748291 35.2593994140625 24.345600128173828 0.24699999392032623 4.098999977111816 19.5 1.7760000228881836 0.40299999713897705 -9.0
11.600000381469727 11.5 22.120100021362305 22.117799758911133 5.052700042724609 35.34749984741211 24.450300216674805 0.22100000083446503 3.9600000381469727 18.200000762939453 1.746000051498413 0.43299999833106995 -9.0
12.100000381469727 12.0 21.99220085144043 21.98979949951172 5.044099807739258 35.3838996887207 24.513900756835938 0.26600000262260437 3.61899995803833 17.0 1.715000033378601 0.3720000088214874 -9.0
12.600000381469727 12.5 21.918699264526367 21.916200637817383 5.0370001792907715 35.38750076293945 24.537200927734375 0.2750000059604645 3.371999979019165 15.899999618530273 1.687999963760376 0.335999995470047 -9.0
13.100000381469727 13.0 21.80109977722168 21.798599243164062 5.026599884033203 35.402099609375 24.581199645996094 0.21899999678134918 3.4159998893737793 14.899999618530273 1.659999966621399 0.3149999976158142 -9.0
13.600000381469727 13.5 21.655799865722656 21.653099060058594 5.0177001953125 35.45050048828125 24.65850067138672 0.2680000066757202 3.5999999046325684 13.800000190734863 1.6269999742507935 0.31200000643730164 -9.0
14.100000381469727 14.0 21.56909942626953 21.566299438476562 5.012400150299072 35.479801177978516 24.70490074157715 0.28600001335144043 3.8959999084472656 12.600000381469727 1.5850000381469727 0.30000001192092896 -9.0
14.600000381469727 14.5 21.516000747680664 21.513099670410156 5.0096001625061035 35.500999450683594 24.73579978942871 0.20999999344348907 3.9210000038146973 11.199999809265137 1.5329999923706055 0.3149999976158142 -9.0

In total, there are 27 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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