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Dataset Title:  "LATEX CTD - d94h067.nc - 29.27N, 93.0W - 1994-04-30" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: latex_d94h067)
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: 26)
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   26 options
    depth ?  =  m   26 options
    temperature ?  =  degree_C   25 options
    potentialTemperature ?  =  degree_C   26 options
    conductivity ?  =  Siemens per meter   23 options
    salinity ?  =  PSU   25 options
    sigmat ?  =  kg m-3   26 options
    descentRate ?  =  meters per second   26 options
    transmission ?  =  percent   25 options
    par ?  =  umol m-2 s-1   4 options
    parv ?  =  volts   5 options
    fluorescence ?  =  volts   25 options
    backscattering ?  =  volts   23 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
3.0 3.0 22.990400314331055 22.98979949951172 5.062900066375732 34.73080062866211 23.733800888061523 0.07000000029802322 3.249000072479248 0.550000011920929 0.07100000232458115 0.9959999918937683 0.25999999046325684
3.5 3.5 23.038999557495117 23.038299560546875 5.06689977645874 34.722801208496094 23.713699340820312 0.3199999928474426 3.2850000858306885 0.6800000071525574 0.16200000047683716 1.055999994277954 0.23999999463558197
4.0 4.0 23.070499420166016 23.069700241088867 5.068600177764893 34.71039962768555 23.695199966430664 0.5339999794960022 3.3350000381469727 0.550000011920929 0.06800000369548798 1.0089999437332153 0.23600000143051147
4.5 4.5 23.071300506591797 23.07040023803711 5.06850004196167 34.70920181274414 23.694000244140625 0.6520000100135803 3.3410000801086426 0.5099999904632568 0.035999998450279236 1.0190000534057617 0.23000000417232513
5.0 5.0 23.072900772094727 23.0718994140625 5.068600177764893 34.708099365234375 23.692800521850586 0.47600001096725464 3.3559999465942383 0.4699999988079071 0.0 1.0190000534057617 0.22599999606609344
5.5 5.5 23.075199127197266 23.074100494384766 5.067399978637695 34.697200775146484 23.68400001525879 0.8370000123977661 3.3480000495910645 0.4699999988079071 0.0 1.0180000066757202 0.2329999953508377
6.0 6.0 23.067899703979492 23.066699981689453 5.06689977645874 34.69900131225586 23.687400817871094 0.8289999961853027 3.3440001010894775 0.4699999988079071 0.0 1.0369999408721924 0.2329999953508377
6.5 6.5 23.045499801635742 23.044200897216797 5.068699836730957 34.730098724365234 23.71739959716797 0.5659999847412109 3.3440001010894775 0.4699999988079071 0.0 1.0549999475479126 0.2329999953508377
7.0 7.0 22.978300094604492 22.976900100708008 5.073299884796143 34.81890106201172 23.80419921875 0.722000002861023 3.3329999446868896 0.4699999988079071 0.0 1.059000015258789 0.2370000034570694
7.599999904632568 7.5 22.952699661254883 22.951200485229492 5.074399948120117 34.847198486328125 23.83289909362793 0.7919999957084656 3.3369998931884766 0.4699999988079071 0.0 1.0729999542236328 0.23000000417232513
8.100000381469727 8.0 22.927099227905273 22.925500869750977 5.075399875640869 34.8755989074707 23.861799240112305 0.6010000109672546 3.3389999866485596 0.4699999988079071 0.0 1.0720000267028809 0.23399999737739563
8.600000381469727 8.5 22.901500701904297 22.899799346923828 5.076499938964844 34.90399932861328 23.89069938659668 0.5830000042915344 3.321000099182129 0.4699999988079071 0.0 1.0759999752044678 0.24500000476837158
9.100000381469727 9.0 22.89620018005371 22.894399642944336 5.084199905395508 34.96739959716797 23.940399169921875 0.7390000224113464 3.382999897003174 0.4699999988079071 0.0 1.0820000171661377 0.25600001215934753
9.600000381469727 9.5 22.927900314331055 22.926000595092773 5.093900203704834 35.0171012878418 23.968900680541992 0.6970000267028809 3.4719998836517334 0.4699999988079071 0.0 1.1050000190734863 0.24699999392032623
10.100000381469727 10.0 22.93899917602539 22.937000274658203 5.098700046539307 35.0452995300293 23.987199783325195 0.4230000078678131 3.5380001068115234 0.4699999988079071 0.0 1.11899995803833 0.20399999618530273
10.600000381469727 10.5 22.93939971923828 22.93720054626465 5.110000133514404 35.13209915161133 24.052900314331055 0.4650000035762787 3.440000057220459 0.4699999988079071 0.0 1.1339999437332153 0.210999995470047
11.100000381469727 11.0 22.932899475097656 22.930599212646484 5.115499973297119 35.1796989440918 24.090700149536133 0.3409999907016754 3.1480000019073486 0.4699999988079071 0.0 1.1059999465942383 0.20999999344348907
11.600000381469727 11.5 22.92020034790039 22.917800903320312 5.120200157165527 35.226200103759766 24.129600524902344 0.421999990940094 2.8259999752044678 0.4699999988079071 0.0 1.0509999990463257 0.23899999260902405
12.100000381469727 12.0 22.909000396728516 22.9064998626709 5.120100021362305 35.23419952392578 24.138999938964844 0.5789999961853027 2.578000068664551 0.4699999988079071 0.0 1.1540000438690186 0.4169999957084656
12.600000381469727 12.5 22.904499053955078 22.901899337768555 5.119900226593018 35.23630142211914 24.142000198364258 0.4350000023841858 2.49399995803833 0.4699999988079071 0.0 1.1579999923706055 0.6489999890327454
13.100000381469727 13.0 22.903099060058594 22.900400161743164 5.119800090789795 35.23630142211914 24.142499923706055 0.3970000147819519 2.4719998836517334 0.4699999988079071 0.0 1.0839999914169312 0.628000020980835
13.600000381469727 13.5 22.90239906311035 22.899599075317383 5.119699954986572 35.235801696777344 24.142099380493164 0.5979999899864197 2.4519999027252197 0.4699999988079071 0.0 1.0420000553131104 0.7789999842643738
14.100000381469727 14.0 22.90239906311035 22.899499893188477 5.11959981918335 35.234901428222656 24.14150047302246 0.5759999752044678 2.546999931335449 0.4699999988079071 0.0 1.034000039100647 0.8429999947547913
14.600000381469727 14.5 22.897199630737305 22.89419937133789 5.119100093841553 35.23500061035156 24.142900466918945 0.31200000643730164 2.4200000762939453 0.4699999988079071 0.0 1.2510000467300415 0.7480000257492065
15.100000381469727 15.0 22.89590072631836 22.892799377441406 5.11899995803833 35.23529815673828 24.143699645996094 0.3479999899864197 2.36299991607666 0.4699999988079071 0.0 1.090000033378601 0.7870000004768372
15.600000381469727 15.5 22.893800735473633 22.890600204467773 5.11899995803833 35.23640060424805 24.145099639892578 0.37700000405311584 2.371999979019165 0.4699999988079071 0.0 1.0440000295639038 0.8569999933242798

In total, there are 26 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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