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Dataset Title:  "LATEX CTD - d94h099.nc - 28.71N, 94.66W - 1994-05-02" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: latex_d94h099)
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: 45)
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   45 options
    depth ?  =  m   45 options
    temperature ?  =  degree_C   42 options
    potentialTemperature ?  =  degree_C   43 options
    conductivity ?  =  Siemens per meter   43 options
    salinity ?  =  PSU   45 options
    sigmat ?  =  kg m-3   44 options
    descentRate ?  =  meters per second   43 options
    transmission ?  =  percent   39 options
    par ?  =  umol m-2 s-1   2 options
    parv ?  =  volts   4 options
    fluorescence ?  =  volts   40 options
    backscattering ?  =  volts   35 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 22.410400390625 22.409799575805664 4.747399806976318 32.74319839477539 22.39109992980957 0.3779999911785126 4.139999866485596 0.5099999904632568 0.0430000014603138 0.6800000071525574 0.08399999886751175
3.5 3.5 22.3966007232666 22.39590072631836 4.746099948883057 32.74330139160156 22.395099639892578 0.5059999823570251 4.046000003814697 0.4699999988079071 0.007000000216066837 0.6800000071525574 0.07699999958276749
4.0 4.0 22.394100189208984 22.393299102783203 4.748899936676025 32.76639938354492 22.413299560546875 0.47200000286102295 4.006999969482422 0.4699999988079071 0.0010000000474974513 0.6759999990463257 0.08799999952316284
4.5 4.5 22.39550018310547 22.39459991455078 4.74459981918335 32.7322998046875 22.387100219726562 0.5509999990463257 4.017000198364258 0.4699999988079071 0.0 0.6809999942779541 0.07800000160932541
5.0 5.0 22.39430046081543 22.393299102783203 4.749899864196777 32.77349853515625 22.41860008239746 0.3959999978542328 4.044000148773193 0.4699999988079071 0.0 0.6579999923706055 0.07800000160932541
5.5 5.5 22.39389991760254 22.392799377441406 4.75029993057251 32.776798248291016 22.421300888061523 0.5630000233650208 4.136000156402588 0.4699999988079071 0.0 0.6639999747276306 0.07400000095367432
6.0 6.0 22.393800735473633 22.39259910583496 4.750100135803223 32.77560043334961 22.420400619506836 0.41100001335144043 4.132999897003174 0.4699999988079071 0.0 0.6579999923706055 0.06499999761581421
6.5 6.5 22.39430046081543 22.39299964904785 4.750500202178955 32.7775993347168 22.42180061340332 0.25999999046325684 4.113999843597412 0.4699999988079071 0.0 0.6570000052452087 0.07000000029802322
7.0 7.0 22.395599365234375 22.39419937133789 4.750400066375732 32.77629852294922 22.420400619506836 0.35199999809265137 4.182000160217285 0.4699999988079071 0.0 0.6869999766349792 0.07900000363588333
7.599999904632568 7.5 22.39579963684082 22.39430046081543 4.75029993057251 32.775299072265625 22.41950035095215 0.3869999945163727 4.173999786376953 0.4699999988079071 0.0 0.6729999780654907 0.07599999755620956
8.100000381469727 8.0 22.395700454711914 22.394100189208984 4.750500202178955 32.77669906616211 22.420700073242188 0.32499998807907104 4.196000099182129 0.4699999988079071 0.0 0.675000011920929 0.08100000023841858
8.600000381469727 8.5 22.39579963684082 22.394100189208984 4.750699996948242 32.77799987792969 22.421600341796875 0.3240000009536743 4.214000225067139 0.4699999988079071 0.0 0.6650000214576721 0.061000000685453415
9.100000381469727 9.0 22.39550018310547 22.393699645996094 4.751399993896484 32.78350067138672 22.425899505615234 0.5490000247955322 4.229000091552734 0.4699999988079071 0.0 0.6710000038146973 0.07100000232458115
9.600000381469727 9.5 22.39539909362793 22.39349937438965 4.7519001960754395 32.786800384521484 22.42840003967285 0.5889999866485596 4.23799991607666 0.4699999988079071 0.0 0.6589999794960022 0.05400000140070915
10.100000381469727 10.0 22.393400192260742 22.391399383544922 4.754199981689453 32.80619812011719 22.443700790405273 0.4950000047683716 4.242000102996826 0.4699999988079071 0.0 0.675000011920929 0.050999999046325684
10.600000381469727 10.5 22.390499114990234 22.388399124145508 4.7581000328063965 32.838199615478516 22.468900680541992 0.8100000023841858 4.25 0.4699999988079071 0.0 0.6899999976158142 0.05000000074505806
11.100000381469727 11.0 22.38949966430664 22.387300491333008 4.758699893951416 32.84370040893555 22.47330093383789 0.8500000238418579 4.25 0.4699999988079071 0.0 0.699999988079071 0.05000000074505806
11.600000381469727 11.5 22.390600204467773 22.3882999420166 4.7571001052856445 32.830101013183594 22.46269989013672 0.6520000100135803 4.250999927520752 0.4699999988079071 0.0 0.6840000152587891 0.04800000041723251
12.100000381469727 12.0 22.38909912109375 22.386699676513672 4.759799957275391 32.85210037231445 22.479700088500977 0.37700000405311584 4.248000144958496 0.4699999988079071 0.0 0.6890000104904175 0.04699999839067459
12.600000381469727 12.5 22.3882999420166 22.385799407958984 4.761199951171875 32.86330032348633 22.488399505615234 0.5339999794960022 4.252999782562256 0.4699999988079071 0.0 0.6850000023841858 0.04699999839067459
13.100000381469727 13.0 22.38759994506836 22.385000228881836 4.762199878692627 32.87110137939453 22.494600296020508 0.4729999899864197 4.250999927520752 0.4699999988079071 0.0 0.6959999799728394 0.04800000041723251
13.600000381469727 13.5 22.386999130249023 22.384300231933594 4.763599872589111 32.8827018737793 22.50349998474121 0.3019999861717224 4.254000186920166 0.4699999988079071 0.0 0.6899999976158142 0.04600000008940697
14.100000381469727 14.0 22.381799697875977 22.378999710083008 4.769899845123291 32.93539810180664 22.545000076293945 0.3100000023841858 4.250999927520752 0.4699999988079071 0.0 0.6859999895095825 0.04800000041723251
14.600000381469727 14.5 22.372400283813477 22.36949920654297 4.776899814605713 32.99639892578125 22.593900680541992 0.3709999918937683 4.25 0.4699999988079071 0.0 0.6990000009536743 0.04500000178813934
15.100000381469727 15.0 22.332500457763672 22.329500198364258 4.802599906921387 33.22520065307617 22.778600692749023 0.3880000114440918 4.25600004196167 0.4699999988079071 0.0 0.7239999771118164 0.04500000178813934
15.600000381469727 15.5 22.299299240112305 22.296199798583984 4.811399936676025 33.319000244140625 22.859100341796875 0.37700000405311584 4.254000186920166 0.4699999988079071 0.0 1.4490000009536743 0.04800000041723251
16.100000381469727 16.0 22.292699813842773 22.289499282836914 4.814700126647949 33.34939956665039 22.884000778198242 0.3089999854564667 4.263999938964844 0.4699999988079071 0.0 1.0149999856948853 0.04899999871850014
16.600000381469727 16.5 22.24329948425293 22.239999771118164 4.82889986038208 33.49720001220703 23.010000228881836 0.3409999907016754 4.256999969482422 0.4699999988079071 0.0 0.7289999723434448 0.04600000008940697
17.100000381469727 17.0 22.219600677490234 22.21619987487793 4.832300186157227 33.54199981689453 23.05069923400879 0.4399999976158142 4.249000072479248 0.4699999988079071 0.0 0.6650000214576721 0.04699999839067459
17.600000381469727 17.5 22.212600708007812 22.2091007232666 4.833499908447266 33.55690002441406 23.063899993896484 0.4009999930858612 4.243000030517578 0.4699999988079071 0.0 0.656000018119812 0.052000001072883606
18.100000381469727 18.0 22.210100173950195 22.206499099731445 4.834000110626221 33.56230163574219 23.068700790405273 0.3490000069141388 4.242000102996826 0.4699999988079071 0.0 0.6370000243186951 0.05000000074505806
18.600000381469727 18.5 22.1968994140625 22.193199157714844 4.835700035095215 33.58539962768555 23.08989906311035 0.37400001287460327 4.232999801635742 0.4699999988079071 0.0 0.6349999904632568 0.057999998331069946
19.100000381469727 19.0 22.194900512695312 22.191099166870117 4.8368000984191895 33.595401763916016 23.098100662231445 0.34299999475479126 4.204999923706055 0.4699999988079071 0.0 0.621999979019165 0.09000000357627869
19.600000381469727 19.5 22.105300903320312 22.10140037536621 4.842299938201904 33.707401275634766 23.208099365234375 0.2370000034570694 4.086999893188477 0.4699999988079071 0.0 0.5960000157356262 0.03400000184774399
20.100000381469727 20.0 22.01569938659668 22.011699676513672 4.847700119018555 33.819801330566406 23.318500518798828 0.4000000059604645 4.09499979019165 0.4699999988079071 0.0 0.4659999907016754 0.09399999678134918
20.600000381469727 20.5 21.835100173950195 21.831100463867188 4.857100009918213 34.03459930419922 23.53179931640625 0.5730000138282776 4.015999794006348 0.4699999988079071 0.0 0.4300000071525574 0.0989999994635582
21.100000381469727 21.0 21.654499053955078 21.650400161743164 4.866399765014648 34.2510986328125 23.746200561523438 0.597000002861023 3.8359999656677246 0.4699999988079071 0.0 0.414000004529953 0.10300000011920929
21.600000381469727 21.5 21.473899841308594 21.46969985961914 4.875800132751465 34.469200134277344 23.96179962158203 0.3970000147819519 3.808000087738037 0.4699999988079071 0.0 0.4259999990463257 0.11800000071525574
22.100000381469727 22.0 21.29330062866211 21.288999557495117 4.885200023651123 34.688899993896484 24.178600311279297 0.4580000042915344 3.806999921798706 0.4699999988079071 0.0 0.4350000023841858 0.10999999940395355
22.700000762939453 22.5 21.047199249267578 21.04290008544922 4.874100208282471 34.80030059814453 24.330400466918945 0.5879999995231628 3.8369998931884766 0.4699999988079071 0.0 0.42800000309944153 0.1340000033378601
23.200000762939453 23.0 20.78849983215332 20.784099578857422 4.868500232696533 34.96649932861328 24.527099609375 0.47600001096725464 3.8350000381469727 0.4699999988079071 0.0 0.43299999833106995 0.1550000011920929
23.700000762939453 23.5 20.457599639892578 20.45319938659668 4.877600193023682 35.31439971923828 24.881200790405273 0.3440000116825104 3.5840001106262207 0.4699999988079071 0.0 0.45899999141693115 0.1459999978542328
24.200000762939453 24.0 20.342199325561523 20.33769989013672 4.880499839782715 35.434200286865234 25.003400802612305 0.27000001072883606 3.4760000705718994 0.4699999988079071 0.0 0.46799999475479126 0.1509999930858612
24.700000762939453 24.5 20.332700729370117 20.328100204467773 4.88100004196167 35.44649887084961 25.015100479125977 0.3709999918937683 3.441999912261963 0.4699999988079071 0.0 0.4880000054836273 0.19599999487400055
25.200000762939453 25.0 20.319599151611328 20.314899444580078 4.881400108337402 35.459999084472656 25.029199600219727 0.47699999809265137 3.4179999828338623 0.4699999988079071 0.0 0.49000000953674316 0.22100000083446503

In total, there are 45 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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