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Dataset Title:  "LATEX CTD - d93d017.nc - 28.97N, 94.0W - 1993-02-06" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: latex_d93d017)
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   26 options
    potentialTemperature ?  =  degree_C   26 options
    conductivity ?  =  Siemens per meter   26 options
    salinity ?  =  PSU   26 options
    sigmat ?  =  kg m-3   26 options
    descentRate ?  =  meters per second   26 options
    transmission ?  =  percent   23 options
    par ?  =  umol m-2 s-1   22 options
    parv ?  =  volts   23 options
    fluorescence ?  =  volts   23 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
3.0 3.0 17.17340087890625 17.17300033569336 4.237100124359131 32.665199279785156 23.683500289916992 -0.08500000089406967 3.9769999980926514 2.190000057220459 1.371000051498413 0.4180000126361847 -9.0
3.5 3.5 17.152799606323242 17.15220069885254 4.232999801635742 32.64609909057617 23.6737003326416 0.19599999487400055 3.9560000896453857 1.8899999856948853 1.3070000410079956 0.4620000123977661 -9.0
4.0 4.0 17.159400939941406 17.158700942993164 4.234099864959717 32.65079879760742 23.67569923400879 0.23600000143051147 3.9590001106262207 1.4700000286102295 1.1970000267028809 0.47999998927116394 -9.0
4.5 4.5 17.16010093688965 17.159400939941406 4.234399795532227 32.65190124511719 23.67650032043457 0.4519999921321869 3.9649999141693115 1.2200000286102295 1.1169999837875366 0.5049999952316284 -9.0
5.0 5.0 17.162500381469727 17.16160011291504 4.234899997711182 32.654300689697266 23.67770004272461 0.335999995470047 3.9619998931884766 0.949999988079071 1.0099999904632568 0.46700000762939453 -9.0
5.5 5.5 17.168100357055664 17.167200088500977 4.236199855804443 32.66120147705078 23.681699752807617 0.1459999978542328 3.9579999446868896 0.8199999928474426 0.9419999718666077 0.43700000643730164 -9.0
6.0 6.0 17.166000366210938 17.165000915527344 4.2357001304626465 32.65840148925781 23.680099487304688 0.3580000102519989 3.9690001010894775 0.6800000071525574 0.8619999885559082 0.4399999976158142 -9.0
6.5 6.5 17.16320037841797 17.162200927734375 4.235099792480469 32.65530014038086 23.67840003967285 0.4790000021457672 3.9649999141693115 0.5899999737739563 0.7979999780654907 0.4519999921321869 -9.0
7.0 7.0 17.165700912475586 17.164600372314453 4.235799789428711 32.659000396728516 23.680599212646484 0.27399998903274536 3.9660000801086426 0.5199999809265137 0.746999979019165 0.4490000009536743 -9.0
7.599999904632568 7.5 17.17569923400879 17.17449951171875 4.23859977722168 32.67470169067383 23.69029998779297 0.3790000081062317 3.9660000801086426 0.4399999976158142 0.6710000038146973 0.4519999921321869 -9.0
8.100000381469727 8.0 17.191099166870117 17.189800262451172 4.242300033569336 32.693599700927734 23.701200485229492 0.5009999871253967 3.9709999561309814 0.3700000047683716 0.5979999899864197 0.4580000042915344 -9.0
8.600000381469727 8.5 17.192899703979492 17.191499710083008 4.243100166320801 32.69889831542969 23.70490074157715 0.3799999952316284 3.9769999980926514 0.3100000023841858 0.5289999842643738 0.46000000834465027 -9.0
9.100000381469727 9.0 17.195999145507812 17.194499969482422 4.243800163269043 32.702701568603516 23.707000732421875 0.28299999237060547 3.9790000915527344 0.2800000011920929 0.4819999933242798 0.4390000104904175 -9.0
9.600000381469727 9.5 17.24340057373047 17.241899490356445 4.257500171661377 32.78150177001953 23.75629997253418 0.5149999856948853 3.994999885559082 0.25 0.4230000078678131 0.4359999895095825 -9.0
10.100000381469727 10.0 17.275800704956055 17.274099349975586 4.26639986038208 32.83169937133789 23.787099838256836 0.45500001311302185 3.992000102996826 0.20999999344348907 0.3610000014305115 0.460999995470047 -9.0
10.600000381469727 10.5 17.288700103759766 17.28700065612793 4.270400047302246 32.85580062866211 23.802600860595703 0.23199999332427979 3.999000072479248 0.1899999976158142 0.3100000023841858 0.46700000762939453 -9.0
11.100000381469727 11.0 17.31679916381836 17.315000534057617 4.280200004577637 32.91669845581055 23.842599868774414 0.49399998784065247 3.984999895095825 0.17000000178813934 0.24799999594688416 0.46399998664855957 -9.0
11.600000381469727 11.5 17.459699630737305 17.457799911499023 4.3282999992370605 33.212799072265625 24.035499572753906 0.5220000147819519 4.014999866485596 0.14000000059604645 0.1850000023841858 0.45500001311302185 -9.0
12.100000381469727 12.0 17.656600952148438 17.654499053955078 4.399400234222412 33.65950012207031 24.33049964904785 0.3449999988079071 4.072000026702881 0.12999999523162842 0.13300000131130219 0.4659999907016754 -9.0
12.600000381469727 12.5 17.789100646972656 17.78689956665039 4.451700210571289 33.996299743652344 24.556499481201172 0.2680000066757202 4.057000160217285 0.11999999731779099 0.0949999988079071 0.5049999952316284 -9.0
13.100000381469727 13.0 17.875099182128906 17.872800827026367 4.48360013961792 34.1974983215332 24.689599990844727 0.5099999904632568 4.119999885559082 0.10000000149011612 0.024000000208616257 0.5600000023841858 -9.0
13.600000381469727 13.5 17.9330997467041 17.93079948425293 4.502500057220459 34.30970001220703 24.76140022277832 0.4300000071525574 4.130000114440918 0.09000000357627869 0.0010000000474974513 0.5609999895095825 -9.0
14.100000381469727 14.0 17.940799713134766 17.938400268554688 4.504499912261963 34.31990051269531 24.76740074157715 0.2280000001192093 4.126999855041504 0.09000000357627869 0.0 0.546999990940094 -9.0
14.600000381469727 14.5 18.01140022277832 18.008899688720703 4.521699905395508 34.40650177001953 24.8164005279541 0.5910000205039978 4.156000137329102 0.09000000357627869 0.0 0.6510000228881836 -9.0
15.100000381469727 15.0 18.041000366210938 18.038400650024414 4.527200222015381 34.4286994934082 24.826099395751953 0.5580000281333923 4.175000190734863 0.09000000357627869 0.0 0.5950000286102295 -9.0
15.600000381469727 15.5 18.055500030517578 18.052900314331055 4.53000020980835 34.440399169921875 24.831600189208984 0.1420000046491623 4.1579999923706055 0.09000000357627869 0.0 0.5070000290870667 -9.0

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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