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ERDDAP > tabledap > Subset ?

Dataset Title:  "NEGOM CTD - n2l04s00.nc - 30.28N, 87.35W - 1998-05-13" Subscribe RSS
Institution:  OCEAN.TAMU   (Dataset ID: negom_n2l04s00)
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: 15)
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   15 options
    depth ?  =  m   15 options
    temperature ?  =  degree_C   15 options
    potentialTemperature ?  =  degree_C   15 options
    conductivity ?  =  Siemens per meter   15 options
    salinity ?  =  PSU   15 options
    sigmat ?  =  kg m-3   15 options
    descentRate ?  =  meters per second   15 options
    transmission ?  =  percent   14 options
    par ?  =  umol m-2 s-1   15 options
    parv ?  =  volts   15 options
    fluorescence ?  =  volts   15 options
    backscattering ?  =  volts   15 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
2.5 2.5 21.776599884033203 21.776100158691406 4.886600017547607 34.31529998779297 23.759899139404297 0.17499999701976776 3.375 699.2999877929688 2.999000072479248 1.6859999895095825 0.7649999856948853
3.0 3.0 21.388900756835938 21.3882999420166 4.875400066375732 34.536399841308594 24.03499984741211 0.30300000309944153 3.385999917984009 583.9000244140625 2.9200000762939453 1.6759999990463257 0.7089999914169312
3.5 3.5 20.925500869750977 20.924800872802734 4.8592000007629395 34.782798767089844 24.348899841308594 0.3149999976158142 3.430000066757202 500.5 2.8519999980926514 1.6779999732971191 0.6650000214576721
4.0 4.0 20.25950050354004 20.258800506591797 4.832300186157227 35.11360168457031 24.779800415039062 0.37400001287460327 3.436000108718872 438.5 2.7950000762939453 1.6820000410079956 0.6600000262260437
4.5 4.5 20.02739906311035 20.026599884033203 4.813399791717529 35.15290069580078 24.871400833129883 0.2770000100135803 3.493000030517578 369.6000061035156 2.7209999561309814 1.725000023841858 0.7390000224113464
5.0 5.0 19.865400314331055 19.864500045776367 4.802199840545654 35.19599914550781 24.94700050354004 0.2329999953508377 3.4240000247955322 315.79998779296875 2.6530001163482666 1.871000051498413 0.8180000185966492
5.5 5.5 19.742700576782227 19.74169921875 4.792900085449219 35.22209930419922 24.999099731445312 0.26499998569488525 3.447999954223633 261.79998779296875 2.569999933242798 1.9470000267028809 0.6380000114440918
6.0 6.0 19.65679931640625 19.65570068359375 4.786200046539307 35.23910140991211 25.034500122070312 0.20499999821186066 3.493000030517578 217.3000030517578 2.490999937057495 1.9329999685287476 0.578000009059906
6.5 6.5 19.578899383544922 19.577699661254883 4.780600070953369 35.2588005065918 25.069900512695312 0.18799999356269836 3.5850000381469727 179.0 2.4059998989105225 1.8919999599456787 0.550000011920929
7.0 7.0 19.506799697875977 19.50550079345703 4.776299953460693 35.283599853515625 25.10770034790039 0.1860000044107437 3.7139999866485596 148.1999969482422 2.322999954223633 1.8270000219345093 0.5220000147819519
7.599999904632568 7.5 19.452800750732422 19.451400756835938 4.774400234222412 35.31340026855469 25.144399642944336 0.19599999487400055 3.7850000858306885 123.5 2.24399995803833 1.781999945640564 0.42800000309944153
8.100000381469727 8.0 19.441200256347656 19.439699172973633 4.773900032043457 35.31840133666992 25.15130043029785 0.18700000643730164 3.7899999618530273 100.19999694824219 2.1540000438690186 1.8049999475479126 0.3630000054836273
8.600000381469727 8.5 19.43869972229004 19.43720054626465 4.77370023727417 35.31880187988281 25.152299880981445 0.20999999344348907 3.805000066757202 83.66000366210938 2.0759999752044678 1.8329999446868896 0.35600000619888306
9.100000381469727 9.0 19.436599731445312 19.434999465942383 4.773600101470947 35.31999969482422 25.153799057006836 0.19699999690055847 3.7950000762939453 72.83000183105469 2.015000104904175 1.8559999465942383 0.36800000071525574
9.600000381469727 9.5 19.43899917602539 19.437299728393555 4.773799896240234 35.31949996948242 25.152799606323242 -0.07400000095367432 3.746000051498413 59.220001220703125 1.930999994277954 1.8650000095367432 0.5899999737739563

In total, there are 15 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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