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Dataset Title:  "NEGOM CTD - n8l07s00.nc - 29.74N, 85.43W - 2000-04-20" Subscribe RSS
Institution:  OCEAN.TAMU   (Dataset ID: negom_n8l07s00)
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: 16)
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   16 options
    depth ?  =  m   16 options
    temperature ?  =  degree_C   16 options
    potentialTemperature ?  =  degree_C   16 options
    conductivity ?  =  Siemens per meter   16 options
    salinity ?  =  PSU   16 options
    sigmat ?  =  kg m-3   16 options
    descentRate ?  =  meters per second   16 options
    transmission ?  =  percent   15 options
    par ?  =  umol m-2 s-1   16 options
    parv ?  =  volts   16 options
    fluorescence ?  =  volts   16 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
1.5 1.5 21.410400390625 21.41010093688965 4.945799827575684 35.080299377441406 24.442800521850586 0.09200000017881393 4.007999897003174 2840.0 3.0759999752044678 1.159999966621399 -9.0
2.0 2.0 21.414100646972656 21.413700103759766 4.946400165557861 35.08169937133789 24.442899703979492 0.1509999930858612 4.001999855041504 710.2999877929688 2.4649999141693115 1.1829999685287476 0.032999999821186066
2.5 2.5 21.417200088500977 21.41670036315918 4.947000026702881 35.083499908447266 24.44339942932129 0.2529999911785126 4.002999782562256 635.2999877929688 2.4079999923706055 1.190000057220459 0.16699999570846558
3.0 3.0 21.418699264526367 21.418100357055664 4.947299957275391 35.08430099487305 24.443599700927734 0.2150000035762787 4.0 541.2000122070312 2.3369998931884766 1.194000005722046 0.28600001335144043
3.5 3.5 21.420799255371094 21.42020034790039 4.948500156402588 35.092498779296875 24.44930076599121 0.20499999821186066 4.005000114440918 455.0 2.260999917984009 1.1970000267028809 0.30799999833106995
4.0 4.0 21.42449951171875 21.4237003326416 4.9506001472473145 35.10599899291992 24.458599090576172 0.20999999344348907 4.004000186920166 420.0 2.2279999256134033 1.2209999561309814 0.3140000104904175
4.5 4.5 21.41390037536621 21.41309928894043 4.955900192260742 35.15650177001953 24.5 0.164000004529953 4.005000114440918 353.1000061035156 2.1559998989105225 1.2330000400543213 0.3140000104904175
5.0 5.0 21.30470085144043 21.303699493408203 4.962600231170654 35.299400329589844 24.6387996673584 0.2409999966621399 4.060999870300293 310.79998779296875 2.0999999046325684 1.2400000095367432 0.30300000309944153
5.5 5.5 21.18790054321289 21.186800003051758 4.968800067901611 35.445701599121094 24.782100677490234 0.19499999284744263 4.11299991607666 262.3999938964844 2.0280001163482666 1.2130000591278076 0.2879999876022339
6.0 6.0 21.107200622558594 21.106000900268555 4.976900100708008 35.57749938964844 24.904699325561523 0.20000000298023224 4.177000045776367 233.60000610351562 1.9769999980926514 1.184999942779541 0.2720000147819519
6.5 6.5 21.08799934387207 21.08679962158203 4.974699974060059 35.57590103149414 24.908700942993164 0.21400000154972076 4.184999942779541 208.10000610351562 1.9270000457763672 1.1540000438690186 0.22300000488758087
7.0 7.0 21.0669002532959 21.065500259399414 4.9730000495910645 35.57899856567383 24.916900634765625 0.1550000011920929 4.159999847412109 179.8000030517578 1.8639999628067017 1.1490000486373901 0.21899999678134918
7.599999904632568 7.5 21.05109977722168 21.04960060119629 4.972400188446045 35.587799072265625 24.927900314331055 0.23899999260902405 4.129000186920166 165.60000610351562 1.8279999494552612 1.1759999990463257 0.20200000703334808
8.100000381469727 8.0 21.048500061035156 21.046899795532227 4.972799777984619 35.59260177612305 24.93239974975586 0.1589999943971634 4.111000061035156 147.1999969482422 1.7769999504089355 1.2089999914169312 0.2240000069141388
8.600000381469727 8.5 21.05579948425293 21.054100036621094 4.974800109863281 35.602298736572266 24.937700271606445 0.17900000512599945 4.078999996185303 136.10000610351562 1.7430000305175781 1.246999979019165 0.23800000548362732
9.100000381469727 9.0 21.070100784301758 21.06839942932129 4.977200031280518 35.609798431396484 24.93950080871582 0.1599999964237213 4.058000087738037 126.5999984741211 1.7120000123977661 1.2690000534057617 0.25699999928474426

In total, there are 16 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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