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Dataset Title:  "LATEX CTD - d92c026.nc - 29.41N, 94.0W - 1992-11-07" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: latex_d92c026)
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: 7)
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   7 options
    depth ?  =  m   7 options
    temperature ?  =  degree_C   7 options
    potentialTemperature ?  =  degree_C   7 options
    conductivity ?  =  Siemens per meter   6 options
    salinity ?  =  PSU   7 options
    sigmat ?  =  kg m-3   6 options
    descentRate ?  =  meters per second   7 options
    transmission ?  =  percent   7 options
    par ?  =  umol m-2 s-1   5 options
    parv ?  =  volts   6 options
    fluorescence ?  =  volts   7 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
3.5 3.5 19.831899642944336 19.831300735473633 3.992300033569336 28.65999984741211 19.9773006439209 0.38600000739097595 3.371000051498413 0.38999998569488525 0.6230000257492065 1.5119999647140503 -9.0
4.0 4.0 19.837600708007812 19.83690071105957 3.9918999671936035 28.652099609375 19.969900131225586 0.14000000059604645 3.3580000400543213 0.28999999165534973 0.48899999260902405 1.6490000486373901 -9.0
4.5 4.5 19.83679962158203 19.836000442504883 3.993000030517578 28.661800384521484 19.977500915527344 0.5799999833106995 3.3269999027252197 0.2199999988079071 0.36800000071525574 1.7000000476837158 -9.0
5.0 5.0 19.834199905395508 19.83329963684082 3.9928998947143555 28.662700653076172 19.978900909423828 0.15399999916553497 3.3259999752044678 0.10999999940395355 0.06199999898672104 1.6360000371932983 -9.0
5.5 5.5 19.831499099731445 19.83049964904785 3.9928998947143555 28.66390037536621 19.980499267578125 0.09099999815225601 3.3399999141693115 0.09000000357627869 -9.0 1.465000033378601 -9.0
6.0 6.0 19.82900047302246 19.827899932861328 3.9925999641418457 28.66360092163086 19.980899810791016 0.11599999666213989 3.3320000171661377 0.09000000357627869 0.0 1.3890000581741333 -9.0
6.5 6.5 19.829599380493164 19.828399658203125 3.9923999309539795 28.660999298095703 19.978900909423828 0.07699999958276749 3.3459999561309814 0.09000000357627869 0.0 1.7039999961853027 -9.0

In total, there are 7 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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