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Dataset Title:  "LATEX CTD - d93g048.nc - 28.88N, 90.51W - 1993-11-10" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: latex_d93g048)
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: 28)
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   28 options
    depth ?  =  m   28 options
    temperature ?  =  degree_C   28 options
    potentialTemperature ?  =  degree_C   28 options
    conductivity ?  =  Siemens per meter   25 options
    salinity ?  =  PSU   25 options
    sigmat ?  =  kg m-3   27 options
    descentRate ?  =  meters per second   28 options
    transmission ?  =  percent   27 options
    par ?  =  umol m-2 s-1   2 options
    parv ?  =  volts   3 options
    fluorescence ?  =  volts   26 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 21.781700134277344 21.781400680541992 4.490600109100342 31.216699600219727 21.40730094909668 0.37299999594688416 2.687000036239624 0.6299999952316284 0.09099999815225601 2.072999954223633 -9.0
4.0 4.0 21.78339958190918 21.783000946044922 4.490799903869629 31.217300415039062 21.40730094909668 0.4830000102519989 2.6410000324249268 0.5099999904632568 -9.0 2.1019999980926514 -9.0
4.5 4.5 21.785999298095703 21.785499572753906 4.491099834442139 31.21769905090332 21.406999588012695 0.6480000019073486 2.683000087738037 0.5099999904632568 0.0 2.130000114440918 -9.0
5.0 5.0 21.785900115966797 21.78529930114746 4.491099834442139 31.217599868774414 21.40690040588379 0.49000000953674316 2.684999942779541 0.5099999904632568 0.0 2.130000114440918 -9.0
5.5 5.5 21.78499984741211 21.784299850463867 4.491099834442139 31.217599868774414 21.407100677490234 0.4099999964237213 2.696000099182129 0.5099999904632568 0.0 2.0840001106262207 -9.0
6.0 6.0 21.782699584960938 21.78190040588379 4.490900039672852 31.217599868774414 21.407800674438477 0.5799999833106995 2.7179999351501465 0.5099999904632568 0.0 2.0439999103546143 -9.0
6.5 6.5 21.780500411987305 21.779600143432617 4.490600109100342 31.217300415039062 21.408300399780273 0.5979999899864197 2.690000057220459 0.5099999904632568 0.0 2.052999973297119 -9.0
7.0 7.0 21.775999069213867 21.774999618530273 4.490200042724609 31.216999053955078 21.409299850463867 0.41600000858306885 2.688999891281128 0.5099999904632568 0.0 2.052999973297119 -9.0
7.5 7.5 21.791799545288086 21.790700912475586 4.493500232696533 31.23080062866211 21.4153995513916 0.34299999475479126 2.693000078201294 0.5099999904632568 0.0 2.0299999713897705 -9.0
8.0 8.0 21.804500579833984 21.80340003967285 4.49560022354126 31.238300323486328 21.417699813842773 0.4959999918937683 2.7039999961853027 0.5099999904632568 0.0 2.059000015258789 -9.0
8.5 8.5 21.808000564575195 21.806699752807617 4.493599891662598 31.21969985961914 21.402599334716797 0.6499999761581421 2.691999912261963 0.5099999904632568 0.0 2.059999942779541 -9.0
9.0 9.0 21.79949951171875 21.798200607299805 4.4944000244140625 31.232200622558594 21.414400100708008 0.6919999718666077 2.7160000801086426 0.5099999904632568 0.0 2.128999948501587 -9.0
9.600000381469727 9.5 21.795400619506836 21.79400062561035 4.493299961090088 31.225900650024414 21.41080093383789 0.5249999761581421 2.7269999980926514 0.5099999904632568 0.0 2.180999994277954 -9.0
10.100000381469727 10.0 21.802900314331055 21.801300048828125 4.4953999519348145 31.23699951171875 21.417200088500977 0.40299999713897705 2.7209999561309814 0.5099999904632568 0.0 2.140000104904175 -9.0
10.600000381469727 10.5 21.80900001525879 21.80739974975586 4.496500015258789 31.241300582885742 21.418800354003906 0.6650000214576721 2.753000020980835 0.5099999904632568 0.0 2.0820000171661377 -9.0
11.100000381469727 11.0 21.809999465942383 21.80820083618164 4.496699810028076 31.242000579833984 21.419200897216797 0.7979999780654907 2.7209999561309814 0.5099999904632568 0.0 2.071000099182129 -9.0
11.600000381469727 11.5 21.817699432373047 21.815900802612305 4.498600006103516 31.250699996948242 21.4237003326416 0.7739999890327454 2.7279999256134033 0.5099999904632568 0.0 2.119999885559082 -9.0
12.100000381469727 12.0 21.824899673461914 21.822999954223633 4.50029993057251 31.25860023498535 21.42770004272461 0.5360000133514404 2.7709999084472656 0.5099999904632568 0.0 2.13700008392334 -9.0
12.600000381469727 12.5 21.83169937133789 21.829700469970703 4.502299785614014 31.26930046081543 21.43400001525879 0.41200000047683716 2.760999917984009 0.5099999904632568 0.0 2.177999973297119 -9.0
13.100000381469727 13.0 21.849300384521484 21.847200393676758 4.507199764251709 31.293899536132812 21.447900772094727 0.6359999775886536 2.7839999198913574 0.5099999904632568 0.0 2.177000045776367 -9.0
13.600000381469727 13.5 21.87649917602539 21.874300003051758 4.515600204467773 31.339500427246094 21.475000381469727 0.6830000281333923 2.73799991607666 0.5099999904632568 0.0 2.1740000247955322 -9.0
14.100000381469727 14.0 21.969999313354492 21.967599868774414 4.5447001457214355 31.497299194335938 21.56920051574707 0.5400000214576721 2.6740000247955322 0.5099999904632568 0.0 2.1619999408721924 -9.0
14.600000381469727 14.5 22.02989959716797 22.02739906311035 4.563499927520752 31.598800659179688 21.62969970703125 0.3490000069141388 2.6619999408721924 0.5099999904632568 0.0 2.1500000953674316 -9.0
15.100000381469727 15.0 22.059099197387695 22.05660057067871 4.57420015335083 31.660200119018555 21.66819953918457 0.3959999978542328 2.571000099182129 0.5099999904632568 0.0 2.174999952316284 -9.0
15.600000381469727 15.5 22.135900497436523 22.13319969177246 4.600900173187256 31.810400009155273 21.76099967956543 0.4519999921321869 2.5350000858306885 0.5099999904632568 0.0 2.2249999046325684 -9.0
16.100000381469727 16.0 22.176300048828125 22.173599243164062 4.614999771118164 31.890300750732422 21.810400009155273 0.41999998688697815 2.5409998893737793 0.5099999904632568 0.0 2.2290000915527344 -9.0
16.600000381469727 16.5 22.192699432373047 22.189800262451172 4.620800018310547 31.922700881958008 21.830400466918945 0.3140000104904175 2.1689999103546143 0.5099999904632568 0.0 2.312000036239624 -9.0
17.100000381469727 17.0 22.202800750732422 22.199800491333008 4.624899864196777 31.946500778198242 21.845699310302734 0.46399998664855957 1.74399995803833 0.5099999904632568 0.0 2.319000005722046 -9.0

In total, there are 28 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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