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Dataset Title:  "NEGOM CTD - n5l03s01.nc - 30.1N, 88.07W - 1999-05-26" Subscribe RSS
Institution:  OCEAN.TAMU   (Dataset ID: negom_n5l03s01)
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: 34)
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   34 options
    depth ?  =  m   34 options
    temperature ?  =  degree_C   34 options
    potentialTemperature ?  =  degree_C   33 options
    conductivity ?  =  Siemens per meter   32 options
    salinity ?  =  PSU   34 options
    sigmat ?  =  kg m-3   34 options
    descentRate ?  =  meters per second   34 options
    transmission ?  =  percent   31 options
    par ?  =  umol m-2 s-1   34 options
    parv ?  =  volts   34 options
    fluorescence ?  =  volts   32 options
    backscattering ?  =  volts   28 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 27.172100067138672 27.171499252319336 4.502099990844727 27.767799377441406 17.227800369262695 -0.03400000184774399 3.984999895095825 356.8999938964844 2.1619999408721924 1.6169999837875366 0.7369999885559082
3.0 3.0 27.16950035095215 27.168800354003906 4.502099990844727 27.76930046081543 17.229799270629883 0.32499998807907104 3.989000082015991 311.8999938964844 2.1029999256134033 1.6169999837875366 0.7300000190734863
3.5 3.5 27.169099807739258 27.16830062866211 4.502200126647949 27.770200729370117 17.230600357055664 0.22699999809265137 3.994999885559082 249.10000610351562 2.00600004196167 1.63100004196167 0.7160000205039978
4.0 4.0 27.169200897216797 27.16830062866211 4.502299785614014 27.77090072631836 17.23110008239746 0.5239999890327454 3.993000030517578 208.39999389648438 1.9270000457763672 1.6549999713897705 0.7229999899864197
4.5 4.5 27.160999298095703 27.15999984741211 4.504300117492676 27.7893009185791 17.247499465942383 0.5509999990463257 3.9709999561309814 181.0 1.8669999837875366 1.652999997138977 0.7110000252723694
5.0 5.0 27.158100128173828 27.156999588012695 4.504899978637695 27.7947998046875 17.252599716186523 0.3149999976158142 3.9800000190734863 148.0 1.777999997138977 1.649999976158142 0.7120000123977661
5.5 5.5 27.149799346923828 27.14859962463379 4.507999897003174 27.821199417114258 17.274999618530273 0.31700000166893005 3.9649999141693115 125.80000305175781 1.7089999914169312 1.6790000200271606 0.7289999723434448
6.099999904632568 6.0 27.12529945373535 27.123899459838867 4.519800186157227 27.916500091552734 17.35420036315918 0.4259999990463257 3.9719998836517334 110.5 1.6510000228881836 1.7200000286102295 0.7379999756813049
6.599999904632568 6.5 27.087900161743164 27.08639907836914 4.540999889373779 28.0851993560791 17.492399215698242 0.36800000071525574 4.013999938964844 94.75 1.5850000381469727 1.7259999513626099 0.7089999914169312
7.099999904632568 7.0 26.966999053955078 26.96540069580078 4.601099967956543 28.57390022277832 17.896900177001953 0.3779999911785126 4.014999866485596 81.54000091552734 1.5199999809265137 1.6699999570846558 0.7239999771118164
7.599999904632568 7.5 26.78730010986328 26.785600662231445 4.68779993057251 29.288700103759766 18.489500045776367 0.34700000286102295 4.013000011444092 72.22000122070312 1.4670000076293945 1.6649999618530273 0.7210000157356262
8.100000381469727 8.0 26.077899932861328 26.076099395751953 4.867700099945068 31.020299911499023 20.010799407958984 0.2750000059604645 3.999000072479248 64.7300033569336 1.4199999570846558 1.5839999914169312 0.7289999723434448
8.600000381469727 8.5 25.43779945373535 25.43589973449707 4.956299781799316 32.098899841308594 21.018800735473633 0.3700000047683716 4.072999954223633 59.08000183105469 1.3799999952316284 1.5260000228881836 0.7300000190734863
9.100000381469727 9.0 25.225500106811523 25.223499298095703 5.000899791717529 32.574798583984375 21.442100524902344 0.42500001192092896 4.083000183105469 54.84000015258789 1.3480000495910645 1.5130000114440918 0.7260000109672546
9.600000381469727 9.5 25.016799926757812 25.014699935913086 5.018400192260742 32.85319900512695 21.715299606323242 0.3490000069141388 4.067999839782715 50.900001525878906 1.315000057220459 1.5299999713897705 0.7229999899864197
10.100000381469727 10.0 24.332300186157227 24.3302001953125 4.97760009765625 33.052101135253906 22.070100784301758 0.23399999737739563 4.051000118255615 48.83000183105469 1.2979999780654907 1.5740000009536743 0.7369999885559082
10.600000381469727 10.5 23.87339973449707 23.871200561523438 4.970799922943115 33.34199905395508 22.42449951171875 0.4300000071525574 4.078999996185303 46.130001068115234 1.2730000019073486 1.5800000429153442 0.7390000224113464
11.100000381469727 11.0 23.69849967956543 23.696199417114258 5.002900123596191 33.71649932861328 22.75909996032715 0.4580000042915344 4.10099983215332 42.939998626708984 1.2419999837875366 1.5839999914169312 0.7429999709129333
11.600000381469727 11.5 23.512699127197266 23.510299682617188 5.011600017547607 33.92399978637695 22.970300674438477 0.33799999952316284 4.086999893188477 39.31999969482422 1.2029999494552612 1.6130000352859497 0.7400000095367432
12.100000381469727 12.0 23.179399490356445 23.17690086364746 5.014599800109863 34.20389938354492 23.27899932861328 0.3050000071525574 4.086999893188477 36.119998931884766 1.1670000553131104 1.6670000553131104 0.7379999756813049
12.600000381469727 12.5 22.93000030517578 22.927400588989258 5.017099857330322 34.41749954223633 23.512699127197266 0.31200000643730164 4.079999923706055 34.72999954223633 1.149999976158142 1.7070000171661377 0.7279999852180481
13.100000381469727 13.0 22.71739959716797 22.714799880981445 5.029399871826172 34.68000030517578 23.7726993560791 0.3370000123977661 4.031000137329102 32.45000076293945 1.1200000047683716 1.7380000352859497 0.718999981880188
13.600000381469727 13.5 22.423599243164062 22.420900344848633 5.048099994659424 35.06050109863281 24.145200729370117 0.3319999873638153 4.0229997634887695 30.420000076293945 1.0920000076293945 1.815000057220459 0.7379999756813049
14.100000381469727 14.0 22.113000869750977 22.110200881958008 5.055200099945068 35.367801666259766 24.466400146484375 0.18000000715255737 4.039999961853027 29.90999984741211 1.0850000381469727 1.7660000324249268 0.7620000243186951
14.600000381469727 14.5 21.876399993896484 21.87350082397461 5.061200141906738 35.60850143432617 24.715700149536133 0.32199999690055847 3.999000072479248 28.809999465942383 1.0679999589920044 1.7450000047683716 0.7749999761581421
15.100000381469727 15.0 21.659500122070312 21.6564998626709 5.060299873352051 35.78070068359375 24.90730094909668 0.24500000476837158 4.043000221252441 26.530000686645508 1.0329999923706055 1.725000023841858 0.8069999814033508
15.600000381469727 15.5 21.5132999420166 21.510299682617188 5.059199810028076 35.89390182495117 25.034099578857422 0.1979999989271164 4.078999996185303 26.360000610351562 1.0299999713897705 1.684999942779541 0.8130000233650208
16.100000381469727 16.0 21.489299774169922 21.4862003326416 5.058700084686279 35.91019821166992 25.053199768066406 0.24400000274181366 4.065000057220459 24.0 0.9890000224113464 1.6690000295639038 0.7990000247955322
16.600000381469727 16.5 21.459999084472656 21.45680046081543 5.057600021362305 35.92559814453125 25.072999954223633 0.16099999845027924 4.019999980926514 23.18000030517578 0.9739999771118164 1.659000039100647 0.8109999895095825
17.100000381469727 17.0 21.42889976501465 21.425600051879883 5.056399822235107 35.941898345947266 25.094100952148438 0.1599999964237213 3.9590001106262207 22.09000015258789 0.953000009059906 1.6619999408721924 0.8349999785423279
17.600000381469727 17.5 21.422199249267578 21.418800354003906 5.056099891662598 35.945098876953125 25.098499298095703 0.1340000033378601 3.9200000762939453 20.600000381469727 0.9229999780654907 1.6679999828338623 0.8809999823570251
18.100000381469727 18.0 21.420799255371094 21.417299270629883 5.056099891662598 35.945899963378906 25.09939956665039 0.15600000321865082 3.9079999923706055 19.110000610351562 0.8899999856948853 1.6799999475479126 0.9269999861717224
18.600000381469727 18.5 21.416799545288086 21.41320037841797 5.0559000968933105 35.947200775146484 25.101600646972656 0.1809999942779541 3.872999906539917 17.68000030517578 0.8569999933242798 1.6399999856948853 0.9570000171661377
19.100000381469727 19.0 21.4153995513916 21.411699295043945 5.055500030517578 35.94540023803711 25.10059928894043 0.00800000037997961 3.864000082015991 18.139999389648438 0.8679999709129333 1.6540000438690186 0.9729999899864197

In total, there are 34 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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