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Dataset Title:  "LATEX CTD - d93g148.nc - 29.08N, 94.77W - 1993-11-15" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: latex_d93g148)
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   27 options
    potentialTemperature ?  =  degree_C   27 options
    conductivity ?  =  Siemens per meter   26 options
    salinity ?  =  PSU   28 options
    sigmat ?  =  kg m-3   28 options
    descentRate ?  =  meters per second   28 options
    transmission ?  =  percent   27 options
    par ?  =  umol m-2 s-1   3 options
    parv ?  =  volts   4 options
    fluorescence ?  =  volts   23 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
2.5 2.5 19.870500564575195 19.870399475097656 4.372399806976318 31.690000534057617 22.273700714111328 0.5960000157356262 1.996999979019165 0.5299999713897705 0.008999999612569809 1.9040000438690186 -9.0
3.0 3.0 19.8710994720459 19.870899200439453 4.373499870300293 31.697999954223633 22.279600143432617 0.5849999785423279 2.0390000343322754 0.5299999713897705 0.014999999664723873 1.906000018119812 -9.0
3.5 3.5 19.871200561523438 19.870899200439453 4.372600078582764 31.690399169921875 22.273799896240234 0.3970000147819519 2.062000036239624 0.5199999809265137 0.0010000000474974513 1.8899999856948853 -9.0
4.0 4.0 19.871000289916992 19.8705997467041 4.371600151062012 31.682600021362305 22.26799964904785 0.4129999876022339 2.075000047683716 0.5099999904632568 0.0 1.8760000467300415 -9.0
4.5 4.5 19.872800827026367 19.872400283813477 4.373300075531006 31.694400787353516 22.276500701904297 0.4169999957084656 2.0759999752044678 0.5099999904632568 0.0 1.8760000467300415 -9.0
5.0 5.0 19.871700286865234 19.8710994720459 4.372399806976318 31.687999725341797 22.27199935913086 0.49000000953674316 2.0789999961853027 0.5099999904632568 0.0 1.9010000228881836 -9.0
5.5 5.5 19.875200271606445 19.87459945678711 4.376399993896484 31.716999053955078 22.29319953918457 0.6639999747276306 2.075000047683716 0.5099999904632568 0.0 1.8849999904632568 -9.0
6.0 6.0 19.880800247192383 19.88010025024414 4.381700038909912 31.755599975585938 22.321199417114258 0.7390000224113464 2.066999912261963 0.5099999904632568 0.0 1.8849999904632568 -9.0
6.5 6.5 19.882200241088867 19.881399154663086 4.384300231933594 31.775800704956055 22.336200714111328 0.6700000166893005 2.0810000896453857 0.5099999904632568 0.0 1.8919999599456787 -9.0
7.0 7.0 19.882200241088867 19.88129997253418 4.387599945068359 31.802499771118164 22.356599807739258 0.41100001335144043 2.109999895095825 0.5099999904632568 0.0 1.9320000410079956 -9.0
7.5 7.5 19.88129997253418 19.880300521850586 4.388299942016602 31.808500289916992 22.361400604248047 0.4269999861717224 2.0920000076293945 0.5099999904632568 0.0 1.9359999895095825 -9.0
8.0 8.0 19.880300521850586 19.879199981689453 4.388599872589111 31.811800003051758 22.364200592041016 0.6959999799728394 2.118000030517578 0.5099999904632568 0.0 1.9500000476837158 -9.0
8.5 8.5 19.88089942932129 19.87969970703125 4.388500213623047 31.809999465942383 22.362699508666992 0.8209999799728394 2.0959999561309814 0.5099999904632568 0.0 1.9479999542236328 -9.0
9.0 9.0 19.871999740600586 19.870800018310547 4.388999938964844 31.82069969177246 22.37310028076172 0.8090000152587891 2.0940001010894775 0.5099999904632568 0.0 1.940999984741211 -9.0
9.600000381469727 9.5 19.852500915527344 19.85110092163086 4.388800144195557 31.833999633789062 22.388399124145508 0.6380000114440918 2.0329999923706055 0.5099999904632568 0.0 1.9520000219345093 -9.0
10.100000381469727 10.0 19.842599868774414 19.84119987487793 4.388800144195557 31.840999603271484 22.396299362182617 0.33500000834465027 1.9739999771118164 0.5099999904632568 0.0 2.015000104904175 -9.0
10.600000381469727 10.5 19.81839942932129 19.8169002532959 4.387700080871582 31.850200653076172 22.409500122070312 0.4259999990463257 1.9630000591278076 0.5099999904632568 0.0 1.9839999675750732 -9.0
11.100000381469727 11.0 19.790199279785156 19.78860092163086 4.387400150299072 31.86870002746582 22.43090057373047 0.5130000114440918 1.5609999895095825 0.5099999904632568 0.0 1.944000005722046 -9.0
11.600000381469727 11.5 19.78179931640625 19.780099868774414 4.386899948120117 31.870800018310547 22.434600830078125 0.4650000035762787 1.5870000123977661 0.5099999904632568 0.0 1.9359999895095825 -9.0
12.100000381469727 12.0 19.769800186157227 19.76799964904785 4.386099815368652 31.873600006103516 22.439899444580078 0.5220000147819519 1.5360000133514404 0.5099999904632568 0.0 1.9509999752044678 -9.0
12.600000381469727 12.5 19.773300170898438 19.771400451660156 4.386300086975098 31.872699737548828 22.43829917907715 0.6119999885559082 1.4789999723434448 0.5099999904632568 0.0 1.937999963760376 -9.0
13.100000381469727 13.0 19.764999389648438 19.76300048828125 4.385200023651123 31.86989974975586 22.438400268554688 0.6060000061988831 1.4299999475479126 0.5099999904632568 0.0 1.9199999570846558 -9.0
13.600000381469727 13.5 19.746000289916992 19.743999481201172 4.383800029754639 31.872400283813477 22.445199966430664 0.5019999742507935 1.3289999961853027 0.5099999904632568 0.0 1.9129999876022339 -9.0
14.100000381469727 14.0 19.711700439453125 19.7096004486084 4.381199836730957 31.877199172973633 22.457599639892578 0.3490000069141388 1.3530000448226929 0.5099999904632568 0.0 1.9179999828338623 -9.0
14.600000381469727 14.5 19.678800582885742 19.676599502563477 4.378799915313721 31.882699966430664 22.470300674438477 0.40799999237060547 1.340999960899353 0.5099999904632568 0.0 1.906000018119812 -9.0
15.100000381469727 15.0 19.666799545288086 19.664499282836914 4.378600120544434 31.890300750732422 22.47920036315918 0.5899999737739563 0.968999981880188 0.5099999904632568 0.0 1.940999984741211 -9.0
15.600000381469727 15.5 19.659000396728516 19.6564998626709 4.380899906158447 31.914199829101562 22.499399185180664 0.6299999952316284 0.8019999861717224 0.5099999904632568 0.0 1.9279999732971191 -9.0
16.100000381469727 16.0 19.657899856567383 19.655399322509766 4.3856000900268555 31.952999114990234 22.529199600219727 0.4480000138282776 0.765999972820282 0.5099999904632568 0.0 1.9160000085830688 -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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