GCOOS Metocean: Historical collections
   
Brought to you by NOAA NMFS SWFSC ERD    

ERDDAP > tabledap > Subset ?

Dataset Title:  "Deepwater CTD - 87g1101.ctd.nc - 27.66N, -94.0W - 1987-11-18" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_87g1101_ctd)
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: 50)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    depth ?  =  m   50 options
    temperature ?  =  degree_C   48 options
    salinity ?  =  PSU   40 options
    oxygen ?  =  milliliters per liter   7 options
    nitrite ?  =  micromols per liter   6 options
    nitrate ?  =  micromols   11 options
    phosphate ?  =  micromols per liter   10 options
    silicate ?  =  micromols per liter   13 options
    salinity2 ?  =  PSU   2 options
    qualityFlag ?  =  1 option: 0.0

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)  

depth temperature salinity oxygen nitrite nitrate phosphate silicate salinity2 qualityFlag
m degree_C PSU milliliters per liter micromols per liter micromols micromols per liter micromols per liter PSU
3.0 23.905000686645508 36.30400085449219 4.800000190734863 0.03999999910593033 0.05999999865889549 0.009999999776482582 3.4000000953674316 -99.0 0.0
6.0 23.908000946044922 36.303001403808594 4.797999858856201 0.029999999329447746 0.07000000029802322 0.009999999776482582 2.619999885559082 -99.0 0.0
12.0 23.906999588012695 36.30400085449219 4.791999816894531 0.029999999329447746 0.07000000029802322 0.009999999776482582 2.5399999618530273 -99.0 0.0
18.0 23.908000946044922 36.303001403808594 -99.0 0.09000000357627869 0.05000000074505806 0.07999999821186066 2.7100000381469727 -99.0 0.0
22.0 23.908000946044922 36.303001403808594 4.756999969482422 0.05999999865889549 0.07999999821186066 0.05000000074505806 2.4200000762939453 -99.0 0.0
27.0 23.91200065612793 36.30400085449219 4.793000221252441 0.03999999910593033 0.12999999523162842 0.05999999865889549 2.3399999141693115 -99.0 0.0
32.0 23.91699981689453 36.30400085449219 -99.0 0.05999999865889549 11.100000381469727 0.6100000143051147 5.5 -99.0 0.0
37.0 23.915000915527344 36.303001403808594 -99.0 0.05999999865889549 11.199999809265137 0.6100000143051147 5.539999961853027 -99.0 0.0
42.0 23.92799949645996 36.31100082397461 -99.0 0.03999999910593033 15.300000190734863 0.8100000023841858 6.650000095367432 -99.0 0.0
48.0 23.94700050354004 36.31999969482422 -99.0 0.05000000074505806 15.300000190734863 0.8399999737739563 7.019999980926514 -99.0 0.0
52.0 23.951000213623047 36.321998596191406 -99.0 0.029999999329447746 16.5 0.8799999952316284 7.510000228881836 -99.0 0.0
57.0 23.966999053955078 36.332000732421875 -99.0 0.05000000074505806 19.200000762939453 1.0499999523162842 9.989999771118164 -99.0 0.0
62.0 23.976999282836914 36.3380012512207 0.0
67.0 23.979000091552734 36.3380012512207 0.0
73.0 23.974000930786133 36.33700180053711 0.0
77.0 23.02899932861328 36.25199890136719 0.0
82.0 21.56599998474121 36.356998443603516 0.0
87.0 20.729999542236328 36.3489990234375 0.0
92.0 20.402000427246094 36.374000549316406 0.0
98.0 20.288999557495117 36.374000549316406 0.0
102.0 20.21299934387207 36.37200164794922 0.0
107.0 19.909000396728516 36.35200119018555 0.0
112.0 19.41200065612793 36.33399963378906 0.0
117.0 18.67300033569336 36.3120002746582 0.0
123.0 18.21500015258789 36.29800033569336 0.0
127.0 17.986000061035156 36.29800033569336 0.0
132.0 17.753000259399414 36.290000915527344 0.0
137.0 17.510000228881836 36.26300048828125 0.0
142.0 17.208999633789062 36.24300003051758 0.0
148.0 16.923999786376953 36.224998474121094 0.0
152.0 16.80699920654297 36.220001220703125 0.0
157.0 16.735000610351562 36.224998474121094 0.0
162.0 16.628999710083008 36.20100021362305 0.0
167.0 16.518999099731445 36.185001373291016 0.0
173.0 16.26099967956543 36.14400100708008 0.0
177.0 16.093000411987305 36.125 0.0
183.0 15.954000473022461 36.10900115966797 0.0
187.0 15.87399959564209 36.09400177001953 0.0
192.0 15.720999717712402 36.06999969482422 0.0
197.0 15.5649995803833 36.047000885009766 0.0
202.0 15.456000328063965 36.027000427246094 0.0
207.0 15.333000183105469 35.99800109863281 0.0
212.0 15.152000427246094 35.96900177001953 0.0
217.0 14.984000205993652 35.952999114990234 0.0
222.0 14.82800006866455 35.92900085449219 0.0
227.0 14.664999961853027 35.9010009765625 0.0
232.0 14.468000411987305 35.87099838256836 0.0
237.0 14.39799976348877 35.86399841308594 0.0
242.0 14.333000183105469 35.84199905395508 0.0
248.0 14.211000442504883 35.832000732421875 0.0

In total, there are 50 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.


 
ERDDAP, Version 2.23
Disclaimers | Privacy Policy | Contact