![]() |
Metocean: Historical collections
|
Brought to you by NOAA NMFS SWFSC ERD |
Dataset Title: | "Deepwater CTD - 00596907.bdo.nc - 21.68N, -85.99W - 1970-04-20"
![]() ![]() |
Institution: | Texas A&M University, Department of Oceanography (Dataset ID: deepwater_00596907_bdo) |
Information: | Summary ![]() ![]() ![]() |
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.
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 | not-measured | not-measured | not-measured | micromols | PSU | |
0.0 | 27.440000534057617 | 35.84700012207031 | 4.710000038146973 | 1.0 | 0.0 | ||||
40.0 | 27.329999923706055 | 35.84600067138672 | 4.659999847412109 | 1.0 | 0.0 | ||||
65.0 | 27.170000076293945 | 35.849998474121094 | 4.71999979019165 | 1.0 | 0.0 | ||||
79.0 | 26.799999237060547 | 35.92100143432617 | 4.659999847412109 | 1.0 | 0.0 | ||||
99.0 | 25.709999084472656 | 36.237998962402344 | 4.349999904632568 | 1.0 | 0.0 | ||||
118.0 | 25.079999923706055 | 36.49599838256836 | 4.059999942779541 | 1.0 | 0.0 | ||||
138.0 | 22.489999771118164 | 36.72600173950195 | 3.5799999237060547 | 1.0 | 0.0 | ||||
158.0 | 21.059999465942383 | 36.75199890136719 | 3.7899999618530273 | 1.0 | 0.0 | ||||
177.0 | 20.139999389648438 | 36.68000030517578 | 3.4100000858306885 | 2.0 | 0.0 | ||||
196.0 | 19.40999984741211 | 36.60499954223633 | 3.7200000286102295 | 2.0 | 0.0 | ||||
226.0 | 18.18000030517578 | 36.470001220703125 | 3.5299999713897705 | 2.0 | 0.0 | ||||
255.0 | 17.15999984741211 | 36.32400131225586 | 3.809999942779541 | 3.0 | 0.0 | ||||
294.0 | 15.9399995803833 | 36.12699890136719 | 3.490000009536743 | 4.0 | 0.0 | ||||
343.0 | 14.510000228881836 | 35.87300109863281 | 3.559999942779541 | 5.0 | 0.0 | ||||
392.0 | 13.5 | 35.70899963378906 | 3.119999885559082 | 6.0 | 0.0 | ||||
442.0 | 13.149999618530273 | -99.98999786376953 | 3.2200000286102295 | 8.0 | 0.0 | ||||
492.0 | 10.890000343322754 | 35.30500030517578 | 2.9200000762939453 | 10.0 | 0.0 | ||||
542.0 | 10.180000305175781 | 35.207000732421875 | 3.0799999237060547 | 12.0 | 0.0 | ||||
612.0 | 8.899999618530273 | 35.0369987487793 | 2.7899999618530273 | 14.0 | 0.0 | ||||
706.0 | 7.159999847412109 | 34.882999420166016 | 3.190000057220459 | 18.0 | 0.0 | ||||
777.0 | 6.519999980926514 | 34.85900115966797 | 3.2100000381469727 | 20.0 | 0.0 | ||||
847.0 | 5.940000057220459 | 34.869998931884766 | 3.700000047683716 | 21.0 | 0.0 | ||||
919.0 | 5.489999771118164 | 34.9010009765625 | 3.6600000858306885 | 21.0 | 0.0 | ||||
990.0 | 5.139999866485596 | 34.917999267578125 | -99.98999786376953 | 22.0 | 0.0 | ||||
1228.0 | 4.539999961853027 | 34.957000732421875 | 4.71999979019165 | 21.0 | 0.0 | ||||
1517.0 | 4.260000228881836 | 34.9739990234375 | 5.010000228881836 | 20.0 | 0.0 | ||||
1790.0 | 4.21999979019165 | 34.97800064086914 | 5.190000057220459 | 20.0 | 0.0 | ||||
1840.0 | 4.210000038146973 | 34.97700119018555 | 5.190000057220459 | 20.0 | 0.0 |
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.
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.