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ERDDAP > tabledap > Subset ?

Dataset Title:  "Deepwater CTD - 53894.ctd.nc - 27.0N, -95.0W - 1992-05-22" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_53894_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: 200)
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   200 options
    temperature ?  =  degree_C   22 options
    salinity ?  =  PSU   21 options
    oxygen ?  =  milligrams per liter   1 option:
    pressure ?  =  decibars   22 options
    nitrite ?  =  not-measured   2 options
    nitrate ?  =  not-measured   2 options
    phosphate ?  =  not-measured   2 options
    silicate ?  =  not-measured   2 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 pressure nitrite nitrate phosphate silicate salinity2 qualityFlag
m degree_C PSU milligrams per liter decibars not-measured not-measured not-measured not-measured PSU
1.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
2.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
3.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
4.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
5.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
6.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
7.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
8.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
9.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
10.0 25.506000518798828 35.85770034790039 9.800000190734863 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
11.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
12.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
13.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
14.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
15.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
16.0 -990.0 -99.0 -99.0 -99.0 -99.0 -99.0 0.0
17.0 -990.0 0.0
18.0 -990.0 0.0
19.0 25.41900062561035 35.935699462890625 19.5 0.0
20.0 -990.0 0.0
21.0 -990.0 0.0
22.0 -990.0 0.0
23.0 -990.0 0.0
24.0 -990.0 0.0
25.0 -990.0 0.0
26.0 -990.0 0.0
27.0 -990.0 0.0
28.0 -990.0 0.0
29.0 24.535999298095703 35.97829818725586 29.100000381469727 0.0
30.0 -990.0 0.0
31.0 -990.0 0.0
32.0 -990.0 0.0
33.0 -990.0 0.0
34.0 -990.0 0.0
35.0 -990.0 0.0
36.0 -990.0 0.0
37.0 -990.0 0.0
38.0 24.756000518798828 36.27619934082031 38.29999923706055 0.0
39.0 -990.0 0.0
40.0 -990.0 0.0
41.0 -990.0 0.0
42.0 -990.0 0.0
43.0 -990.0 0.0
44.0 -990.0 0.0
45.0 -990.0 0.0
46.0 -990.0 0.0
47.0 -990.0 0.0
48.0 -990.0 0.0
49.0 23.70400047302246 36.289398193359375 49.20000076293945 0.0
50.0 -990.0 0.0
51.0 -990.0 0.0
52.0 -990.0 0.0
53.0 -990.0 0.0
54.0 -990.0 0.0
55.0 -990.0 0.0
56.0 -990.0 0.0
57.0 23.400999069213867 36.367401123046875 57.79999923706055 0.0
58.0 -990.0 0.0
59.0 -990.0 0.0
60.0 -990.0 0.0
61.0 -990.0 0.0
62.0 -990.0 0.0
63.0 -990.0 0.0
64.0 -990.0 0.0
65.0 -990.0 0.0
66.0 -990.0 0.0
67.0 23.084999084472656 36.333900451660156 67.5 0.0
68.0 -990.0 0.0
69.0 -990.0 0.0
70.0 -990.0 0.0
71.0 -990.0 0.0
72.0 -990.0 0.0
73.0 -990.0 0.0
74.0 -990.0 0.0
75.0 -990.0 0.0
76.0 22.871999740600586 36.33489990234375 76.0999984741211 0.0
77.0 -990.0 0.0
78.0 -990.0 0.0
79.0 -990.0 0.0
80.0 -990.0 0.0
81.0 -990.0 0.0
82.0 -990.0 0.0
83.0 -990.0 0.0
84.0 -990.0 0.0
85.0 22.799999237060547 36.36029815673828 85.19999694824219 0.0
86.0 -990.0 0.0
87.0 -990.0 0.0
88.0 -990.0 0.0
89.0 -990.0 0.0
90.0 -990.0 0.0
91.0 -990.0 0.0
92.0 -990.0 0.0
93.0 -990.0 0.0
94.0 22.49799919128418 36.3025016784668 94.4000015258789 0.0
95.0 -990.0 0.0
96.0 -990.0 0.0
97.0 -990.0 0.0
98.0 -990.0 0.0
99.0 -990.0 0.0
100.0 -990.0 0.0
101.0 -990.0 0.0
102.0 -990.0 0.0
103.0 -990.0 0.0
104.0 -990.0 0.0
105.0 -990.0 0.0
106.0 -990.0 0.0
107.0 22.066999435424805 36.27009963989258 107.9000015258789 0.0
108.0 -990.0 0.0
109.0 -990.0 0.0
110.0 -990.0 0.0
111.0 -990.0 0.0
112.0 -990.0 0.0
113.0 -990.0 0.0
114.0 -990.0 0.0
115.0 -990.0 0.0
116.0 -990.0 0.0
117.0 21.384000778198242 36.26300048828125 117.4000015258789 0.0
118.0 -990.0 0.0
119.0 -990.0 0.0
120.0 -990.0 0.0
121.0 -990.0 0.0
122.0 -990.0 0.0
123.0 -990.0 0.0
124.0 -990.0 0.0
125.0 -990.0 0.0
126.0 -990.0 0.0
127.0 20.611000061035156 36.27009963989258 127.5999984741211 0.0
128.0 -990.0 0.0
129.0 -990.0 0.0
130.0 -990.0 0.0
131.0 -990.0 0.0
132.0 -990.0 0.0
133.0 -990.0 0.0
134.0 -990.0 0.0
135.0 -990.0 0.0
136.0 20.288000106811523 36.34709930419922 137.10000610351562 0.0
137.0 -990.0 0.0
138.0 -990.0 0.0
139.0 -990.0 0.0
140.0 -990.0 0.0
141.0 -990.0 0.0
142.0 -990.0 0.0
143.0 -990.0 0.0
144.0 -990.0 0.0
145.0 -990.0 0.0
146.0 -990.0 0.0
147.0 19.871000289916992 36.45349884033203 148.3000030517578 0.0
148.0 -990.0 0.0
149.0 -990.0 0.0
150.0 -990.0 0.0
151.0 -990.0 0.0
152.0 -990.0 0.0
153.0 -990.0 0.0
154.0 -990.0 0.0
155.0 19.445999145507812 36.464599609375 156.10000610351562 0.0
156.0 -990.0 0.0
157.0 -990.0 0.0
158.0 -990.0 0.0
159.0 -990.0 0.0
160.0 -990.0 0.0
161.0 -990.0 0.0
162.0 -990.0 0.0
163.0 -990.0 0.0
164.0 -990.0 0.0
165.0 18.816999435424805 36.43629837036133 166.1999969482422 0.0
166.0 -990.0 0.0
167.0 -990.0 0.0
168.0 -990.0 0.0
169.0 -990.0 0.0
170.0 -990.0 0.0
171.0 -990.0 0.0
172.0 -990.0 0.0
173.0 -990.0 0.0
174.0 -990.0 0.0
175.0 18.341999053955078 36.38759994506836 176.60000610351562 0.0
176.0 -990.0 0.0
177.0 -990.0 0.0
178.0 -990.0 0.0
179.0 -990.0 0.0
180.0 -990.0 0.0
181.0 -990.0 0.0
182.0 -990.0 0.0
183.0 -990.0 0.0
184.0 18.016000747680664 36.35419845581055 185.1999969482422 0.0
185.0 -990.0 0.0
186.0 -990.0 0.0
187.0 -990.0 0.0
188.0 -990.0 0.0
189.0 -990.0 0.0
190.0 -990.0 0.0
191.0 -990.0 0.0
192.0 17.493000030517578 36.273101806640625 193.8000030517578 0.0
193.0 -990.0 0.0
194.0 -990.0 0.0
195.0 -990.0 0.0
196.0 -990.0 0.0
197.0 -990.0 0.0
198.0 -990.0 0.0
199.0 -990.0 0.0
200.0 17.132999420166016 36.21030044555664 201.89999389648438 0.0

In total, there are 200 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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