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Dataset Title:	Glider - gp_363-20160630T0230
Institution:	Ocean Observatories Initiative   (Dataset ID: gp_363_20160630t0230)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Data Access Form | 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.

trajectory	= (ANY) gp_363-20160630T023000Z	1 option: gp_363-20160630T023000Z
wmo_id	= (ANY) 4801994	1 option: 4801994
time	= (ANY) 2016-06-30T02:37:32Z 2016-06-30T03:05:48Z 2016-06-30T03:41:44Z 2016-06-30T04:31:44Z 2016-06-30T06:05:31Z 2016-06-30T08:49:09Z 2016-06-30T13:07:11Z 2016-06-30T17:45:24Z 2016-06-30T23:01:11Z 2016-07-01T04:23:24Z 2016-07-01T09:40:28Z 2016-07-01T15:04:36Z 2016-07-01T20:35:25Z 2016-07-02T01:57:23Z 2016-07-02T07:19:44Z 2016-07-02T12:38:58Z 2016-07-02T18:06:01Z 2016-07-02T23:38:33Z 2016-07-03T05:02:07Z 2016-07-03T10:25:01Z 2016-07-03T15:56:21Z 2016-07-03T21:20:48Z 2016-07-04T02:49:54Z 2016-07-04T08:20:15Z 2016-07-04T13:53:18Z 2016-07-04T19:27:56Z 2016-07-04T20:20:58Z 2016-07-04T21:13:38Z	28 options
latitude	= (ANY) 50.09508311704829 50.09585682910367 50.09651968297593 50.1016270006161 50.10272147616616 50.102988914377576 50.11182512399696 50.11219354784774 50.11351440706085 50.11352516530454 50.11832498308175 50.1216259029708 50.12611787545968 50.12749809744268 50.12838124710379 50.13029736757338 50.13092221778603 50.132649542593484 50.134020739598355 50.134214143498525 50.13484668017094 50.13550897178504 50.14375451284151 50.156211596835554 50.16363049646808 50.16661830477615 50.16742955478937 50.16770960995229  degrees_north	28 options
longitude	= (ANY) -144.61082261941223 -144.60200275459567 -144.55808016611132 -144.55390024984752 -144.5216603474233 -144.50460793496003 -144.50376135455778 -144.49935235539223 -144.49783568142033 -144.49738940159807 -144.44807612752209 -144.42833036271503 -144.42769043583718 -144.427074277536 -144.42483196144727 -144.423141306795 -144.42186960185828 -144.42046878073046 -144.41975478080565 -144.41919765585155 -144.4189039126939 -144.41690310691746 -144.41683151380903 -144.41621088445743 -144.4114454563638 -144.41131499941733 -144.40930981899447 -144.40848028360057  degrees_east	28 options
profile_id	= (ANY) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28	28 options
time_uv	= (ANY) NaN	1 option: NaN
lat_uv	= (ANY)  degrees_north	1 option:
lon_uv	= (ANY)  degrees_east	1 option:
u	= (ANY)  m s-1	1 option:
v	= (ANY)  m s-1	1 option:

View:      Map of Distinct Data      Distinct Data Counts     Distinct Data  0 10 100 1000 10000 100000      Related Data Counts     Related Data  0 10 100 1000 10000 100000

 

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Map of Distinct Data   (Refine the map and/or download the image)
Optional: Click on the map to select the closest data.

 

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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.
 

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Distinct Data   (Metadata)    (Refine the data subset and/or download the data)  

trajectory	wmo_id	time	latitude	longitude	profile_id	time_uv	lat_uv	lon_uv	u	v
		UTC	degrees_north	degrees_east		UTC	degrees_north	degrees_east	m s-1	m s-1
gp_363-20160630T023000Z	4801994	2016-06-30T02:37:32Z	50.16742955478937	-144.49935235539223	1
gp_363-20160630T023000Z	4801994	2016-06-30T03:05:48Z	50.16770960995229	-144.49738940159807	2
gp_363-20160630T023000Z	4801994	2016-06-30T03:41:44Z	50.16661830477615	-144.49783568142033	3
gp_363-20160630T023000Z	4801994	2016-06-30T04:31:44Z	50.16363049646808	-144.50460793496003	4
gp_363-20160630T023000Z	4801994	2016-06-30T06:05:31Z	50.156211596835554	-144.5216603474233	5
gp_363-20160630T023000Z	4801994	2016-06-30T08:49:09Z	50.14375451284151	-144.55808016611132	6
gp_363-20160630T023000Z	4801994	2016-06-30T13:07:11Z	50.132649542593484	-144.60200275459567	7
gp_363-20160630T023000Z	4801994	2016-06-30T17:45:24Z	50.12749809744268	-144.61082261941223	8
gp_363-20160630T023000Z	4801994	2016-06-30T23:01:11Z	50.13092221778603	-144.55390024984752	9
gp_363-20160630T023000Z	4801994	2016-07-01T04:23:24Z	50.134214143498525	-144.50376135455778	10
gp_363-20160630T023000Z	4801994	2016-07-01T09:40:28Z	50.13484668017094	-144.44807612752209	11
gp_363-20160630T023000Z	4801994	2016-07-01T15:04:36Z	50.11351440706085	-144.41621088445743	12
gp_363-20160630T023000Z	4801994	2016-07-01T20:35:25Z	50.09585682910367	-144.4189039126939	13
gp_363-20160630T023000Z	4801994	2016-07-02T01:57:23Z	50.11182512399696	-144.42769043583718	14
gp_363-20160630T023000Z	4801994	2016-07-02T07:19:44Z	50.12611787545968	-144.42186960185828	15
gp_363-20160630T023000Z	4801994	2016-07-02T12:38:58Z	50.10272147616616	-144.41683151380903	16
gp_363-20160630T023000Z	4801994	2016-07-02T18:06:01Z	50.11352516530454	-144.423141306795	17
gp_363-20160630T023000Z	4801994	2016-07-02T23:38:33Z	50.1216259029708	-144.42046878073046	18
gp_363-20160630T023000Z	4801994	2016-07-03T05:02:07Z	50.1016270006161	-144.41690310691746	19
gp_363-20160630T023000Z	4801994	2016-07-03T10:25:01Z	50.09651968297593	-144.41975478080565	20
gp_363-20160630T023000Z	4801994	2016-07-03T15:56:21Z	50.11219354784774	-144.42833036271503	21
gp_363-20160630T023000Z	4801994	2016-07-03T21:20:48Z	50.134020739598355	-144.41919765585155	22
gp_363-20160630T023000Z	4801994	2016-07-04T02:49:54Z	50.102988914377576	-144.40848028360057	23
gp_363-20160630T023000Z	4801994	2016-07-04T08:20:15Z	50.09508311704829	-144.427074277536	24
gp_363-20160630T023000Z	4801994	2016-07-04T13:53:18Z	50.11832498308175	-144.42483196144727	25
gp_363-20160630T023000Z	4801994	2016-07-04T19:27:56Z	50.13550897178504	-144.41131499941733	26
gp_363-20160630T023000Z	4801994	2016-07-04T20:20:58Z	50.13029736757338	-144.40930981899447	27
gp_363-20160630T023000Z	4801994	2016-07-04T21:13:38Z	50.12838124710379	-144.4114454563638	28

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.
 

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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.
 

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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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