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Dataset Title:	Glider - gp_363-20160630T0230-delayed
Institution:	OOI Coastal & Global Scale Nodes (CGSN)   (Dataset ID: gp_363_20160630t0230_delayed)
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: 29)
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_363-20160630T0230	1 option: gp_363-20160630T0230
wmo_id	= (ANY) 4801994	1 option: 4801994
profile_id	= (ANY)	1 option:
time	= (ANY) 2016-06-30T02:37:14Z 2016-06-30T03:06:47Z 2016-06-30T03:46:40Z 2016-06-30T04:49:21Z 2016-06-30T06:42:25Z 2016-06-30T09:50:56Z 2016-06-30T14:14:52Z 2016-06-30T18:54:26Z 2016-07-01T00:20:19Z 2016-07-01T05:31:41Z 2016-07-01T10:57:26Z 2016-07-01T16:11:55Z 2016-07-01T21:52:05Z 2016-07-02T03:13:51Z 2016-07-02T08:34:50Z 2016-07-02T13:55:04Z 2016-07-02T19:24:43Z 2016-07-03T00:56:11Z 2016-07-03T06:20:18Z 2016-07-03T11:45:36Z 2016-07-03T17:08:06Z 2016-07-03T22:37:18Z 2016-07-04T04:10:04Z 2016-07-04T09:39:42Z 2016-07-04T15:11:32Z 2016-07-04T19:34:06Z 2016-07-04T20:25:32Z 2016-07-04T21:18:59Z 2016-07-04T22:10:48Z	29 options
latitude	= (ANY) 50.09505776349277 50.095827348732094 50.096542054365884 50.10164040385576 50.10269440342841 50.10295369554141 50.11183567470564 50.112125720440645 50.11339614421983 50.113587220499646 50.118250651243436 50.12166167951828 50.12570495494004 50.12612565267517 50.12749168460813 50.12828548177245 50.1303432104004 50.1309253691688 50.13264565831091 50.13405505796582 50.13420047617155 50.1348799187302 50.135521585342275 50.14374257983155 50.15623144700995 50.16368036410163 50.166675992677604 50.16735357408639 50.167712987174  degrees_north	29 options
longitude	= (ANY) -144.6109075042427 -144.60202457910583 -144.55810864947736 -144.55385607237955 -144.5216037795611 -144.50450833294136 -144.50389816719724 -144.49945601016404 -144.49786772830387 -144.4972851049181 -144.44816211361012 -144.4283393550198 -144.4277061579787 -144.4270618824308 -144.42484693316635 -144.42318019766665 -144.4218566236768 -144.42047960457626 -144.41977471378232 -144.41920023308032 -144.41882216334034 -144.41688894388986 -144.41677389095503 -144.41623012969754 -144.4142793006132 -144.41177244377835 -144.4112647374714 -144.40938030918895 -144.40852330293384  degrees_east	29 options
lat_uv	= (ANY) 50.09778202240122 50.09830543280178 50.09947918012209 50.099578676889735 50.09959201569647 50.104357803487105 50.10515800043918 50.11557027372609 50.11719473013961 50.11934328920194 50.120994452541794 50.12138982626879 50.12439959756962 50.12516214149075 50.12577687250539 50.12808984601355 50.12952719337331 50.12995980652921 50.1303754836506 50.130886860025825 50.13141289657347 50.13389868383757 50.135682315485035 50.14013500816802 50.153363952943735 50.1621285533346 50.166020321243415 50.167312408993595 50.167397531907675  degrees_north	29 options
lon_uv	= (ANY) -144.61163504987493 -144.59561146298333 -144.5691037280966 -144.5410752364525 -144.5292589616978 -144.50778709867285 -144.49961456982086 -144.49917631192338 -144.49805828542856 -144.48899446097312 -144.43853237398 -144.42725380087458 -144.42605449766674 -144.42589127345994 -144.4250233050048 -144.42323430833895 -144.42319623104842 -144.42203876427288 -144.42151494092053 -144.41896535670273 -144.41831427113354 -144.41800072261657 -144.41738992120577 -144.41689144061945 -144.41397645517327 -144.41319676955752 -144.41275975457097 -144.41168711070162 -144.41095837272712  degrees_east	29 options
time_uv	= (ANY) 2016-06-30T02:41:05Z 2016-06-30T03:14:24Z 2016-06-30T03:57:38Z 2016-06-30T05:09:17Z 2016-06-30T07:20:08Z 2016-06-30T10:51:44Z 2016-06-30T15:16:54Z 2016-06-30T20:14:29Z 2016-07-01T01:32:54Z 2016-07-01T06:53:17Z 2016-07-01T12:11:27Z 2016-07-01T17:38:31Z 2016-07-01T23:06:56Z 2016-07-02T04:28:40Z 2016-07-02T09:49:03Z 2016-07-02T15:13:02Z 2016-07-02T20:42:39Z 2016-07-03T02:11:52Z 2016-07-03T07:34:38Z 2016-07-03T13:01:25Z 2016-07-03T18:30:28Z 2016-07-03T23:54:23Z 2016-07-04T05:26:00Z 2016-07-04T10:56:47Z 2016-07-04T16:27:21Z 2016-07-04T19:49:23Z 2016-07-04T20:40:24Z 2016-07-04T21:33:40Z 2016-07-04T22:25:12Z	29 options
u	= (ANY) -0.104497 -0.0570919 -0.0413324 -0.0339709 -0.0302287 -0.0272061 -0.0252379 -0.0226544 -0.0223793 -0.0216409 -0.0214544 -0.0202768 -0.0192107 -0.0188142 -0.0185073 -0.0161346 -0.0158054 -0.0154528 -0.0145218 -0.0130977 -0.00580844 -3.38535E-4 0.0142881 0.0145365 0.0293787 0.0406341 0.0528037 0.0675871 0.115099  m s-1	29 options
v	= (ANY) -0.179956 -0.139917 -0.0957322 -0.0701381 -0.00750276 -0.00201682 6.87771E-4 0.00139686 0.00654169 0.00901477 0.0117308 0.0117738 0.0125168 0.0224167 0.0303797 0.0308058 0.0308651 0.0388702 0.0394449 0.0426343 0.0491461 0.0491506 0.0509953 0.0547374 0.0592121 0.0613129 0.069483 0.073277 0.08329  m s-1	29 options

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	profile_id	time	latitude	longitude	lat_uv	lon_uv	time_uv	u	v
			UTC	degrees_north	degrees_east	degrees_north	degrees_east	UTC	m s-1	m s-1
gp_363-20160630T0230	4801994		2016-06-30T02:37:14Z	50.16735357408639	-144.49945601016404	50.167397531907675	-144.49917631192338	2016-06-30T02:41:05Z	0.0528037	0.08329
gp_363-20160630T0230	4801994		2016-06-30T03:06:47Z	50.167712987174	-144.4972851049181	50.167312408993595	-144.49805828542856	2016-06-30T03:14:24Z	0.0406341	0.0388702
gp_363-20160630T0230	4801994		2016-06-30T03:46:40Z	50.166675992677604	-144.49786772830387	50.166020321243415	-144.49961456982086	2016-06-30T03:57:38Z	-0.0302287	0.00901477
gp_363-20160630T0230	4801994		2016-06-30T04:49:21Z	50.16368036410163	-144.50450833294136	50.1621285533346	-144.50778709867285	2016-06-30T05:09:17Z	-0.0130977	0.0308058
gp_363-20160630T0230	4801994		2016-06-30T06:42:25Z	50.15623144700995	-144.5216037795611	50.153363952943735	-144.5292589616978	2016-06-30T07:20:08Z	-0.0413324	6.87771E-4
gp_363-20160630T0230	4801994		2016-06-30T09:50:56Z	50.14374257983155	-144.55810864947736	50.14013500816802	-144.5691037280966	2016-06-30T10:51:44Z	-0.0216409	0.0117308
gp_363-20160630T0230	4801994		2016-06-30T14:14:52Z	50.13264565831091	-144.60202457910583	50.1303754836506	-144.61163504987493	2016-06-30T15:16:54Z	-0.0223793	0.0491461
gp_363-20160630T0230	4801994		2016-06-30T18:54:26Z	50.12749168460813	-144.6109075042427	50.12952719337331	-144.59561146298333	2016-06-30T20:14:29Z	-0.0185073	0.069483
gp_363-20160630T0230	4801994		2016-07-01T00:20:19Z	50.1309253691688	-144.55385607237955	50.13141289657347	-144.5410752364525	2016-07-01T01:32:54Z	-0.0226544	0.0613129
gp_363-20160630T0230	4801994		2016-07-01T05:31:41Z	50.13420047617155	-144.50389816719724	50.135682315485035	-144.48899446097312	2016-07-01T06:53:17Z	-0.0339709	0.073277
gp_363-20160630T0230	4801994		2016-07-01T10:57:26Z	50.1348799187302	-144.44816211361012	50.130886860025825	-144.43853237398	2016-07-01T12:11:27Z	-0.0154528	0.0426343
gp_363-20160630T0230	4801994		2016-07-01T16:11:55Z	50.113587220499646	-144.41623012969754	50.10515800043918	-144.41397645517327	2016-07-01T17:38:31Z	0.0142881	0.0491506
gp_363-20160630T0230	4801994		2016-07-01T21:52:05Z	50.095827348732094	-144.41882216334034	50.09778202240122	-144.4250233050048	2016-07-01T23:06:56Z	-0.0202768	-0.00750276
gp_363-20160630T0230	4801994		2016-07-02T03:13:51Z	50.11183567470564	-144.4277061579787	50.120994452541794	-144.42605449766674	2016-07-02T04:28:40Z	-0.0570919	0.0547374
gp_363-20160630T0230	4801994		2016-07-02T08:34:50Z	50.12612565267517	-144.4218566236768	50.11719473013961	-144.41800072261657	2016-07-02T09:49:03Z	0.0145365	-0.00201682
gp_363-20160630T0230	4801994		2016-07-02T13:55:04Z	50.10269440342841	-144.41677389095503	50.104357803487105	-144.42151494092053	2016-07-02T15:13:02Z	-0.0158054	0.0303797
gp_363-20160630T0230	4801994		2016-07-02T19:24:43Z	50.11339614421983	-144.42318019766665	50.11934328920194	-144.42319623104842	2016-07-02T20:42:39Z	-0.0192107	0.0224167
gp_363-20160630T0230	4801994		2016-07-03T00:56:11Z	50.12166167951828	-144.42047960457626	50.11557027372609	-144.41831427113354	2016-07-03T02:11:52Z	-3.38535E-4	0.0125168
gp_363-20160630T0230	4801994		2016-07-03T06:20:18Z	50.10164040385576	-144.41688894388986	50.09830543280178	-144.41896535670273	2016-07-03T07:34:38Z	-0.0272061	0.0509953
gp_363-20160630T0230	4801994		2016-07-03T11:45:36Z	50.096542054365884	-144.41977471378232	50.099578676889735	-144.42203876427288	2016-07-03T13:01:25Z	-0.0161346	0.0117738
gp_363-20160630T0230	4801994		2016-07-03T17:08:06Z	50.112125720440645	-144.4283393550198	50.12138982626879	-144.42589127345994	2016-07-03T18:30:28Z	-0.0252379	0.0394449
gp_363-20160630T0230	4801994		2016-07-03T22:37:18Z	50.13405505796582	-144.41920023308032	50.12516214149075	-144.41738992120577	2016-07-03T23:54:23Z	-0.00580844	0.00139686
gp_363-20160630T0230	4801994		2016-07-04T04:10:04Z	50.10295369554141	-144.40852330293384	50.09959201569647	-144.41275975457097	2016-07-04T05:26:00Z	-0.0188142	0.0592121
gp_363-20160630T0230	4801994		2016-07-04T09:39:42Z	50.09505776349277	-144.4270618824308	50.09947918012209	-144.42725380087458	2016-07-04T10:56:47Z	-0.0145218	0.00654169
gp_363-20160630T0230	4801994		2016-07-04T15:11:32Z	50.118250651243436	-144.42484693316635	50.12439959756962	-144.42323430833895	2016-07-04T16:27:21Z	-0.0214544	0.0308651
gp_363-20160630T0230	4801994		2016-07-04T19:34:06Z	50.135521585342275	-144.4112647374714	50.13389868383757	-144.41168711070162	2016-07-04T19:49:23Z	0.115099	-0.0701381
gp_363-20160630T0230	4801994		2016-07-04T20:25:32Z	50.1303432104004	-144.40938030918895	50.12995980652921	-144.41095837272712	2016-07-04T20:40:24Z	0.0293787	-0.0957322
gp_363-20160630T0230	4801994		2016-07-04T21:18:59Z	50.12828548177245	-144.41177244377835	50.12808984601355	-144.41319676955752	2016-07-04T21:33:40Z	0.0675871	-0.139917
gp_363-20160630T0230	4801994		2016-07-04T22:10:48Z	50.12570495494004	-144.4142793006132	50.12577687250539	-144.41689144061945	2016-07-04T22:25:12Z	-0.104497	-0.179956

In total, there are 29 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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