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ERDDAP > tabledap > Subset ?

Dataset Title:  Modeled Carbonate System (1998-2018) - CB3 2 Subscribe RSS
Institution:  Penn State   (Dataset ID: CB_MCS_CB3_2)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 185)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    station_id ?  =  1 option: CB3.2
    latitude ?  =  degrees_north   1 option: 39.16369
    longitude ?  =  degrees_east   1 option: -76.30631
    omegaar ?  =  1   185 options

View:      Map of Distinct Data ?      Distinct Data Counts ?     Distinct Data ?      Related Data Counts ?     Related Data ?

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

station_id latitude longitude omegaar
degrees_north degrees_east 1
CB3.2 39.16369 -76.30631
CB3.2 39.16369 -76.30631 0.006265668591591329
CB3.2 39.16369 -76.30631 0.007600230423648572
CB3.2 39.16369 -76.30631 0.020314997361164055
CB3.2 39.16369 -76.30631 0.02276394671685685
CB3.2 39.16369 -76.30631 0.02344886100613673
CB3.2 39.16369 -76.30631 0.024540015366601144
CB3.2 39.16369 -76.30631 0.035329782007956785
CB3.2 39.16369 -76.30631 0.03693885894484203
CB3.2 39.16369 -76.30631 0.04211173064588809
CB3.2 39.16369 -76.30631 0.043679315003013544
CB3.2 39.16369 -76.30631 0.04646668727046979
CB3.2 39.16369 -76.30631 0.04688378105974377
CB3.2 39.16369 -76.30631 0.048862573262819
CB3.2 39.16369 -76.30631 0.049443424698707425
CB3.2 39.16369 -76.30631 0.050219879170926726
CB3.2 39.16369 -76.30631 0.05057821614581626
CB3.2 39.16369 -76.30631 0.05214813623676397
CB3.2 39.16369 -76.30631 0.053628098665537395
CB3.2 39.16369 -76.30631 0.05372929691715246
CB3.2 39.16369 -76.30631 0.05506395844807067
CB3.2 39.16369 -76.30631 0.059243211691417025
CB3.2 39.16369 -76.30631 0.05932241377939197
CB3.2 39.16369 -76.30631 0.062322189361559435
CB3.2 39.16369 -76.30631 0.06317845846080425
CB3.2 39.16369 -76.30631 0.06427674181880112
CB3.2 39.16369 -76.30631 0.06685190698468331
CB3.2 39.16369 -76.30631 0.06685903823046307
CB3.2 39.16369 -76.30631 0.06953188953737957
CB3.2 39.16369 -76.30631 0.06972589374374835
CB3.2 39.16369 -76.30631 0.07112505896564009
CB3.2 39.16369 -76.30631 0.07354034126842161
CB3.2 39.16369 -76.30631 0.07362036355895149
CB3.2 39.16369 -76.30631 0.07442966675218533
CB3.2 39.16369 -76.30631 0.0779863356768363
CB3.2 39.16369 -76.30631 0.07819966610105732
CB3.2 39.16369 -76.30631 0.08136358889024503
CB3.2 39.16369 -76.30631 0.0821556326851604
CB3.2 39.16369 -76.30631 0.08252567151530937
CB3.2 39.16369 -76.30631 0.08348038047307628
CB3.2 39.16369 -76.30631 0.08490309002154171
CB3.2 39.16369 -76.30631 0.08552468449000236
CB3.2 39.16369 -76.30631 0.08815535681698602
CB3.2 39.16369 -76.30631 0.09002830348063603
CB3.2 39.16369 -76.30631 0.09003389426953756
CB3.2 39.16369 -76.30631 0.09154732658730516
CB3.2 39.16369 -76.30631 0.09294943217883826
CB3.2 39.16369 -76.30631 0.09683866197804285
CB3.2 39.16369 -76.30631 0.09873079861488801
CB3.2 39.16369 -76.30631 0.1010662318443078
CB3.2 39.16369 -76.30631 0.10510666488294877
CB3.2 39.16369 -76.30631 0.10581593644160031
CB3.2 39.16369 -76.30631 0.10781634688492084
CB3.2 39.16369 -76.30631 0.10847590846073815
CB3.2 39.16369 -76.30631 0.10894136942184078
CB3.2 39.16369 -76.30631 0.11159150278412289
CB3.2 39.16369 -76.30631 0.11241709656299419
CB3.2 39.16369 -76.30631 0.11303837014234343
CB3.2 39.16369 -76.30631 0.113788674845248
CB3.2 39.16369 -76.30631 0.11392172481983863
CB3.2 39.16369 -76.30631 0.11555216256278808
CB3.2 39.16369 -76.30631 0.11598921838720794
CB3.2 39.16369 -76.30631 0.11669435262420885
CB3.2 39.16369 -76.30631 0.1187203986580942
CB3.2 39.16369 -76.30631 0.11912243946168956
CB3.2 39.16369 -76.30631 0.11996697571446752
CB3.2 39.16369 -76.30631 0.12407908906911971
CB3.2 39.16369 -76.30631 0.12505804282453187
CB3.2 39.16369 -76.30631 0.1251348043401623
CB3.2 39.16369 -76.30631 0.12792550838586295
CB3.2 39.16369 -76.30631 0.13002922924156288
CB3.2 39.16369 -76.30631 0.1304736807806181
CB3.2 39.16369 -76.30631 0.1307034164094607
CB3.2 39.16369 -76.30631 0.1309365853548467
CB3.2 39.16369 -76.30631 0.1328551906571498
CB3.2 39.16369 -76.30631 0.13316268404545242
CB3.2 39.16369 -76.30631 0.1338056155098009
CB3.2 39.16369 -76.30631 0.1341494667374592
CB3.2 39.16369 -76.30631 0.13425506927850736
CB3.2 39.16369 -76.30631 0.13516326634436096
CB3.2 39.16369 -76.30631 0.13526859070590705
CB3.2 39.16369 -76.30631 0.1385976258291113
CB3.2 39.16369 -76.30631 0.1388166903449031
CB3.2 39.16369 -76.30631 0.1404956239624036
CB3.2 39.16369 -76.30631 0.14073103413325583
CB3.2 39.16369 -76.30631 0.14121516650584753
CB3.2 39.16369 -76.30631 0.14228233251466055
CB3.2 39.16369 -76.30631 0.14401895282123972
CB3.2 39.16369 -76.30631 0.1449676868858043
CB3.2 39.16369 -76.30631 0.14552282900791483
CB3.2 39.16369 -76.30631 0.14593179509887882
CB3.2 39.16369 -76.30631 0.1464399865953955
CB3.2 39.16369 -76.30631 0.14708293376638823
CB3.2 39.16369 -76.30631 0.14753790193776392
CB3.2 39.16369 -76.30631 0.14906756291917395
CB3.2 39.16369 -76.30631 0.15012830354447979
CB3.2 39.16369 -76.30631 0.15083767564450615
CB3.2 39.16369 -76.30631 0.15185802150293815
CB3.2 39.16369 -76.30631 0.15418997290285108
CB3.2 39.16369 -76.30631 0.1558575029989942
CB3.2 39.16369 -76.30631 0.1559159635046695
CB3.2 39.16369 -76.30631 0.15692279571146678
CB3.2 39.16369 -76.30631 0.15971173709110775
CB3.2 39.16369 -76.30631 0.16079022649875688
CB3.2 39.16369 -76.30631 0.16125390358964026
CB3.2 39.16369 -76.30631 0.16297941739950625
CB3.2 39.16369 -76.30631 0.16405062712917343
CB3.2 39.16369 -76.30631 0.16507220176828827
CB3.2 39.16369 -76.30631 0.17155457041349653
CB3.2 39.16369 -76.30631 0.1729256484453484
CB3.2 39.16369 -76.30631 0.18441215669103428
CB3.2 39.16369 -76.30631 0.1893115624936769
CB3.2 39.16369 -76.30631 0.19035820722987137
CB3.2 39.16369 -76.30631 0.19473169048418315
CB3.2 39.16369 -76.30631 0.19706158259658185
CB3.2 39.16369 -76.30631 0.19985094689961075
CB3.2 39.16369 -76.30631 0.19985964080860935
CB3.2 39.16369 -76.30631 0.2012525613649708
CB3.2 39.16369 -76.30631 0.20128600796872934
CB3.2 39.16369 -76.30631 0.2042595915032405
CB3.2 39.16369 -76.30631 0.204671108457011
CB3.2 39.16369 -76.30631 0.2055300079301806
CB3.2 39.16369 -76.30631 0.20730685420109843
CB3.2 39.16369 -76.30631 0.2077945637585356
CB3.2 39.16369 -76.30631 0.2080091739657951
CB3.2 39.16369 -76.30631 0.20863020771173266
CB3.2 39.16369 -76.30631 0.20886196567205917
CB3.2 39.16369 -76.30631 0.2090469448305678
CB3.2 39.16369 -76.30631 0.20930431594100773
CB3.2 39.16369 -76.30631 0.21227297932700306
CB3.2 39.16369 -76.30631 0.21387857255544146
CB3.2 39.16369 -76.30631 0.21696891642237193
CB3.2 39.16369 -76.30631 0.21900524578632033
CB3.2 39.16369 -76.30631 0.22430967666457458
CB3.2 39.16369 -76.30631 0.2252621224285436
CB3.2 39.16369 -76.30631 0.2259366038444787
CB3.2 39.16369 -76.30631 0.22953894985588957
CB3.2 39.16369 -76.30631 0.23048188090070276
CB3.2 39.16369 -76.30631 0.2347957248741775
CB3.2 39.16369 -76.30631 0.23541152949569488
CB3.2 39.16369 -76.30631 0.23659449344984207
CB3.2 39.16369 -76.30631 0.23986101012966857
CB3.2 39.16369 -76.30631 0.24229078525000403
CB3.2 39.16369 -76.30631 0.24543257263830084
CB3.2 39.16369 -76.30631 0.24545314065712298
CB3.2 39.16369 -76.30631 0.2462061136552568
CB3.2 39.16369 -76.30631 0.24672267239515225
CB3.2 39.16369 -76.30631 0.24781116108163664
CB3.2 39.16369 -76.30631 0.2579354337316644
CB3.2 39.16369 -76.30631 0.29683472453923204
CB3.2 39.16369 -76.30631 0.2976926791716733
CB3.2 39.16369 -76.30631 0.3139189952060631
CB3.2 39.16369 -76.30631 0.3285349120034184
CB3.2 39.16369 -76.30631 0.3596091739741977
CB3.2 39.16369 -76.30631 0.36970866733995256
CB3.2 39.16369 -76.30631 0.37003950335885955
CB3.2 39.16369 -76.30631 0.37503096865772045
CB3.2 39.16369 -76.30631 0.38153580860133074
CB3.2 39.16369 -76.30631 0.4062800528028224
CB3.2 39.16369 -76.30631 0.41439924340333395
CB3.2 39.16369 -76.30631 0.4189834529483327
CB3.2 39.16369 -76.30631 0.4404023139721315
CB3.2 39.16369 -76.30631 0.4568277431740501
CB3.2 39.16369 -76.30631 0.4603515440588335
CB3.2 39.16369 -76.30631 0.4603991571689131
CB3.2 39.16369 -76.30631 0.46286514646851795
CB3.2 39.16369 -76.30631 0.47357790135531813
CB3.2 39.16369 -76.30631 0.49243606478319646
CB3.2 39.16369 -76.30631 0.4935702288755348
CB3.2 39.16369 -76.30631 0.4967059620138898
CB3.2 39.16369 -76.30631 0.5196564281591161
CB3.2 39.16369 -76.30631 0.5263450315849763
CB3.2 39.16369 -76.30631 0.5294469505820469
CB3.2 39.16369 -76.30631 0.5585656528277239
CB3.2 39.16369 -76.30631 0.5793386344189725
CB3.2 39.16369 -76.30631 0.6073586690550494
CB3.2 39.16369 -76.30631 0.6414615738547411
CB3.2 39.16369 -76.30631 0.7740180168908449
CB3.2 39.16369 -76.30631 0.7857125895345222
CB3.2 39.16369 -76.30631 0.8114499031823537
CB3.2 39.16369 -76.30631 1.548401205826683
CB3.2 39.16369 -76.30631 2.1302356289471738
CB3.2 39.16369 -76.30631 2.338428553372226
CB3.2 39.16369 -76.30631 2.371726110779007
CB3.2 39.16369 -76.30631 2.4753892514093

In total, there are 185 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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