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Dataset Title:	Carbon, Nitrogen, biogenic silica, thorium-234, and mass fluxes from upper ocean sediment traps at the Porcupine Abyssal Plain Sustained Observatory (PAP- SO) site in the Northeast Atlantic Ocean during RRS Discovery cruise DY077 in April of 2017
Institution:	BCO-DMO   (Dataset ID: bcodmo_dataset_765835)
Information:	Summary | License | ISO 19115 | Metadata | Background | Files | Make a graph

 

Variable	Optional Constraint #1		Optional Constraint #2		Minimum	Maximum
deployment (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		1	2
station (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		22	73
platform (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"NBST200"	"STT"
collector (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"NBST_tube"	"PIT_tube_modified"
collection_area (meters squared (m^2))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.00385	0.1156
replicates (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		1	3
depth (m)	!= =~ <= >= = < >		!= =~ <= >= = < >		200.0	350.0
latitude (degrees_north)	!= =~ <= >= = < >		!= =~ <= >= = < >		48.9575	48.9943
longitude (degrees_east)	!= =~ <= >= = < >		!= =~ <= >= = < >		-16.363	-16.3234
lat_recover (Latitude, decimal degrees (DD))	!= =~ <= >= = < >		!= =~ <= >= = < >		48.8198	49.2422
lon_recover (Longitude, decimal degrees (DD))	!= =~ <= >= = < >		!= =~ <= >= = < >		-16.7132	-16.59
date_start (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"2017-04-19"	"2017-04-26"
time_start (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"12:00:00"	"9:31:00"
time (ISO Date Time Start, UTC)	!= =~ <= >= = < >		!= =~ <= >= = < >		2017-04-19T09:00:00Z	2017-04-26T02:30:00Z
date_end (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"2017-04-21"	"2017-04-27"
time_end (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"0:00:00"	"8:30:00"
date_recover (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"2017-04-21"	"2017-04-27"
time_recover (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"16:00:00"	"8:30:00"
deploy_length (number of days)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.79	2.96
N_f_mean (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.114	0.8
N_f_err_mean (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.001	0.5
N_f_A (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.114	0.548
N_f_err_A (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.001	0.02
N_f_B (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.128	1.32
N_f_err_B (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.001	0.02
N_f_C (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.114	0.625
N_f_err_C (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.001	0.02
N_f_D (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	0.317
N_f_err_D (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	0.02
TC_f_mean (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.9	5.6
TC_f_err_mean (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.01	3.5
TC_f_A (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.89	4.7
TC_f_err_A (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.01	0.2
TC_f_B (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		1.02	9.6
TC_f_err_B (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.01	0.2
TC_f_C (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.9	4.8
TC_f_err_C (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.01	0.2
TC_f_D (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		2.7	3.2
TC_f_err_D (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.04	0.2
PIC_f_mean (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		81	1236
PIC_f_err_mean (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		2	782
PIC_f_A (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		80	2137
PIC_f_err_A (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		2	30
PIC_f_B (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		83	1097
PIC_f_err_B (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		2	30
PIC_f_C (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		78	1220
PIC_f_err_C (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		2	30
PIC_f_D (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		678	878
PIC_f_err_D (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		8	30
POC_f_mean (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.8	5.2
POC_f_err_mean (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	3.5
POC_f_A (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		1.1	3.3
POC_f_err_A (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.01	0.2
POC_f_B (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.86	9.21
POC_f_err_B (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.01	0.2
POC_f_C (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.82	4.4
POC_f_err_C (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.01	0.2
POC_f_D (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		2.0	2.4
POC_f_err_D (millimoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.04	0.2
bSi_f_mean (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		110	615
bSi_f_err_mean (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		11	129
bSi_f_E (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		25	617
bSi_f_err_E (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		2	29
bSi_f_F (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		120	685
bSi_f_err_F (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		2	29
bSi_f_G (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		66	889
bSi_f_err_G (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		2	29
bSi_f_H (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		214	577
bSi_f_err_H (micromoles per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		7	29
Mass_f_mean (milligrams per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		53	341
Mass_f_err_mean (milligrams per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		5	62
Mass_f_E (milligrams per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		44	290
Mass_f_err_E (milligrams per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0	5
Mass_f_F (milligrams per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		48	401
Mass_f_err_F (milligrams per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0	5
Mass_f_G (milligrams per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		56	322
Mass_f_err_G (milligrams per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		0	5
Mass_f_H (milligrams per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		139	380
Mass_f_err_H (milligrams per meter squared per day (mmol/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		1	5
Th234_f_mean (disintegration per minute per meter squared per day (dpm/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		129	1071
Th234_f_err_mean (disintegration per minute per meter squared per day (dpm/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		16	159
Th234_f_A (disintegration per minute per meter squared per day (dpm/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		127	1052
Th234_f_err_A (disintegration per minute per meter squared per day (dpm/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		5	57
Th234_f_B (disintegration per minute per meter squared per day (dpm/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		132	1117
Th234_f_err_B (disintegration per minute per meter squared per day (dpm/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		6	51
Th234_f_C (disintegration per minute per meter squared per day (dpm/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		115	1043
Th234_f_err_C (disintegration per minute per meter squared per day (dpm/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		7	48
Th234_f_D (disintegration per minute per meter squared per day (dpm/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		605	888
Th234_f_err_D (disintegration per minute per meter squared per day (dpm/m^2/d))	!= =~ <= >= = < >		!= =~ <= >= = < >		20	51

 

Server-side Functions

distinct()

orderBy orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean (" deployment station platform collector collection_area replicates depth latitude longitude lat_recover lon_recover date_start time_start time date_end time_end date_recover time_recover deploy_length N_f_mean N_f_err_mean N_f_A N_f_err_A N_f_B N_f_err_B N_f_C N_f_err_C N_f_D N_f_err_D TC_f_mean TC_f_err_mean TC_f_A TC_f_err_A TC_f_B TC_f_err_B TC_f_C TC_f_err_C TC_f_D TC_f_err_D PIC_f_mean PIC_f_err_mean PIC_f_A PIC_f_err_A PIC_f_B PIC_f_err_B PIC_f_C PIC_f_err_C PIC_f_D PIC_f_err_D POC_f_mean POC_f_err_mean POC_f_A POC_f_err_A POC_f_B POC_f_err_B POC_f_C POC_f_err_C POC_f_D POC_f_err_D bSi_f_mean bSi_f_err_mean bSi_f_E bSi_f_err_E bSi_f_F bSi_f_err_F bSi_f_G bSi_f_err_G bSi_f_H bSi_f_err_H Mass_f_mean Mass_f_err_mean Mass_f_E Mass_f_err_E Mass_f_F Mass_f_err_F Mass_f_G Mass_f_err_G Mass_f_H Mass_f_err_H Th234_f_mean Th234_f_err_mean Th234_f_A Th234_f_err_A Th234_f_B Th234_f_err_B Th234_f_C Th234_f_err_C Th234_f_D Th234_f_err_D deployment station platform collector collection_area replicates depth latitude longitude lat_recover lon_recover date_start time_start time date_end time_end date_recover time_recover deploy_length N_f_mean N_f_err_mean N_f_A N_f_err_A N_f_B N_f_err_B N_f_C N_f_err_C N_f_D N_f_err_D TC_f_mean TC_f_err_mean TC_f_A TC_f_err_A TC_f_B TC_f_err_B TC_f_C TC_f_err_C TC_f_D TC_f_err_D PIC_f_mean PIC_f_err_mean PIC_f_A PIC_f_err_A PIC_f_B PIC_f_err_B PIC_f_C PIC_f_err_C PIC_f_D PIC_f_err_D POC_f_mean POC_f_err_mean POC_f_A POC_f_err_A POC_f_B POC_f_err_B POC_f_C POC_f_err_C POC_f_D POC_f_err_D bSi_f_mean bSi_f_err_mean bSi_f_E bSi_f_err_E bSi_f_F bSi_f_err_F bSi_f_G bSi_f_err_G bSi_f_H bSi_f_err_H Mass_f_mean Mass_f_err_mean Mass_f_E Mass_f_err_E Mass_f_F Mass_f_err_F Mass_f_G Mass_f_err_G Mass_f_H Mass_f_err_H Th234_f_mean Th234_f_err_mean Th234_f_A Th234_f_err_A Th234_f_B Th234_f_err_B Th234_f_C Th234_f_err_C Th234_f_D Th234_f_err_D deployment station platform collector collection_area replicates depth latitude longitude lat_recover lon_recover date_start time_start time date_end time_end date_recover time_recover deploy_length N_f_mean N_f_err_mean N_f_A N_f_err_A N_f_B N_f_err_B N_f_C N_f_err_C N_f_D N_f_err_D TC_f_mean TC_f_err_mean TC_f_A TC_f_err_A TC_f_B TC_f_err_B TC_f_C TC_f_err_C TC_f_D TC_f_err_D PIC_f_mean PIC_f_err_mean PIC_f_A PIC_f_err_A PIC_f_B PIC_f_err_B PIC_f_C PIC_f_err_C PIC_f_D PIC_f_err_D POC_f_mean POC_f_err_mean POC_f_A POC_f_err_A POC_f_B POC_f_err_B POC_f_C POC_f_err_C POC_f_D POC_f_err_D bSi_f_mean bSi_f_err_mean bSi_f_E bSi_f_err_E bSi_f_F bSi_f_err_F bSi_f_G bSi_f_err_G bSi_f_H bSi_f_err_H Mass_f_mean Mass_f_err_mean Mass_f_E Mass_f_err_E Mass_f_F Mass_f_err_F Mass_f_G Mass_f_err_G Mass_f_H Mass_f_err_H Th234_f_mean Th234_f_err_mean Th234_f_A Th234_f_err_A Th234_f_B Th234_f_err_B Th234_f_C Th234_f_err_C Th234_f_D Th234_f_err_D deployment station platform collector collection_area replicates depth latitude longitude lat_recover lon_recover date_start time_start time date_end time_end date_recover time_recover deploy_length N_f_mean N_f_err_mean N_f_A N_f_err_A N_f_B N_f_err_B N_f_C N_f_err_C N_f_D N_f_err_D TC_f_mean TC_f_err_mean TC_f_A TC_f_err_A TC_f_B TC_f_err_B TC_f_C TC_f_err_C TC_f_D TC_f_err_D PIC_f_mean PIC_f_err_mean PIC_f_A PIC_f_err_A PIC_f_B PIC_f_err_B PIC_f_C PIC_f_err_C PIC_f_D PIC_f_err_D POC_f_mean POC_f_err_mean POC_f_A POC_f_err_A POC_f_B POC_f_err_B POC_f_C POC_f_err_C POC_f_D POC_f_err_D bSi_f_mean bSi_f_err_mean bSi_f_E bSi_f_err_E bSi_f_F bSi_f_err_F bSi_f_G bSi_f_err_G bSi_f_H bSi_f_err_H Mass_f_mean Mass_f_err_mean Mass_f_E Mass_f_err_E Mass_f_F Mass_f_err_F Mass_f_G Mass_f_err_G Mass_f_H Mass_f_err_H Th234_f_mean Th234_f_err_mean Th234_f_A Th234_f_err_A Th234_f_B Th234_f_err_B Th234_f_C Th234_f_err_C Th234_f_D Th234_f_err_D deployment station platform collector collection_area replicates depth latitude longitude lat_recover lon_recover date_start time_start time date_end time_end date_recover time_recover deploy_length N_f_mean N_f_err_mean N_f_A N_f_err_A N_f_B N_f_err_B N_f_C N_f_err_C N_f_D N_f_err_D TC_f_mean TC_f_err_mean TC_f_A TC_f_err_A TC_f_B TC_f_err_B TC_f_C TC_f_err_C TC_f_D TC_f_err_D PIC_f_mean PIC_f_err_mean PIC_f_A PIC_f_err_A PIC_f_B PIC_f_err_B PIC_f_C PIC_f_err_C PIC_f_D PIC_f_err_D POC_f_mean POC_f_err_mean POC_f_A POC_f_err_A POC_f_B POC_f_err_B POC_f_C POC_f_err_C POC_f_D POC_f_err_D bSi_f_mean bSi_f_err_mean bSi_f_E bSi_f_err_E bSi_f_F bSi_f_err_F bSi_f_G bSi_f_err_G bSi_f_H bSi_f_err_H Mass_f_mean Mass_f_err_mean Mass_f_E Mass_f_err_E Mass_f_F Mass_f_err_F Mass_f_G Mass_f_err_G Mass_f_H Mass_f_err_H Th234_f_mean Th234_f_err_mean Th234_f_A Th234_f_err_A Th234_f_B Th234_f_err_B Th234_f_C Th234_f_err_C Th234_f_D Th234_f_err_D ")

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---

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  deployment {
    Byte _FillValue 127;
    Byte actual_range 1, 2;
    String bcodmo_name "deploy";
    String description "deployment cycle during cruise DY077";
    String long_name "Deployment";
    String units "unitless";
  }
  station {
    Byte _FillValue 127;
    Byte actual_range 22, 73;
    String bcodmo_name "station";
    String description "station occupied during cruise DY077";
    String long_name "Station";
    String units "unitless";
  }
  platform {
    String bcodmo_name "platform";
    String description "type of sediment trap deployed";
    String long_name "Platform";
    String units "unitless";
  }
  collector {
    String bcodmo_name "sample_descrip";
    String description "type of particle collector deployed on sediment trap platform";
    String long_name "Collector";
    String units "unitless";
  }
  collection_area {
    Float32 _FillValue NaN;
    Float32 actual_range 0.00385, 0.1156;
    String bcodmo_name "site_descrip";
    String description "area of collector opening";
    String long_name "Collection Area";
    String units "meters squared (m^2)";
  }
  replicates {
    Byte _FillValue 127;
    Byte actual_range 1, 3;
    String bcodmo_name "sample_descrip";
    String description "number of collectors installed on platform at given depth";
    String long_name "Replicates";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 200.0, 350.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "target depth of sediment trap collectors";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 48.9575, 48.9943;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude of platform deployment";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String source_name "lat_deploy";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -16.363, -16.3234;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude of platform deployment";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String source_name "lon_deploy";
    String standard_name "longitude";
    String units "degrees_east";
  }
  lat_recover {
    Float32 _FillValue NaN;
    Float32 actual_range 48.8198, 49.2422;
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude of platform recovery";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "decimal degrees (DD)";
  }
  lon_recover {
    Float32 _FillValue NaN;
    Float32 actual_range -16.7132, -16.59;
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude of platform recovery";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "decimal degrees (DD)";
  }
  date_start {
    String bcodmo_name "date_utc";
    String description "date sampling began (GMT) in ISO 8601 format yyyy-mm-dd";
    String long_name "Date Start";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  time_start {
    String bcodmo_name "time_utc";
    String description "time sampling began (GMT) in ISO 8601 format hh:mm:ss";
    String long_name "Time Start";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.4925924e+9, 1.4931738e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Date time sampling began (GMT) in format yyyy-mm-ddTHH:MMZ";
    String ioos_category "Time";
    String long_name "ISO Date Time Start";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String source_name "ISO_DateTime_start";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  date_end {
    String bcodmo_name "date_utc";
    String description "date of collector lid closure or platform recovery (GMT) in ISO 8601 format yyyy-mm-dd";
    String long_name "Date End";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  time_end {
    String bcodmo_name "time_utc";
    String description "time of collector lid closure or platform recovery (GMT) in ISO 8601 format hh:mm:ss";
    String long_name "Time End";
    String units "unitless";
  }
  date_recover {
    String bcodmo_name "date_utc";
    String description "date of platform recovery (GMT) in ISO 8601 format yyyy-mm-dd";
    String long_name "Date Recover";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  time_recover {
    String bcodmo_name "time_utc";
    String description "time of platform recovery (GMT) in ISO 8601 format hh:mm:ss";
    String long_name "Time Recover";
    String units "unitless";
  }
  deploy_length {
    Float32 _FillValue NaN;
    Float32 actual_range 0.79, 2.96;
    String bcodmo_name "time_elapsed";
    String description "length of sampling period";
    String long_name "Deploy Length";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ELTMZZZZ/";
    String units "number of days";
  }
  N_f_mean {
    Float32 _FillValue NaN;
    Float32 actual_range 0.114, 0.8;
    String bcodmo_name "N";
    String description "mean total nitrogen flux of splits A, B, C, D";
    String long_name "N F Mean";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  N_f_err_mean {
    Float32 _FillValue NaN;
    Float32 actual_range 0.001, 0.5;
    String bcodmo_name "N";
    String description "total nitrogen flux uncertainty, propagated from the maximum of either the per-filter analytical error or the standard deviation among replicate filter splits";
    String long_name "N F Err Mean";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  N_f_A {
    Float32 _FillValue NaN;
    Float32 actual_range 0.114, 0.548;
    String bcodmo_name "N";
    String description "total nitrogen flux of split A";
    String long_name "N F A";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  N_f_err_A {
    Float32 _FillValue NaN;
    Float32 actual_range 0.001, 0.02;
    String bcodmo_name "N";
    String description "total nitrogen flux uncertainty of split A, propagated from the per-filter analytical error";
    String long_name "N F Err A";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  N_f_B {
    Float32 _FillValue NaN;
    Float32 actual_range 0.128, 1.32;
    String bcodmo_name "N";
    String description "total nitrogen flux of split B";
    String long_name "N F B";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  N_f_err_B {
    Float32 _FillValue NaN;
    Float32 actual_range 0.001, 0.02;
    String bcodmo_name "N";
    String description "total nitrogen flux uncertainty of split B, propagated from the per-filter analytical error";
    String long_name "N F Err B";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  N_f_C {
    Float32 _FillValue NaN;
    Float32 actual_range 0.114, 0.625;
    String bcodmo_name "N";
    String description "total nitrogen flux of split C";
    String long_name "N F C";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  N_f_err_C {
    Float32 _FillValue NaN;
    Float32 actual_range 0.001, 0.02;
    String bcodmo_name "N";
    String description "total nitrogen flux uncertainty of split C, propagated from the per-filter analytical error";
    String long_name "N F Err C";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  N_f_D {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.317;
    String bcodmo_name "N";
    String description "total nitrogen flux of split D";
    String long_name "N F D";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  N_f_err_D {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.02;
    String bcodmo_name "N";
    String description "total nitrogen flux uncertainty of split D, propagated from the per-filter analytical error";
    String long_name "N F Err D";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  TC_f_mean {
    Float32 _FillValue NaN;
    Float32 actual_range 0.9, 5.6;
    String bcodmo_name "C";
    String description "mean total carbon flux of splits A, B, C, D";
    String long_name "TC F Mean";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  TC_f_err_mean {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 3.5;
    String bcodmo_name "C";
    String description "total carbon flux uncertainty, propagated from the maximum of either the per-filter analytical error or the standard deviation among replicate filter splits";
    String long_name "TC F Err Mean";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  TC_f_A {
    Float32 _FillValue NaN;
    Float32 actual_range 0.89, 4.7;
    String bcodmo_name "C";
    String description "total carbon flux of split A";
    String long_name "TC F A";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  TC_f_err_A {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 0.2;
    String bcodmo_name "C";
    String description "total carbon flux uncertainty of split A, propagated from the per-filter analytical error";
    String long_name "TC F Err A";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  TC_f_B {
    Float32 _FillValue NaN;
    Float32 actual_range 1.02, 9.6;
    String bcodmo_name "C";
    String description "total carbon flux of split B";
    String long_name "TC F B";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  TC_f_err_B {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 0.2;
    String bcodmo_name "C";
    String description "total carbon flux uncertainty of split B, propagated from the per-filter analytical error";
    String long_name "TC F Err B";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  TC_f_C {
    Float32 _FillValue NaN;
    Float32 actual_range 0.9, 4.8;
    String bcodmo_name "C";
    String description "total carbon flux of split C";
    String long_name "TC F C";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  TC_f_err_C {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 0.2;
    String bcodmo_name "C";
    String description "total carbon flux uncertainty of split C, propagated from the per-filter analytical error";
    String long_name "TC F Err C";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  TC_f_D {
    Float32 _FillValue NaN;
    Float32 actual_range 2.7, 3.2;
    String bcodmo_name "C";
    String description "total carbon flux of split D";
    String long_name "TC F D";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  TC_f_err_D {
    Float32 _FillValue NaN;
    Float32 actual_range 0.04, 0.2;
    String bcodmo_name "C";
    String description "total carbon flux uncertainty of split D, propagated from the per-filter analytical error";
    String long_name "TC F Err D";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  PIC_f_mean {
    Int16 _FillValue 32767;
    Int16 actual_range 81, 1236;
    String bcodmo_name "PIC";
    String description "mean particulate inorganic carbon flux of splits A, B, C, D";
    String long_name "PIC F Mean";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  PIC_f_err_mean {
    Int16 _FillValue 32767;
    Int16 actual_range 2, 782;
    String bcodmo_name "PIC";
    String description "particulate inorganic carbon flux uncertainty, propagated from the maximum of either the per-filter analytical error or the standard deviation among replicate filter splits";
    String long_name "PIC F Err Mean";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  PIC_f_A {
    Int16 _FillValue 32767;
    Int16 actual_range 80, 2137;
    String bcodmo_name "PIC";
    String description "particulate inorganic carbon flux of split A";
    String long_name "PIC F A";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  PIC_f_err_A {
    Byte _FillValue 127;
    Byte actual_range 2, 30;
    String bcodmo_name "PIC";
    String description "particulate inorganic carbon flux uncertainty of split A, propagated from the per-filter analytical error";
    String long_name "PIC F Err A";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  PIC_f_B {
    Int16 _FillValue 32767;
    Int16 actual_range 83, 1097;
    String bcodmo_name "PIC";
    String description "particulate inorganic carbon flux of split B";
    String long_name "PIC F B";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  PIC_f_err_B {
    Byte _FillValue 127;
    Byte actual_range 2, 30;
    String bcodmo_name "PIC";
    String description "particulate inorganic carbon flux uncertainty of split B, propagated from the per-filter analytical error";
    String long_name "PIC F Err B";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  PIC_f_C {
    Int16 _FillValue 32767;
    Int16 actual_range 78, 1220;
    String bcodmo_name "PIC";
    String description "particulate inorganic carbon flux of split C";
    String long_name "PIC F C";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  PIC_f_err_C {
    Byte _FillValue 127;
    Byte actual_range 2, 30;
    String bcodmo_name "PIC";
    String description "particulate inorganic carbon flux uncertainty of split C, propagated from the per-filter analytical error";
    String long_name "PIC F Err C";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  PIC_f_D {
    Int16 _FillValue 32767;
    Int16 actual_range 678, 878;
    String bcodmo_name "PIC";
    String description "particulate inorganic carbon flux of split D";
    String long_name "PIC F D";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  PIC_f_err_D {
    Byte _FillValue 127;
    Byte actual_range 8, 30;
    String bcodmo_name "PIC";
    String description "particulate inorganic carbon flux uncertainty of split D, propagated from the per-filter analytical error";
    String long_name "PIC F Err D";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  POC_f_mean {
    Float32 _FillValue NaN;
    Float32 actual_range 0.8, 5.2;
    String bcodmo_name "POC";
    String description "mean particulate organic carbon flux,computed as the difference between mean TC flux and mean PIC flux";
    String long_name "POC F Mean";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  POC_f_err_mean {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 3.5;
    String bcodmo_name "POC";
    String description "particulate organic carbon flux uncertainty, POC_f_err_mean = (TC_f_err_mean^2 + PIC_f_err_mean^2)1/2";
    String long_name "POC F Err Mean";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  POC_f_A {
    Float32 _FillValue NaN;
    Float32 actual_range 1.1, 3.3;
    String bcodmo_name "POC";
    String description "particulate organic carbon flux of split A, computed as the difference between TC flux and PIC flux of split A";
    String long_name "POC F A";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  POC_f_err_A {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 0.2;
    String bcodmo_name "POC";
    String description "particulate organic carbon flux uncertainty of split A,POC_f_err_A = (TC_f_err_A^2 + PIC_f_err_A^2)1/2";
    String long_name "POC F Err A";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  POC_f_B {
    Float32 _FillValue NaN;
    Float32 actual_range 0.86, 9.21;
    String bcodmo_name "POC";
    String description "particulate organic carbon flux of split B, computed as the difference between TC flux and PIC flux of split B";
    String long_name "POC F B";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  POC_f_err_B {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 0.2;
    String bcodmo_name "POC";
    String description "particulate organic carbon flux uncertainty of split B,POC_f_err_B = (TC_f_err_B^2 + PIC_f_err_B^2)1/2";
    String long_name "POC F Err B";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  POC_f_C {
    Float32 _FillValue NaN;
    Float32 actual_range 0.82, 4.4;
    String bcodmo_name "POC";
    String description "particulate organic carbon flux of split C, computed as the difference between TC flux and PIC flux of split C";
    String long_name "POC F C";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  POC_f_err_C {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 0.2;
    String bcodmo_name "POC";
    String description "particulate organic carbon flux uncertainty of split C,POC_f_err_C = (TC_f_err_C^2 + PIC_f_err_C^2)1/2";
    String long_name "POC F Err C";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  POC_f_D {
    Float32 _FillValue NaN;
    Float32 actual_range 2.0, 2.4;
    String bcodmo_name "POC";
    String description "particulate organic carbon flux of split D, computed as the difference between TC flux and PIC flux of split D";
    String long_name "POC F D";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  POC_f_err_D {
    Float32 _FillValue NaN;
    Float32 actual_range 0.04, 0.2;
    String bcodmo_name "POC";
    String description "particulate organic carbon flux uncertainty of split D,POC_f_err_D = (TC_f_err_D^2 + PIC_f_err_D^2)1/2";
    String long_name "POC F Err D";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
    String units "millimoles per meter squared per day (mmol/m^2/d)";
  }
  bSi_f_mean {
    Int16 _FillValue 32767;
    Int16 actual_range 110, 615;
    String bcodmo_name "Si_bio";
    String description "mean biogenic silica flux of splits E, F, G, H";
    String long_name "B Si F Mean";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  bSi_f_err_mean {
    Int16 _FillValue 32767;
    Int16 actual_range 11, 129;
    String bcodmo_name "Si_bio";
    String description "biogenic silica flux uncertainty,propagated from the maximum of either the per-filter analytical error or the standard deviation among replicate filter splits";
    String long_name "B Si F Err Mean";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  bSi_f_E {
    Int16 _FillValue 32767;
    Int16 actual_range 25, 617;
    String bcodmo_name "Si_bio";
    String description "biogenic silica flux of split E";
    String long_name "B Si F E";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  bSi_f_err_E {
    Byte _FillValue 127;
    Byte actual_range 2, 29;
    String bcodmo_name "Si_bio";
    String description "biogenic silica flux uncertainty of split E,propagated from the per-filter analytical error";
    String long_name "B Si F Err E";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  bSi_f_F {
    Int16 _FillValue 32767;
    Int16 actual_range 120, 685;
    String bcodmo_name "Si_bio";
    String description "biogenic silica flux of split F";
    String long_name "B Si F F";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  bSi_f_err_F {
    Byte _FillValue 127;
    Byte actual_range 2, 29;
    String bcodmo_name "Si_bio";
    String description "biogenic silica flux uncertainty of split F,propagated from the per-filter analytical error";
    String long_name "B Si F Err F";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  bSi_f_G {
    Int16 _FillValue 32767;
    Int16 actual_range 66, 889;
    String bcodmo_name "Si_bio";
    String description "biogenic silica flux of split G";
    String long_name "B Si F G";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  bSi_f_err_G {
    Byte _FillValue 127;
    Byte actual_range 2, 29;
    String bcodmo_name "Si_bio";
    String description "biogenic silica flux uncertainty of split G,propagated from the per-filter analytical error";
    String long_name "B Si F Err G";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  bSi_f_H {
    Int16 _FillValue 32767;
    Int16 actual_range 214, 577;
    String bcodmo_name "Si_bio";
    String description "biogenic silica flux of split H";
    String long_name "B Si F H";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  bSi_f_err_H {
    Byte _FillValue 127;
    Byte actual_range 7, 29;
    String bcodmo_name "Si_bio";
    String description "biogenic silica flux uncertainty of split H,propagated from the per-filter analytical error";
    String long_name "B Si F Err H";
    String units "micromoles per meter squared per day (mmol/m^2/d)";
  }
  Mass_f_mean {
    Int16 _FillValue 32767;
    Int16 actual_range 53, 341;
    String bcodmo_name "unknown";
    String description "mean mass flux of splits E, F, G, H";
    String long_name "Mass F Mean";
    String units "milligrams per meter squared per day (mmol/m^2/d)";
  }
  Mass_f_err_mean {
    Byte _FillValue 127;
    Byte actual_range 5, 62;
    String bcodmo_name "unknown";
    String description "mass flux uncertainty,propagated from the maximum of either the per-filter analytical error or the standard deviation among replicate filter splits";
    String long_name "Mass F Err Mean";
    String units "milligrams per meter squared per day (mmol/m^2/d)";
  }
  Mass_f_E {
    Int16 _FillValue 32767;
    Int16 actual_range 44, 290;
    String bcodmo_name "unknown";
    String description "mass flux of split E";
    String long_name "Mass F E";
    String units "milligrams per meter squared per day (mmol/m^2/d)";
  }
  Mass_f_err_E {
    Byte _FillValue 127;
    Byte actual_range 0, 5;
    String bcodmo_name "unknown";
    String description "mass flux uncertainty of split E,propagated from the per-filter analytical error";
    String long_name "Mass F Err E";
    String units "milligrams per meter squared per day (mmol/m^2/d)";
  }
  Mass_f_F {
    Int16 _FillValue 32767;
    Int16 actual_range 48, 401;
    String bcodmo_name "unknown";
    String description "mass flux of split F";
    String long_name "Mass F F";
    String units "milligrams per meter squared per day (mmol/m^2/d)";
  }
  Mass_f_err_F {
    Byte _FillValue 127;
    Byte actual_range 0, 5;
    String bcodmo_name "unknown";
    String description "mass flux uncertainty of split F,propagated from the per-filter analytical error";
    String long_name "Mass F Err F";
    String units "milligrams per meter squared per day (mmol/m^2/d)";
  }
  Mass_f_G {
    Int16 _FillValue 32767;
    Int16 actual_range 56, 322;
    String bcodmo_name "unknown";
    String description "mass flux of split G";
    String long_name "Mass F G";
    String units "milligrams per meter squared per day (mmol/m^2/d)";
  }
  Mass_f_err_G {
    Byte _FillValue 127;
    Byte actual_range 0, 5;
    String bcodmo_name "unknown";
    String description "mass flux uncertainty of split G,propagated from the per-filter analytical error";
    String long_name "Mass F Err G";
    String units "milligrams per meter squared per day (mmol/m^2/d)";
  }
  Mass_f_H {
    Int16 _FillValue 32767;
    Int16 actual_range 139, 380;
    String bcodmo_name "unknown";
    String description "mass flux of split H";
    String long_name "Mass F H";
    String units "milligrams per meter squared per day (mmol/m^2/d)";
  }
  Mass_f_err_H {
    Byte _FillValue 127;
    Byte actual_range 1, 5;
    String bcodmo_name "unknown";
    String description "mass flux uncertainty of split H,propagated from the per-filter analytical error";
    String long_name "Mass F Err H";
    String units "milligrams per meter squared per day (mmol/m^2/d)";
  }
  Th234_f_mean {
    Int16 _FillValue 32767;
    Int16 actual_range 129, 1071;
    String bcodmo_name "thorium-234";
    String description "mean thorium-234 flux of splits A, B, C, D";
    String long_name "Th234 F Mean";
    String units "disintegration per minute per meter squared per day (dpm/m^2/d)";
  }
  Th234_f_err_mean {
    Int16 _FillValue 32767;
    Int16 actual_range 16, 159;
    String bcodmo_name "thorium-234";
    String description "thorium-234 uncertainty,propagated from the standard deviation among replicate filter splits";
    String long_name "Th234 F Err Mean";
    String units "disintegration per minute per meter squared per day (dpm/m^2/d)";
  }
  Th234_f_A {
    Int16 _FillValue 32767;
    Int16 actual_range 127, 1052;
    String bcodmo_name "thorium-234";
    String description "thorium-234 flux of split A";
    String long_name "Th234 F A";
    String units "disintegration per minute per meter squared per day (dpm/m^2/d)";
  }
  Th234_f_err_A {
    Byte _FillValue 127;
    Byte actual_range 5, 57;
    String bcodmo_name "thorium-234";
    String description "thorium-234 uncertainty of split A, propagated from counting statistics";
    String long_name "Th234 F Err A";
    String units "disintegration per minute per meter squared per day (dpm/m^2/d)";
  }
  Th234_f_B {
    Int16 _FillValue 32767;
    Int16 actual_range 132, 1117;
    String bcodmo_name "thorium-234";
    String description "thorium-234 flux of split B";
    String long_name "TH234 F B";
    String units "disintegration per minute per meter squared per day (dpm/m^2/d)";
  }
  Th234_f_err_B {
    Byte _FillValue 127;
    Byte actual_range 6, 51;
    String bcodmo_name "thorium-234";
    String description "thorium-234 uncertainty of split B, propagated from counting statistics";
    String long_name "Th234 F Err B";
    String units "disintegration per minute per meter squared per day (dpm/m^2/d)";
  }
  Th234_f_C {
    Int16 _FillValue 32767;
    Int16 actual_range 115, 1043;
    String bcodmo_name "thorium-234";
    String description "thorium-234 flux of split C";
    String long_name "TH234 F C";
    String units "disintegration per minute per meter squared per day (dpm/m^2/d)";
  }
  Th234_f_err_C {
    Byte _FillValue 127;
    Byte actual_range 7, 48;
    String bcodmo_name "thorium-234";
    String description "thorium-234 uncertainty of split C, propagated from counting statistics";
    String long_name "Th234 F Err C";
    String units "disintegration per minute per meter squared per day (dpm/m^2/d)";
  }
  Th234_f_D {
    Int16 _FillValue 32767;
    Int16 actual_range 605, 888;
    String bcodmo_name "thorium-234";
    String description "thorium-234 flux of split D";
    String long_name "TH234 F D";
    String units "disintegration per minute per meter squared per day (dpm/m^2/d)";
  }
  Th234_f_err_D {
    Byte _FillValue 127;
    Byte actual_range 20, 51;
    String bcodmo_name "thorium-234";
    String description "thorium-234 uncertainty of split D, propagated from counting statistics";
    String long_name "Th234 F Err D";
    String units "disintegration per minute per meter squared per day (dpm/m^2/d)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Methodology:
 
Samples were collected during two deployment cycles (termed deployment 1 and
deployment 2) occupied during the RRS Discovery cruise DY077 to the Porcupine
Abyssal Plain Sustained Observatory (PAP-SO) Site in April 2017 (Figure 1). In
each of the cycles, we conducted particle flux sampling method
intercomparisons between two types of neutrally buoyant sediment traps (NBST
and PELAGRA), a surface tethered array of sediment traps (STT), and fluxes
derived from upper water column deficits of 234Th vs. its parent isotope,
238U. DY077 samples analyzed in US (WHOI and Skidmore College) are archived
here; DY077 samples analyzed in the UK (NOC) are archived in the British
Oceanographic Data Centre.
 
Neutrally Buoyant Sediment Trap (NBST)  
 NBSTs consist of four cylindrical sediment trap tubes (collection area
0.0113 m2) and a 0.25-m pathlength transmissometer (C-Rover 2000, WETLabs,
Inc.) arranged around a central SOLO profiling float. The traps are programmed
to sink to a predetermined depth, drift while collecting sedimenting
particles, close the trap lids, and then rise to the surface at a programmed
time for recovery. Recovery aids consist of GPS/Iridium and a flashing strobe
light. The transmissometer operates as an optical sediment trap and measures
attenuance flux as a function of time, which is a proxy for sinking
particulate carbon flux. For the deployments conducted on DY077, trap tubes
were set up as follows: Three tubes were prepared with a layer of 500 mL of 70
ppt brine poisoned with 0.1% formaldehyde and borate buffered to pH 8.5. This
brine layer was overlain with 1-\\u03bcm filtered seawater from 350 m. In the
fourth trap tube, a jar containing approximately 50 mL of polyacrylamide gel
replaced the brine layer and allowed preservation of collected particles for
microscopic imaging after recovery. During deployment 1, the NBST sampled at a
depth of 200 m; during deployment 2, it sampled at a depth of 350 m.
 
PELAGRA neutral sediment traps  
 The Particle Export LAGRAngian (PELAGRA) trap was designed at the National
Oceanography Centre, Southampton, UK (Lampitt et al. 2008) and consists of an
arrangement of four conical traps (collection area 0.5 m2) around an APEX
float (Teledyne-Webb Research, Inc.), with mechanically opening and closing
collection cups. For this cruise, samples were collected from three PELAGRA
traps: P4, P7, and P9. P4 and P7 each carried two conventional sediment
funnels, two non-funnelled collectors for gel sampling and a camera/flash
system for capturing time-lapse images of sinking particles. For these traps,
the two cups situated beneath the conventional funnels were filled with the
same brine solution used in the bottom of the NBST traps. Under the non-funnel
collectors, jars containing polyacrylamide gel (described above) and
commercially available cryogel were attached. P9 carried four conventional
sediment funnels, each with a brine cup installed.
 
Surface Tethered Trap (STT) arrays  
 Alongside the neutral traps was deployed a drifting mooring carrying
cylindrical sediment trap tubes set up identically to those on the NBSTs as
well as tubes of a different design provided by collaborator C. Lamborg (and
henceforth termed modified PIT tubes). Modified PIT tubes are identical to
standard PIT tubes (collection area 0.00385 m2) but with detachable bottoms.
During deployment 1 two arrays were deployed, one at 200 m and one at 350 m.
Both arrays contained two NBST-style brine-filled tubes, one NBST-style gel
tube, and two modified PIT tubes which collected samples into 125-mL bottles
filled with the same poisoned brine used in the other tubes. A programmable
burnwire controller was set up to close the NBST-style tube lids at the same
time as on the NBST traps. The burnwire controller at 200 m operated as
planned but the controller at 350 m did not, due to a hardware failure. During
the second deployment, a single trap array at 350 m was deployed using the
fully-functioning burnwire controller. Two NBST-style tubes were set up to
close at the same time as the NBSTs, two more were set up to remain open, and
a third pair of modified PIT tubes (without lids) were included. During both
deployments a Nortek current meter was deployed looking downwards
approximately 2 m below the bottom of the 350-m trap array
 
Upon platform retrieval, trap brine samples were processed as follows.  
 NBST samples and NBST-style tubes on STT: After a period of 1-3 hours to
allow particles to finish settling in trap tubes, overlying filtered seawater
was removed via peristaltic pump. The bottom brine layer was screened through
350-\\u03bcm nylon mesh to aid in swimmer removal. The replicate brine tubes
were drained through a single screen and combined. The screen was picked under
12x magnification to remove obvious swimmers while leaving behind passively
sinking particles. Material remaining on the screen was rinsed back into the
main sample while swimmers were filtered onto a QMA filter for later carbon
and thorium-234 analysis. Combined trap samples were split eight ways using a
custom rotary splitter. Splits were filtered onto QMA filters for C/N, PIC,
and 234Th analysis or polycarbonate filters for biogenic Si and mass analysis
on shore. Splits were also kept aside to return to collaborators labs at NOC.
 
Modified PIT tubes on STT: Overlying seawater was siphoned off as above, then
the 125-ml sample collection bottles were removed and combined into an extra
NBST tube used as a dispenser. The sample was processed from this point
identically to the NBST tubes.  
 PELAGRA trap samples: Brine cups were removed and either kept by the NOC lab
for parallel processing (generally cup 1 on P4 and P7 and cups 3 and 4 on P9)
or treated as described for modified PIT tubes above, minus the siphoning
step.
 
QMA filters were dried at 45C, mounted, and immediately counted for low-level
\\u03b2 emission onboard the ship. At WHOI, a subset of samples was re-counted
within one month on shore. Final background counts to measure non-234Th
related \\u03b2 emissions were conducted several months later. At this point,
QMA filters were unmounted, re-dried, and gravimetrically subdivided into four
sections. One half of the filter was analyzed for total carbon and nitrogen
after high-temperature combustion on a Thermo Electron FlashEA 1112 C/N
analyzer. Coulometric analysis for PIC after sample acidification was
performed on a quarter of the filter (Johnson et al, 1985; Honjo et al, 2000).
The remainder of the filter was archived. At Skidmore College, polycarbonate
filters for mass and bSi determination were dried and weighed repeatedly on a
microbalance until stable weights with a precision better than 0.01 mg were
achieved. Filter tare weights were subtracted and net mass accumulation was
calculated. Then the filters were digested to release bSi using a weak
alkaline digest (0.2 N NaOH for 2 hours at 95C) and analyzed following
standard spectrophotometric methods (Strickland and Parsons, 1972).
 
A replicate set of each type of trap collector was prepared as described
above, held in the shipboard laboratory during each deployment, and then
analyzed in parallel to provide a process blank determination. The blanks from
the two deployments were averaged to determine the mean process blank for the
cruise (Table 1).";
    String awards_0_award_nid "762021";
    String awards_0_award_number "OCE-1659995";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1659995";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "Dr Simone Metz";
    String awards_0_program_manager_nid "51479";
    String awards_1_award_nid "762029";
    String awards_1_award_number "OCE-1660012";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1660012";
    String awards_1_funder_name "NSF Division of Ocean Sciences";
    String awards_1_funding_acronym "NSF OCE";
    String awards_1_funding_source_nid "355";
    String awards_1_program_manager "Dr Simone Metz";
    String awards_1_program_manager_nid "51479";
    String cdm_data_type "Other";
    String comment 
"Sediment Trap Fluxes 
  Margaret Estapa 
  Data Version 3: 2019-06-26";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2019-04-29T16:15:54Z";
    String date_modified "2019-06-26T19:32:42Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.765835.3";
    Float64 Easternmost_Easting -16.3234;
    Float64 geospatial_lat_max 48.9943;
    Float64 geospatial_lat_min 48.9575;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -16.3234;
    Float64 geospatial_lon_min -16.363;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 350.0;
    Float64 geospatial_vertical_min 200.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-04-24T18:07:28Z (local files)
2024-04-24T18:07:28Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_765835.html";
    String infoUrl "https://www.bco-dmo.org/dataset/765835";
    String institution "BCO-DMO";
    String instruments_0_acronym "CO2 coulometer";
    String instruments_0_dataset_instrument_nid "766190";
    String instruments_0_description "A CO2 coulometer semi-automatically controls the sample handling and extraction of CO2 from seawater samples. Samples are acidified and the CO2 gas is bubbled into a titration cell where CO2 is converted to hydroxyethylcarbonic acid which is then automatically titrated with a coulometrically-generated base to a colorimetric endpoint.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB12";
    String instruments_0_instrument_name "CO2 Coulometer";
    String instruments_0_instrument_nid "507";
    String instruments_0_supplied_name "Coulometer";
    String instruments_1_acronym "Sediment Trap";
    String instruments_1_dataset_instrument_description "PELAGRA, Particle Export LAGRAngian sediment traps, NOC: The PELAGRA trap was designed at the National Oceanography Centre, Southampton, UK (Lampitt et al. 2008) and consists of an arrangement of four conical traps (collection area 0.5 m2) around an APEX float (Teledyne-Webb Research, Inc.) with mechanically opening and closing collection cups.";
    String instruments_1_dataset_instrument_nid "766186";
    String instruments_1_description "Sediment traps are specially designed containers deployed in the water column for periods of time to collect particles from the water column falling toward the sea floor. In general a sediment trap has a jar at the bottom to collect the sample and a broad funnel-shaped opening at the top with baffles to keep out very large objects and help prevent the funnel from clogging. This designation is used when the specific type of sediment trap was not specified by the contributing investigator.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/33/";
    String instruments_1_instrument_name "Sediment Trap";
    String instruments_1_instrument_nid "518";
    String instruments_1_supplied_name "Particle Export LAGRAngian sediment traps (PELAGRA)";
    String instruments_2_acronym "Sediment Trap";
    String instruments_2_dataset_instrument_description "STT, surface tethered trap, WHOI";
    String instruments_2_dataset_instrument_nid "766187";
    String instruments_2_description "Sediment traps are specially designed containers deployed in the water column for periods of time to collect particles from the water column falling toward the sea floor. In general a sediment trap has a jar at the bottom to collect the sample and a broad funnel-shaped opening at the top with baffles to keep out very large objects and help prevent the funnel from clogging. This designation is used when the specific type of sediment trap was not specified by the contributing investigator.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/33/";
    String instruments_2_instrument_name "Sediment Trap";
    String instruments_2_instrument_nid "518";
    String instruments_2_supplied_name "surface tethered trap (STT)";
    String instruments_3_acronym "NBST";
    String instruments_3_dataset_instrument_nid "766185";
    String instruments_3_description "In general, sediment traps are specially designed containers deployed in the water  column for periods of time to collect particles from the water column  falling toward the sea floor. The Neutrally Buoyant Sediment Trap (NBST) was designed by researchers at Woods Hole Oceanographic Institution. The central cylinder of the NBST controls buoyancy and houses a satellite transmitter. The other tubes collect sediment as the trap drifts in currents at a predetermined depth. The samples are collected when the tubes snap shut before the trap returns to the surface. (more: https://www.whoi.edu/instruments/viewInstrument.do?id=10286)";
    String instruments_3_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/33/";
    String instruments_3_instrument_name "Neutrally Buoyant Sediment Trap";
    String instruments_3_instrument_nid "632";
    String instruments_3_supplied_name "NBST, neutrally buoyant sediment trap, WHOI";
    String instruments_4_acronym "Riso Beta Counter";
    String instruments_4_dataset_instrument_nid "766188";
    String instruments_4_description 
"Low-level beta detectors manufactured by Riso (now Nutech) in Denmark. These instruments accept samples that can be mounted on a 25mm filter holder. These detectors have very low backgrounds, 0.17 counts per minute, and can have counting efficiencies as high as 55%.

See:
http://cafethorium.whoi.edu/website/about/services_radioanalytical_facility_equip.html
and
http://www.nutech.dtu.dk/Produkter/Dosimetri/NUK_instruments/GM_multicounter.aspx";
    String instruments_4_instrument_name "Riso Laboratory Anti-coincidence Beta Counters";
    String instruments_4_instrument_nid "687";
    String instruments_4_supplied_name "Riso Beta Counter";
    String instruments_5_acronym "Spectrophotometer";
    String instruments_5_dataset_instrument_nid "766191";
    String instruments_5_description "An instrument used to measure the relative absorption of electromagnetic radiation of different wavelengths in the near infra-red, visible and ultraviolet wavebands by samples.";
    String instruments_5_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB20/";
    String instruments_5_instrument_name "Spectrophotometer";
    String instruments_5_instrument_nid "707";
    String instruments_5_supplied_name "Spectrophotometer";
    String instruments_6_dataset_instrument_nid "766189";
    String instruments_6_description "Instruments that quantify carbon, nitrogen and sometimes other elements by combusting the sample at very high temperature and assaying the resulting gaseous oxides. Usually used for samples including organic material.";
    String instruments_6_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB01/";
    String instruments_6_instrument_name "Elemental Analyzer";
    String instruments_6_instrument_nid "546339";
    String instruments_6_supplied_name "Thermo Electron FlashEA 1112 C/N analyzer";
    String keywords "area, bco, bco-dmo, biological, bSi_f_E, bSi_f_err_E, bSi_f_err_F, bSi_f_err_G, bSi_f_err_H, bSi_f_err_mean, bSi_f_F, bSi_f_G, bSi_f_H, bSi_f_mean, chemical, collection, collection_area, collector, data, dataset, date, date_end, date_recover, date_start, deploy, deploy_length, deployment, depth, dmo, end, erddap, error, iso, lat_recover, latitude, length, lon_recover, longitude, management, mass, Mass_f_E, Mass_f_err_E, Mass_f_err_F, Mass_f_err_G, Mass_f_err_H, Mass_f_err_mean, Mass_f_F, Mass_f_G, Mass_f_H, Mass_f_mean, mean, N_f_A, N_f_B, N_f_C, N_f_D, N_f_err_A, N_f_err_B, N_f_err_C, N_f_err_D, N_f_err_mean, N_f_mean, oceanography, office, pic, PIC_f_A, PIC_f_B, PIC_f_C, PIC_f_D, PIC_f_err_A, PIC_f_err_B, PIC_f_err_C, PIC_f_err_D, PIC_f_err_mean, PIC_f_mean, platform, poc, POC_f_A, POC_f_B, POC_f_C, POC_f_D, POC_f_err_A, POC_f_err_B, POC_f_err_C, POC_f_err_D, POC_f_err_mean, POC_f_mean, preliminary, recover, replicates, start, station, TC_f_A, TC_f_B, TC_f_C, TC_f_D, TC_f_err_A, TC_f_err_B, TC_f_err_C, TC_f_err_D, TC_f_err_mean, TC_f_mean, th234, Th234_f_A, Th234_f_B, Th234_f_C, Th234_f_D, Th234_f_err_A, Th234_f_err_B, Th234_f_err_C, Th234_f_err_D, Th234_f_err_mean, Th234_f_mean, time, time_end, time_recover, time_start";
    String license "https://www.bco-dmo.org/dataset/765835/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/765835";
    Float64 Northernmost_Northing 48.9943;
    String param_mapping "{'765835': {'lat_deploy': 'master - latitude', 'depth': 'master - depth', 'ISO_DateTime_start': 'master - time', 'lon_deploy': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/765835/parameters";
    String people_0_affiliation "Skidmore College";
    String people_0_person_name "Margaret L. Estapa";
    String people_0_person_nid "644830";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI";
    String people_1_person_name "Kenneth O. Buesseler";
    String people_1_person_nid "50522";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Southampton";
    String people_2_person_name "Dr Richard Lampitt";
    String people_2_person_nid "50764";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Amber York";
    String people_3_person_nid "643627";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Are Traps Equal";
    String projects_0_acronym "Are Traps Equal";
    String projects_0_description 
"NSF Award Abstract:
There is considerable need to understand the biological and ecological processes that through net primary production fix dissolved carbon dioxide (CO2) into organic matter in the upper ocean, and the processes that subsequently transport this organic carbon in to the ocean's interior. Most of the particulate organic carbon flux to the deep ocean is thought to be mediated by sinking particles. Ultimately it is the deep organic carbon transport and its sequestration that define the impact of ocean biota on atmospheric CO2 levels and hence climate. Currently, various methods are available to measure the amount of particles in the ocean that sink over a specified period of time commonly referred to as particle flux. Unfortunately, all of these methods are used independently of each other with very little intercomparison, leaving some uncertainty as to which approach provides the most accurate estimates. This study seeks to be the first concerted effort to standardize particle flux measurements. Seeking to keep the cost modest, the researchers are taking advantage of a collaboration with scientists in the United Kingdom to participate in an already scheduled research cruise. The proposed research will have much greater impact that merely standardization of particle flux measurements because it will provide the science and modeling community the ability to quantify the transfer of carbon throughout the surface ocean. Also, this project provides a variety of mentoring and training opportunities for students. A PhD student at Woods Hole Oceanographic Institute will get their first sea-going experience and will learn all of the processing steps for the study of an isotope of thorium (234Th). Skidmore College will have an undergraduate participant in the research and the results from the cruise will also be an excellent additional component for undergraduate oceanography classes.
Researchers from Woods Hole Oceanographic Institution and Skidmore College, in collaboration with a scientist from the National Oceanography Centre, Southampton will inter-compare direct, tracer, and optical-sensor methods used to determine sinking particle fluxes in the surface ocean. To do this, they will firstly conduct a comparison of two types of neutrally buoyant traps and one surface-tethered, drifting array. Secondly, measured trap fluxes will be compared to predicted 234Th fluxes from a 3D time-series of data. Lastly, optical sediment trap measurements will be compared to particle size distributions in the water column and gel traps, as well as size-fractionated particles on filters from large volume pumps. With this research, global ocean models, particularly carbon, will have greater accuracy and stronger conclusions will be able to be drawn from them.";
    String projects_0_end_date "2019-06";
    String projects_0_geolocation "Porcupine Abyssal Plain Sustained Observatory (PAP-SO) site in the Northeast Atlantic Ocean (49°N, 16.5°W)";
    String projects_0_name "Collaborative Research:   Are all traps created equal?  A multi-method assessment of the collection and detection of sinking particles in the ocean";
    String projects_0_project_nid "762022";
    String projects_0_start_date "2017-01";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 48.9575;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Carbon, Nitrogen, biogenic silica, thorium-234, and mass fluxes from upper ocean sediment traps at the Porcupine Abyssal Plain Sustained Observatory (PAP-SO) site in the Northeast Atlantic Ocean during RRS Discovery cruise DY077 in April of 2017.";
    String time_coverage_end "2017-04-26T02:30:00Z";
    String time_coverage_start "2017-04-19T09:00:00Z";
    String title "Carbon, Nitrogen, biogenic silica, thorium-234, and mass fluxes from upper ocean sediment traps at the Porcupine Abyssal Plain Sustained Observatory (PAP-SO) site in the Northeast Atlantic Ocean during RRS Discovery cruise DY077 in April of 2017";
    String version "3";
    Float64 Westernmost_Easting -16.363;
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

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Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP Data Access Protocol (DAP) and its selection constraints.

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

• (easy) You can get data by using the dataset's Data Access Form or Subset form. They make the URL for you.
• (easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
• (not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.

 

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