BCO-DMO ERDDAP
Accessing BCO-DMO data 		log in    
Brought to you by BCO-DMO    
 
 
Row Type Variable Name Attribute Name Data Type Value
attribute NC_GLOBAL cdm_data_type String Other
attribute NC_GLOBAL Conventions String COARDS, CF-1.6, ACDD-1.3
attribute NC_GLOBAL creator_email String info at bco-dmo.org
attribute NC_GLOBAL creator_name String BCO-DMO
attribute NC_GLOBAL creator_url String https://www.bco-dmo.org/ (external link)
attribute NC_GLOBAL doi String 10.26008/1912/bco-dmo.885506.2
attribute NC_GLOBAL Easternmost_Easting double 359.5
attribute NC_GLOBAL geospatial_lat_max double 89.5
attribute NC_GLOBAL geospatial_lat_min double -77.5
attribute NC_GLOBAL geospatial_lat_units String degrees_north
attribute NC_GLOBAL geospatial_lon_max double 359.5
attribute NC_GLOBAL geospatial_lon_min double 0.5
attribute NC_GLOBAL geospatial_lon_units String degrees_east
attribute NC_GLOBAL infoUrl String https://www.bco-dmo.org/dataset/885506 (external link)
attribute NC_GLOBAL institution String BCO-DMO
attribute NC_GLOBAL license String The data may be used and redistributed for free but is not intended\nfor legal use, since it may contain inaccuracies. Neither the data\nContributor, ERD, NOAA, nor the United States Government, nor any\nof their employees or contractors, makes any warranty, express or\nimplied, including warranties of merchantability and fitness for a\nparticular purpose, or assumes any legal liability for the accuracy,\ncompleteness, or usefulness, of this information.
attribute NC_GLOBAL Northernmost_Northing double 89.5
attribute NC_GLOBAL sourceUrl String (local files)
attribute NC_GLOBAL Southernmost_Northing double -77.5
attribute NC_GLOBAL summary String We present a spatially and vertically resolved global grid of dissolved barium concentrations ([Ba]) in seawater determined using Gaussian Process Regression machine learning. This model was trained using 4,345 quality-controlled GEOTRACES data from the Arctic, Atlantic, Pacific, and Southern Oceans. Model output was validated by assessing the accuracy of [Ba] simulations in the Indian Ocean, noting that none of the Indian Ocean data were seen by the model during training. We identify a model that can accurate predict [Ba] in the Indian Ocean using seven features: depth, temperature, salinity, as well as dissolved dioxygen, phosphate, nitrate, and silicate concentrations. This model achieves a mean absolute percentage error of 6.0 %, which we assume represents the generalization error. This model was used to simulate [Ba] on a global basis using predictor data from the World Ocean Atlas 2018. The global model of [Ba] is on a 1°x 1° grid with 102 depth levels from 0 to 5,500 m. The dissolved [Ba] output was then used to simulate dissolved Ba* (barium-star), which is the difference between 'observed' and [Ba] predicted from co-located [Si]. Lastly, [Ba] data were combined with temperature, salinity, and pressure data from the World Ocean Atlas to calculate the saturation state of seawater with respect to barite. The model reveals that the volume-weighted mean oceanic [Ba] and and saturation state are 89 nmol/kg and 0.82, respectively. These results imply that the total marine Ba inventory is 122(±7) ×10¹² mol and that the ocean below 1,000 m is at barite equilibrium.
attribute NC_GLOBAL title String [Distribution of dissolved barium in seawater determined using machine learning] - A spatially and vertically resolved global grid of dissolved barium concentrations in seawater determined using Gaussian Process Regression machine learning (The Speed, Signature, and Significance of Barium Transformations in Seawater)
attribute NC_GLOBAL Westernmost_Easting double 0.5
variable Station int
attribute Station actual_range int 1, 41088
attribute Station long_name String Station
attribute Station units String unitless
variable longitude float
attribute longitude _CoordinateAxisType String Lon
attribute longitude actual_range float 0.5, 359.5
attribute longitude axis String X
attribute longitude ioos_category String Location
attribute longitude long_name String Longitude_degreese
attribute longitude standard_name String longitude
attribute longitude units String degrees_east
variable latitude float
attribute latitude _CoordinateAxisType String Lat
attribute latitude actual_range float -77.5, 89.5
attribute latitude axis String Y
attribute latitude ioos_category String Location
attribute latitude long_name String Latitude_degreesn
attribute latitude standard_name String latitude
attribute latitude units String degrees_north
variable Depth_m int
attribute Depth_m actual_range int 0, 5500
attribute Depth_m long_name String Depth_m
attribute Depth_m units String meters (m)
variable dBa_nmol_kg float
attribute dBa_nmol_kg long_name String Dba_nmol_kg
attribute dBa_nmol_kg units String nanomoles per kilogram (nmol/kg)
variable omega_Ba float
attribute omega_Ba long_name String Omega_ba
attribute omega_Ba units String unitless
variable Ba_star_nmol_kg float
attribute Ba_star_nmol_kg actual_range float -27.19973, 27.89195
attribute Ba_star_nmol_kg long_name String Ba_star_nmol_kg
attribute Ba_star_nmol_kg units String nanomoles per kilogram (nmol/kg)

 
ERDDAP, Version 2.22
Disclaimers | Privacy Policy | Contact