File(s) | Type | Description | Action |
---|---|---|---|
noble_gas_obs.csv (437.12 KB) | Comma Separated Values (.csv) | Primary data file for dataset ID 675575 | Download |
This dataset includes:
1) noble gas observations used in the ECCO noble gas model. They were collected globally at sea and were analyzed by mass spectrometry.
(2) model simulations decomposed to isolate bubble-mediated gas exchange.
Noble Gas Observations:
The observation data is provided in MATLAB format: noblegasDB.mat (download here) (size = 94 KB)
The variables are a MATLAB table ‘NGall’ and a list of original references ‘NGprojects’
The served data is provided in jgofs format with the columns slightly rearranged for database best practices.
Global Model Simulations:
The simulation file is provided in MATLAB format: ECCOv2_NobleGases.mat (download here) (size = 1 GB)
Noble gases and nitrogen were simulated in the Estimating the Circulation & Climate of the Ocean (ECCO) global ocean state estimate utilizing a matrix-free Newton–Krylov (MFNK) scheme to efficiently compute the periodic seasonal solutions for noble gas tracers.
Original simulations:
sim1 = diffusive gas exchange only
sim2 = diffusive gas exchange and bubble injection
sim3 = diffusive gas exchange and bubble exchange
DG = sim1
IG = sim2-sim1
EG = sim3-sim1
For each gas ‘G’ total gas concentration is calculated as Gsol(S,T) * (AG + BG + CG)
DG is results of the simulation with no bubbles, while IG and EG are the isolated contribution from bubble injection and bubble exchange, respectively.
Nicholson, D. P., Khatiwala, S., Stanley, R. (2017) Noble gas global observations used in the ECCO noble gas model and simulations decomposed to isolate bubble-mediated gas exchange (Noble gas modeling project). Biological and Chemical Oceanography Data Management Office (BCO-DMO). Version Date 2017-01-23 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/675575 [access date]
Terms of Use
This dataset is licensed under Creative Commons Attribution 4.0.
If you wish to use this dataset, it is highly recommended that you contact the original principal investigators (PI). Should the relevant PI be unavailable, please contact BCO-DMO (info@bco-dmo.org) for additional guidance. For general guidance please see the BCO-DMO Terms of Use document.