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Found 1 dataset matching "in particular the Global Ocean Monitoring and Observations program (fund reference 100007298)".

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#1 Federal
AOML_ET: Partial pressure of CO2 (pCO2) and sea-air CO2 fluxes for the global ocean, along with the predictor variables from 1998-01-01 to 2023-12-30, using an Extra Trees (extremely randomized trees) machine learning (NCEI Accession 0298989)
- Organization: National Oceanic and Atmospheric Administration, Department of Commerce
- Updated: 2024-11-21T00:00:00.000+00:00
This dataset contains global surface water partial pressure of CO2 data, pCO2w data, and sea-air CO2 fluxes based on the extremely randomized trees or extra trees, ET machine learning approach....
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Search relevance: 76.67 | Views last month: 0

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AOML_ET: Partial pressure of CO2 (pCO2) and sea-air CO2 fluxes for the global ocean, along with the predictor variables from 1998-01-01 to 2023-12-30, using an Extra Trees (extremely randomized trees) machine learning (NCEI Accession 0298989)