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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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LDEO-HPD: Lamont-Doherty Earth Observatory Hybrid Physics Data pCO2 Product

Authors: Gloege, Lucas; Yan, Monica; Zheng, Tian; McKinley, Galen A.;

LDEO-HPD: Lamont-Doherty Earth Observatory Hybrid Physics Data pCO2 Product

Abstract

Lamont-Doherty Earth Observatory Hybrid Physics Data (LDEO-HPD) This collection contains the Lamont-Doherty Earth Observatory Hybrid Physics Data (LDEO-HPD) product. This product makes near-global monthly estimates of surface ocean pCO2 from January 1982 through December 2018 with a 1ºx1º spatial resolution. LDEO-HPD uses an eXtreme Gradient Boosting (XGB) algorithm to make estimates of the misfit between observations and mode-based estimates. These spatiotemporal misfit estimates are then added back to the model-based estimate to make the final LDEO-HPD estimate. This is done for each of nine models part of the Global Carbon Budget 2020. Air-sea CO2 flux is calculated using a bulk parameterization, which is a function of wind speed. Three wind speed products are used to estimate flux. The average across these three estimates is taken as the best estimate. Datasets in this collection: LDEO-HPD_error_v20210425_1x1_198201-201812.nc : contains estimates of the misfit from each model LDEO-HPD_spco2_v20210425_1x1_198201-201812.nc : contains estimates of surface ocean pCO2 for each model LDEO-HPD_fgco2_v20210425_1x1_198201-201812.nc : contains estimates of air-sea CO2 flux for each model and wind product

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Keywords

xgboost, machine learning, carbon, global carbon budget, pco2, ocean

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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