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Record W2397224232 · doi:10.5194/gmd-10-1131-2017

A joint global carbon inversion system using both CO <sub>2</sub> and <sup>13</sup> CO <sub>2</sub> atmospheric concentration data

2017· article· en· W2397224232 on OpenAlex
Jing M. Chen, Gang Mo, Feng Deng

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGeoscientific model development · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Toronto
FundersNational Oceanic and Atmospheric AdministrationMinistry of Science and Technology of the People's Republic of ChinaCanadian Foundation for Climate and Atmospheric SciencesU.S. Department of Energy
KeywordsDisequilibriumEnvironmental scienceSink (geography)Carbon fluxInversion (geology)Carbon sinkAtmospheric sciencesPhotosynthesisSpatial distributionEcosystemClimatologyClimate changeOceanographyChemistryGeologyEcologyBiologyGeography

Abstract

fetched live from OpenAlex

Abstract. Observations of 13CO2 at 73 sites compiled in the GLOBALVIEW database are used for an additional constraint in a global atmospheric inversion of the surface CO2 flux using CO2 observations at 210 sites (62 collocated with 13CO2 sites) for the 2002–2004 period for 39 land regions and 11 ocean regions. This constraint is implemented using prior CO2 fluxes estimated with a terrestrial ecosystem model and an ocean model. These models simulate 13CO2 discrimination rates of terrestrial photosynthesis and ocean–atmosphere diffusion processes. In both models, the 13CO2 disequilibrium between fluxes to and from the atmosphere is considered due to the historical change in atmospheric 13CO2 concentration. This joint inversion system using both13CO2 and CO2 observations is effectively a double deconvolution system with consideration of the spatial variations of isotopic discrimination and disequilibrium. Compared to the CO2-only inversion, this 13CO2 constraint on the inversion considerably reduces the total land carbon sink from 3.40 ± 0.84 to 2.53 ± 0.93 Pg C year−1 but increases the total oceanic carbon sink from 1.48 ± 0.40 to 2.36 ± 0.49 Pg C year−1. This constraint also changes the spatial distribution of the carbon sink. The largest sink increase occurs in the Amazon, while the largest source increases are in southern Africa, and Asia, where CO2 data are sparse. Through a case study, in which the spatial distribution of the annual 13CO2 discrimination rate over land is ignored by treating it as a constant at the global average of −14. 1 ‰, the spatial distribution of the inverted CO2 flux over land was found to be significantly modified (up to 15 % for some regions). The uncertainties in our disequilibrium flux estimation are 8.0 and 12.7 Pg C year−1 ‰ for land and ocean, respectively. These uncertainties induced the unpredictability of 0.47 and 0.54 Pg C year−1 in the inverted CO2 fluxes for land and ocean, respectively. Our joint inversion system is therefore useful for improving the partitioning between ocean and land sinks and the spatial distribution of the inverted carbon flux.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.224
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it