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Record W4322010439 · doi:10.5194/egusphere-egu23-13301

CoMet 2.0 Arctic: Carbon Dioxide and Methane Mission for HALO

2023· preprint· en· W4322010439 on OpenAlexaboutno aff
Andreas Fix, H. Bovensmann, Christoph Gerbig, Sven Krautwurst, Michał Gałkowski, Quatrevalet Mathieu, C. Fruck, Sebastian Wolff, Friedemann Reum, Paul Waldmann, Florian Ewald, Bernhard Mayer, Patrick Jöckel, Christoph Kiemle, Charles E. Miller, and the CoMet . Arctic team

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceArcticPermafrostGreenhouse gasCometAstrobiologyOceanographyGeology

Abstract

fetched live from OpenAlex

In order to reliably predict the climate of our planet, and to help inform political conventions on greenhouse gas emissions such as the Paris Agreement of 2015, adequate knowledge of both natural and anthropogenic sources of the greenhouse gases Carbon dioxide (CO2) and methane (CH4) and their feedbacks is needed. Despite the recognized importance of this issue, our current understanding about sources and sinks of CO2 and CH4 is still inadequate. This is particularly true for the Arctic, where large wetlands and permafrost areas constitute the most relevant but least quantified ecosystems for the global carbon budget.The CoMet 2.0 Arctic mission wants to help remedy this deficiency with a multi-disciplinary approach providing relevant measurements from Arctic regions using a suite of sophisticated scientific instrumentation onboard the German research aircraft HALO (High Altitude and LOng Range Research Aircraft, https://halo-research.de) to support state-of-the-art Earth System Models. At the same time, CoMet intends to support and improve current and future satellite missions, which still struggle to make high-quality measurements given the low sun elevation, low albedo, and adverse cloud conditions in the Arctic.CoMet 2.0 Arctic (https://comet2arctic.de/) has successfully been conducted within a six-week intensive operation period from August 10th to September 16th, 2022 targeting greenhouse gas emissions from boreal wetlands and permafrost areas in the Canadian Arctic, from wildfires, and from anthropogenic emission sources such oil, gas, and coal extraction sites and landfills.For that mission, HALO was equipped with a suite of remote sensing and in-situ instruments for the measurement of greenhouse gases and meteorological parameters. The remote sensing package comprised the CH4 and CO2 lidar CHARM-F (operated by DLR), the imaging spectrometer MAMAP2D-Light (operated by University of Bremen) and the hyperspectral imager specMACS (operated by LMU Munich). The remote sensors were supported by several in-situ instruments (operated by MPI Jena and DLR) to measure the main greenhouse gases and related trace species as well as an air sampler that collects air samples at flight level for later analysis (e.g. w.r.t. isotopes) in the laboratory. Furthermore, instruments to provide detailed information about the standard meteorological parameters (pressure, wind, humidity) were operated and several small meteorological sondes were launched in order to link those in-flight data to profiles.A total of 135 flight hours including a test flight to landfills in Spain and transfer flights from Europe have been performed. 16 scientific flights took place out of Edmonton, Alberta, to various regions all over Canada.CoMet 2.0 Arctic has partly been coordinated with the Arctic-Boreal Vulnerability Experiment field program by NASA (ABoVE, https://above.nasa.gov/). Both missions, ABoVE and CoMet 2.0 Arctic, are linked through the transatlantic initiative AMPAC (Arctic Methane and Permafrost Challenge, https://www.ampac-net.info/) that has recently been inaugurated by the US and European Space Agencies, NASA and ESA.Thus, a valuable data set was acquired to help better understand the methane and carbon dioxide cycles in the Arctic and emissions from natural and anthropogenic sources.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.007

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 head0.023
GPT teacher head0.251
Teacher spread0.228 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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