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Record W3199112589 · doi:10.1016/j.rse.2021.112688

The Monitoring Nitrous Oxide Sources (MIN2OS) satellite project

2021· article· en· W3199112589 on OpenAlexaff
Philippe Ricaud, Jean‐Luc Attié, Rémi Chalinel, F. Pasternak, Joël Léonard, Isabelle Pison, Elizabeth Pattey, Rona L. Thompson, Zdeněk Zelinger, Jos Lelieveld, Jean Sciare, Naoko Saitoh, J. X. Warner, Audrey Fortems‐Cheiney, Hélène Reynal, Jérôme Vidot, Laure Brooker, Laurent Berdeu, Olivier Saint-Pé, Prabir K. Patra, Michal Dostál, Jan Suchánek, Václav Nevrlý, Christine Groot Zwaaftink

Bibliographic record

VenueRemote Sensing of Environment · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsNational Association of Friendship CentresAgriculture and Agri-Food Canada
FundersInstitut national des sciences de l'UniversNational Oceanic and Atmospheric AdministrationRégion Occitanie Pyrénées-MéditerranéeAirbus Defense and SpaceCentre National de la Recherche ScientifiqueCentre National d’Etudes SpatialesEuropean Space AgencyNational Aeronautics and Space Administration
KeywordsEnvironmental scienceNitrous oxideRemote sensingSatelliteInversion (geology)Atmospheric sciencesMeteorologyGeologyPhysics

Abstract

fetched live from OpenAlex

The Monitoring Nitrous Oxide Sources (MIN2OS) satellite project aims at monitoring global-scale nitrous oxide (N2O) sources by retrieving N2O surface fluxes from the inversion of space-borne N2O measurements that are sensitive to the lowermost atmospheric layers under favorable conditions. MIN2OS will provide emission estimates of N2O at a horizontal resolution of 1° × 1° on the global scale and 10 × 10 km2 on the regional scale on a weekly to monthly basis depending on the application (e.g., agriculture, national inventories, policy, scientific research). Our novel approach is based on the development of: 1) a space-borne instrument operating in the Thermal InfraRed domain providing, in clear sky conditions, N2O mixing ratio in the lowermost atmosphere (900 hPa) under favorable conditions (summer daytime) over land and under favorable and unfavorable (winter nighttime) conditions over the ocean and 2) an atmospheric inversion framework to estimate N2O surface fluxes from the atmospheric satellite observations. After studying three N2O spectral bands (B1 at 1240–1350 cm−1, B2 at 2150–2260 cm−1 and B3 at 2400–2600 cm−1), a new TIR instrument will be developed, centered at 1250–1330 cm−1, with a resolution of 0.125 cm−1, a Full Width at Half Maximum of 0.25 cm−1 and a swath of 300 km. To optimally constrain the retrieval of N2O vertical profiles, the instrument will be on-board a platform at ~830 km altitude in a sun-synchronous orbit crossing the Equator in descending node at 09:30 local time in synergy with two other platforms (Metop-SG and Sentinel-2 NG) expected to fly in 2031–32 aiming at detecting surface properties, agricultural information on the field scale and vertical profiles of atmospheric constituents and temperature. The lifetime of the MIN2OS project would be 4–5 years to study the interannual variability of N2O surface fluxes. The spectral noise can be decreased by at least a factor of 5 compared to the lowest noise accessible to date with the Infrared Atmospheric Sounding Interferometer-New Generation (IASI-NG) mission. The N2O total error is expected to be less than ~1% (~3 ppbv) along the vertical. The preliminary design of the MIN2OS project results in a small instrument (payload of 90 kg, volume of 1200 × 600 × 300 mm3) with, in addition to the spectrometer, a wide field and 1-km resolution imager for cloud detection. The instruments could be hosted on a small platform, the whole satellite being largely compatible with a dual launch on VEGA-C. The MIN2OS project has been submitted to the European Space Agency Earth Explorer 11 mission ideas.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.211
Teacher spread0.201 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations22
Published2021
Admission routes1
Has abstractyes

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