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WhoFromWhatNotes

Markus Reichstein

Max-Planck-Institute for Biogeochemistry
 WMO-G3W

Welcome, Motivation, some overview

Gianpaolo Balsamo

WMO-ECMWF

The Global Greenhouse Gas Watch in short

View file
nameG3W_intro_short_final.pdf
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Dario Papale

National Research Council Italy

GHGs Ecosystem level observations status


Philippe Ciais

LSCE, France

Near real time carbon budgets from multiple data-streams – first results


Mathew Williams

Uni of Edinburgh, UK

Reanalysis of ecological carbon dynamics – potential links to AI approaches


Vitus Benson

MPI BGC

GNNs for atmospheric transport of CO2


Christian Lessig

ECMWF

Large scale machine learning based Earth system models (foundation models, AtmoRep)


Matthew Chantry

ECMWF

AIFS and beyond


Anna Agusti-Panareda

ECMWF

Considerations for CO2 AIFS


Further readings

  • The systematic carbon observations and the needs for policy-relevant carbon monitoring (Ciais et al. 2014)
  • The satellite and insitu observations for advancing Earth surface modelling: A review (Balsamo et al. 2018)
  • The first steps towards an operational predictions capacity of the near-term climate (Kushnir et al. 2019)
  • The European vision for a CO2MVS - CO2 Monitoring & Verification Support (Janssens-Maenhout et al. 2020)
  • The quantification of CO2 - Carbon dioxide emissions reduction during the COVID-19 (Le Queré et al. 2021)
  • The CHE - CO2 Human Emissions: First steps towards European operational capacity (Balsamo et al. 2021)
  • The quantification of CH4 - Methane emissions from hotspots and during COVID-19 (McNorton et al. 2022)
  • The Copernicus Atmosphere Monitoring Service European GHGs reanalysis (Agusti-Panareda et al. 2023)
  • The European synthesis of CH4 & N2O emissions for EU27 and UK: 1990–2019 (Petrescu et al., 2023)
  • The European synthesis of CO2 emissions and removals for EU27 and UK: 1990–2020 (McGrath et al. 2023)
  • PLEASE ADD BELOW OTHERS Papers relevant for "AI for Carbon-Meteorology?" here with similar reporting style

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