Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement

Anna Agustí-Panareda; Joe McNorton; Gianpaolo Balsamo; Bianca C. Baier; Nicolas Bousserez; Souhail Boussetta; Frédéric Chevallier; Margarita Choulga; Michail Diamantakis; Richard Engelen; Johannes Flemming; Claire Granier; Marc Guevara; Hugo Denier van der Gon; Nellie Elguindi; Jean Matthieu Haussaire; Martin Jung; Greet Janssens-Maenhout; Rigel Kivi; Sébastien Massart; Dario Papale; Mark Parrington; Miha Razinger; Colm Sweeney; Alex Vermeulen; Sophia Walther

doi:10.1038/s41597-022-01228-2

Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement

Anna Agustí-Panareda, Joe McNorton, Gianpaolo Balsamo, Bianca C. Baier, Nicolas Bousserez, Souhail Boussetta, Frédéric Chevallier, Margarita Choulga, Michail Diamantakis, Richard Engelen, Johannes Flemming, Claire Granier, Marc Guevara, Hugo Denier van der Gon, Nellie Elguindi, Jean Matthieu Haussaire, Martin Jung, Greet Janssens-Maenhout, Rigel Kivi, Sébastien MassartDario Papale, Mark Parrington, Miha Razinger, Colm Sweeney, Alex Vermeulen, Sophia Walther

Research output: Contribution to journal › Article › peer-review

Abstract

The CO₂ Human Emissions project has generated realistic high-resolution 9 km global simulations for atmospheric carbon tracers referred to as nature runs to foster carbon-cycle research applications with current and planned satellite missions, as well as the surge of in situ observations. Realistic atmospheric CO₂, CH₄ and CO fields can provide a reference for assessing the impact of proposed designs of new satellites and in situ networks and to study atmospheric variability of the tracers modulated by the weather. The simulations spanning 2015 are based on the Copernicus Atmosphere Monitoring Service forecasts at the European Centre for Medium Range Weather Forecasts, with improvements in various model components and input data such as anthropogenic emissions, in preparation of a CO₂ Monitoring and Verification Support system. The relative contribution of different emissions and natural fluxes towards observed atmospheric variability is diagnosed by additional tagged tracers in the simulations. The evaluation of such high-resolution model simulations can be used to identify model deficiencies and guide further model improvements.

Original language	English
Article number	160
Journal	Scientific Data
Volume	9
Issue number	1
DOIs	https://doi.org/10.1038/s41597-022-01228-2
Publication status	Published - 2022 Dec

Bibliographical note

Funding Information:
The Copernicus Atmosphere Monitoring Service is operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European Commission as part of the Copernicus Programme ( http://copernicus.eu ). The CHE and CoCO2 projects have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 776186 and No 958927. We also thank the FLUXNET and TCCON PIs for providing the data used for the validation of the nature run dataset.

Funding Information:
The Copernicus Atmosphere Monitoring Service is operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European Commission as part of the Copernicus Programme (http://copernicus.eu). The CHE and CoCO2 projects have received funding from the European Union?s Horizon 2020 research and innovation programme under grant agreement No 776186 and No 958927. We also thank the FLUXNET and TCCON PIs for providing the data used for the validation of the nature run dataset.

Publisher Copyright:
© 2022, The Author(s).

Subject classification (UKÄ)

Meteorology and Atmospheric Sciences
Climate Research

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s41597-022-01228-2Licence: CC BY

Cite this

Agustí-Panareda, A., McNorton, J., Balsamo, G., Baier, B. C., Bousserez, N., Boussetta, S., Chevallier, F., Choulga, M., Diamantakis, M., Engelen, R., Flemming, J., Granier, C., Guevara, M., Denier van der Gon, H., Elguindi, N., Haussaire, J. M., Jung, M., Janssens-Maenhout, G., Kivi, R., ... Walther, S. (2022). Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement. Scientific Data, 9(1), Article 160. https://doi.org/10.1038/s41597-022-01228-2

@article{5c695eb038ee4c04830f0b121a4b6913,

title = "Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement",

abstract = "The CO2 Human Emissions project has generated realistic high-resolution 9 km global simulations for atmospheric carbon tracers referred to as nature runs to foster carbon-cycle research applications with current and planned satellite missions, as well as the surge of in situ observations. Realistic atmospheric CO2, CH4 and CO fields can provide a reference for assessing the impact of proposed designs of new satellites and in situ networks and to study atmospheric variability of the tracers modulated by the weather. The simulations spanning 2015 are based on the Copernicus Atmosphere Monitoring Service forecasts at the European Centre for Medium Range Weather Forecasts, with improvements in various model components and input data such as anthropogenic emissions, in preparation of a CO2 Monitoring and Verification Support system. The relative contribution of different emissions and natural fluxes towards observed atmospheric variability is diagnosed by additional tagged tracers in the simulations. The evaluation of such high-resolution model simulations can be used to identify model deficiencies and guide further model improvements.",

author = "Anna Agust{\'i}-Panareda and Joe McNorton and Gianpaolo Balsamo and Baier, {Bianca C.} and Nicolas Bousserez and Souhail Boussetta and Fr{\'e}d{\'e}ric Chevallier and Margarita Choulga and Michail Diamantakis and Richard Engelen and Johannes Flemming and Claire Granier and Marc Guevara and {Denier van der Gon}, Hugo and Nellie Elguindi and Haussaire, {Jean Matthieu} and Martin Jung and Greet Janssens-Maenhout and Rigel Kivi and S{\'e}bastien Massart and Dario Papale and Mark Parrington and Miha Razinger and Colm Sweeney and Alex Vermeulen and Sophia Walther",

note = "Funding Information: The Copernicus Atmosphere Monitoring Service is operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European Commission as part of the Copernicus Programme ( http://copernicus.eu ). The CHE and CoCO2 projects have received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement No 776186 and No 958927. We also thank the FLUXNET and TCCON PIs for providing the data used for the validation of the nature run dataset. Funding Information: The Copernicus Atmosphere Monitoring Service is operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European Commission as part of the Copernicus Programme (http://copernicus.eu). The CHE and CoCO2 projects have received funding from the European Union?s Horizon 2020 research and innovation programme under grant agreement No 776186 and No 958927. We also thank the FLUXNET and TCCON PIs for providing the data used for the validation of the nature run dataset. Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = dec,

doi = "10.1038/s41597-022-01228-2",

language = "English",

volume = "9",

journal = "Scientific Data",

issn = "2052-4463",

publisher = "Nature Publishing Group",

number = "1",

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Agustí-Panareda, A, McNorton, J, Balsamo, G, Baier, BC, Bousserez, N, Boussetta, S, Chevallier, F, Choulga, M, Diamantakis, M, Engelen, R, Flemming, J, Granier, C, Guevara, M, Denier van der Gon, H, Elguindi, N, Haussaire, JM, Jung, M, Janssens-Maenhout, G, Kivi, R, Massart, S, Papale, D, Parrington, M, Razinger, M, Sweeney, C, Vermeulen, A & Walther, S 2022, 'Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement', Scientific Data, vol. 9, no. 1, 160. https://doi.org/10.1038/s41597-022-01228-2

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T1 - Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement

AU - Agustí-Panareda, Anna

AU - McNorton, Joe

AU - Balsamo, Gianpaolo

AU - Baier, Bianca C.

AU - Bousserez, Nicolas

AU - Boussetta, Souhail

AU - Chevallier, Frédéric

AU - Choulga, Margarita

AU - Diamantakis, Michail

AU - Engelen, Richard

AU - Flemming, Johannes

AU - Granier, Claire

AU - Guevara, Marc

AU - Denier van der Gon, Hugo

AU - Elguindi, Nellie

AU - Haussaire, Jean Matthieu

AU - Jung, Martin

AU - Janssens-Maenhout, Greet

AU - Kivi, Rigel

AU - Massart, Sébastien

AU - Papale, Dario

AU - Parrington, Mark

AU - Razinger, Miha

AU - Sweeney, Colm

AU - Vermeulen, Alex

AU - Walther, Sophia

N1 - Funding Information: The Copernicus Atmosphere Monitoring Service is operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European Commission as part of the Copernicus Programme ( http://copernicus.eu ). The CHE and CoCO2 projects have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 776186 and No 958927. We also thank the FLUXNET and TCCON PIs for providing the data used for the validation of the nature run dataset. Funding Information: The Copernicus Atmosphere Monitoring Service is operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European Commission as part of the Copernicus Programme (http://copernicus.eu). The CHE and CoCO2 projects have received funding from the European Union?s Horizon 2020 research and innovation programme under grant agreement No 776186 and No 958927. We also thank the FLUXNET and TCCON PIs for providing the data used for the validation of the nature run dataset. Publisher Copyright: © 2022, The Author(s).

PY - 2022/12

Y1 - 2022/12

N2 - The CO2 Human Emissions project has generated realistic high-resolution 9 km global simulations for atmospheric carbon tracers referred to as nature runs to foster carbon-cycle research applications with current and planned satellite missions, as well as the surge of in situ observations. Realistic atmospheric CO2, CH4 and CO fields can provide a reference for assessing the impact of proposed designs of new satellites and in situ networks and to study atmospheric variability of the tracers modulated by the weather. The simulations spanning 2015 are based on the Copernicus Atmosphere Monitoring Service forecasts at the European Centre for Medium Range Weather Forecasts, with improvements in various model components and input data such as anthropogenic emissions, in preparation of a CO2 Monitoring and Verification Support system. The relative contribution of different emissions and natural fluxes towards observed atmospheric variability is diagnosed by additional tagged tracers in the simulations. The evaluation of such high-resolution model simulations can be used to identify model deficiencies and guide further model improvements.

AB - The CO2 Human Emissions project has generated realistic high-resolution 9 km global simulations for atmospheric carbon tracers referred to as nature runs to foster carbon-cycle research applications with current and planned satellite missions, as well as the surge of in situ observations. Realistic atmospheric CO2, CH4 and CO fields can provide a reference for assessing the impact of proposed designs of new satellites and in situ networks and to study atmospheric variability of the tracers modulated by the weather. The simulations spanning 2015 are based on the Copernicus Atmosphere Monitoring Service forecasts at the European Centre for Medium Range Weather Forecasts, with improvements in various model components and input data such as anthropogenic emissions, in preparation of a CO2 Monitoring and Verification Support system. The relative contribution of different emissions and natural fluxes towards observed atmospheric variability is diagnosed by additional tagged tracers in the simulations. The evaluation of such high-resolution model simulations can be used to identify model deficiencies and guide further model improvements.

U2 - 10.1038/s41597-022-01228-2

DO - 10.1038/s41597-022-01228-2

M3 - Article

C2 - 35410420

AN - SCOPUS:85128042382

SN - 2052-4463

VL - 9

JO - Scientific Data

JF - Scientific Data

IS - 1

M1 - 160

ER -

Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement

Abstract

Bibliographical note

Subject classification (UKÄ)

UN SDGs

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