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Forecasting global atmospheric CO_2

Agustí-Panareda, A. and Massart, S. and Chevallier, F. and Bousetta, S. and Balsamo, G. and Beljaars, A. and Ciais, P. and Deutscher, N. M. and Engelen, R. and Jones, L. and Kivi, R. and Parise, J.-D. and Peuch, V.-H. and Sherlock, V. and Vermeulen, A. T. and Wennberg, P. O. and Wunch, D. (2014) Forecasting global atmospheric CO_2. Atmospheric Chemistry and Physics, 14 (21). pp. 11959-11983. ISSN 1680-7316. https://resolver.caltech.edu/CaltechAUTHORS:20141219-104743832

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Abstract

A new global atmospheric carbon dioxide (CO_2) real-time forecast is now available as part of the pre-operational Monitoring of Atmospheric Composition and Climate – Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO_2 forecasting system is that the land surface, including vegetation CO_2 fluxes, is modelled online within the IFS. Other CO_2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO_2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO_2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO_2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO_2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO_2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO_2 fluxes also lead to accumulating errors in the CO_2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO_2 fluxes compared to total optimized fluxes and the atmospheric CO_2 compared to observations. The largest biases in the atmospheric CO_2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO_2 analyses based on the assimilation of CO_2 products retrieved from satellite measurements and CO_2 in situ observations, as they become available in near-real time. In this way, the accumulation of errors in the atmospheric CO_2 forecast will be reduced. Improvements in the CO_2 forecast are also expected with the continuous developments in the operational IFS.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.5194/acp-14-11959-2014DOIArticle
http://www.atmos-chem-phys.net/14/11959/2014/acp-14-11959-2014.htmlPublisherArticle
ORCID:
AuthorORCID
Wennberg, P. O.0000-0002-6126-3854
Wunch, D.0000-0002-4924-0377
Alternate Title:Forecasting global atmospheric CO2
Additional Information:© 2014 Author(s). CC Attribution 3.0 License. Received: 1 April 2014. Published in Atmos. Chem. Phys. Discuss.: 27 May 2014. Revised: 8 September 2014. Accepted: 8 September 2014. Published: 14 November 2014. Edited by: S. Galmarini. This study was funded by the European Commission under the EU Seventh Research Framework Programme (grant agreement No. 283576, MACC II). The ICOS data were obtained from the ICOS Atmospheric Thematic Center (Laboratoire des Sciences du Climat et l’Environnement) website at https://icos-atc-demo.lsce.ipsl.fr. The authors acknowledge the European Commission for the support of the preparatory phase of ICOS (2008–2013), the Netherlands Ministry of IenM and ECN for the support of the observations at Cabauw, and the monitoring network SNO-RAMCES/ICOS-France which is in charge of Ivittuut, Mace Head and Lamto stations with the support of CNRS, CEA and OVSQ. Thanks to F. Truong (LSCE) and to A. Diawara and Y. Palmer for the maintenance of Station Géophysique de LAMTO with the support of University of Abidjan. Thanks to J. L. Bonne and M. Delmotte for the data from Ivittuut station, with the support of Greenland’s Kommando, Danish Armed Forces, Island Commander Greenland and Kommuneqarfik Sermersooq. Thanks to V. Kazan and G. Spain for the maintenance of Mace Head station with the support of the Irish Environmental Protection Agency, and the National University of Ireland, Galway. Thanks to Harri Portin, Juha Hatakka, Tuomas Laurila (FMI) for providing the data from the ICOS station at Puijo, Finland. We are grateful to Jérôme Tarniewicz for his technical support with the ICOS database and to Miha Razinger for his help in the development and maintenance of the ICOS monitoring plots in the MACC website. Thanks to the NOAA/ESRL Global Monitoring Division for providing their data from the baseline observatories at Barrow (Alaska), American Samoa, South Pole (Antarctica), the tall towers at Argyle (Maine), Park Falls (Wisconsin), West Branch (Iowa), and the vertical profiles from the NOAA GMD Carbon Cycle Vertical Profile Network. TCCON data were obtained from the TCCON Data Archive, operated by the California Institute of Technology from the website at http://tccon.ipac.caltech.edu/. We acknowledge financial support of the Bialystok TCCON site from the Senate of Bremen and EU projects IMECC, GEOmon and InGOS, as well as maintenance and logistical work provided by the AeroMeteo Service and additional operational funding from the National Institute for Environmental Studies (NIES, Japan). POW and DW thank NASA’s Carbon Cycle Science program (NNX10AT83G and NNX11AG01G) and the Orbiting Carbon Observatory Program for support of TCCON and this research. The HIPPO Merged 10 s data set was obtained from the website at http://hippo.ornl.gov/dataaccess. The HIPPO Programme was supported by NSF grants ATM-0628575, ATM-0628519 and ATM-0628388 to Harvard University, University of California (San Diego), University Corporation for Atmospheric Research, NOAA Earth System Research Laboratory, University of Colorado/CIRES and by the NCAR. The NCAR is supported by the National Science Foundation. The feedback from Britton Stephens is greatly appreciated.
Funders:
Funding AgencyGrant Number
European Research Council (ERC)283576, MACC II
European CommissionICOS (2008–2013)
Centre National de la Recherche Scientifique (CNRS)UNSPECIFIED
Commissariat à l’Energie Atomique (CEA)UNSPECIFIED
OVSQUNSPECIFIED
University of AbidjanUNSPECIFIED
Greenland’s KommandoUNSPECIFIED
Danish Armed ForcesUNSPECIFIED
Island Commander GreenlandUNSPECIFIED
Kommuneqarfik SermersooqUNSPECIFIED
Environmental Protection Agency (Ireland)UNSPECIFIED
National University of Ireland, GalwayUNSPECIFIED
Bialystok TCCON Senate of BremenUNSPECIFIED
EU projects IMECC, GEOmon and InGOSUNSPECIFIED
National Institute for Environmental Studies (Japan)UNSPECIFIED
NASANNX10AT83G
NASANNX11AG01G
NASA Orbiting Carbon ObservatoryUNSPECIFIED
NSFATM-0628575
NSFATM-0628519
NSFATM-0628388
University of California (San Diego)UNSPECIFIED
University Corporation for Atmospheric Research UNSPECIFIED
National Oceanic and Atmospheric Administration (NOAA)UNSPECIFIED
University of Colorado/CIRESUNSPECIFIED
National Center for Atmospheric Research (NCAR)UNSPECIFIED
Issue or Number:21
Record Number:CaltechAUTHORS:20141219-104743832
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20141219-104743832
Official Citation:Agustí-Panareda, A., Massart, S., Chevallier, F., Boussetta, S., Balsamo, G., Beljaars, A., Ciais, P., Deutscher, N. M., Engelen, R., Jones, L., Kivi, R., Paris, J.-D., Peuch, V.-H., Sherlock, V., Vermeulen, A. T., Wennberg, P. O., and Wunch, D.: Forecasting global atmospheric CO2, Atmos. Chem. Phys., 14, 11959-11983, doi:10.5194/acp-14-11959-2014, 2014.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:53037
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:19 Dec 2014 19:58
Last Modified:03 Oct 2019 07:46

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