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Forecasting global atmospheric CO2

Agusti-Panareda, Anna; Chevallier, F.; Boussetta, Souhail; Balsamo, G; Beljaars, Antoon; Ciais, P; Deutscher, N; Jones, L.; Engelen, Richard and Kivi, R., et al. (2014) In Atmospheric Chemistry and Physics 14. p.11959-11983
Abstract
A new global atmospheric carbon dioxide (CO2) real-time forecast is now available as part of the pre- operational Monitoring of Atmospheric Composition and Climate – Interim Implementation (MACC-II) service us- ing the infrastructure of the European Centre for Medium- Range Weather Forecasts (ECMWF) Integrated Forecast- ing System (IFS). One of the strengths of the CO2 fore- casting system is that the land surface, including vegetation CO2 fluxes, is modelled online within the IFS. Other CO2 fluxes are prescribed from inventories and from off-line sta- tistical and physical models. The CO2 forecast also bene- fits from the transport modelling from a state-of-the-art nu- merical weather prediction (NWP) system initialized daily with a... (More)
A new global atmospheric carbon dioxide (CO2) real-time forecast is now available as part of the pre- operational Monitoring of Atmospheric Composition and Climate – Interim Implementation (MACC-II) service us- ing the infrastructure of the European Centre for Medium- Range Weather Forecasts (ECMWF) Integrated Forecast- ing System (IFS). One of the strengths of the CO2 fore- casting system is that the land surface, including vegetation CO2 fluxes, is modelled online within the IFS. Other CO2 fluxes are prescribed from inventories and from off-line sta- tistical and physical models. The CO2 forecast also bene- fits from the transport modelling from a state-of-the-art nu- merical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper de- scribes the capability of the forecast in modelling the vari- ability of CO2 on different temporal and spatial scales com- pared to observations. The modulation of the amplitude of the CO2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO2 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 CO2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cy- cle. However, biases in the modelled CO2 fluxes also lead to accumulating errors in the CO2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO2 fluxes compared to total op-
timized fluxes and the atmospheric CO2 compared to obser- vations. The largest biases in the atmospheric CO2 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 CO2 analy- ses based on the assimilation of CO2 products retrieved from satellite measurements and CO2 in situ observations, as they become available in near-real time. In this way, the accumu- lation of errors in the atmospheric CO2 forecast will be re- duced. Improvements in the CO2 forecast are also expected with the continuous developments in the operational IFS. (Less)
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Atmospheric Chemistry and Physics
volume
14
pages
11959 - 11983
publisher
Copernicus Gesellschaft mbH
external identifiers
  • scopus:84912141061
ISSN
1680-7324
DOI
10.5194/acp-14-11959-2014
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English
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@article{7db9a059-29dd-4952-9dfe-ef09ba32f7af,
  abstract     = {A new global atmospheric carbon dioxide (CO2) real-time forecast is now available as part of the pre- operational Monitoring of Atmospheric Composition and Climate – Interim Implementation (MACC-II) service us- ing the infrastructure of the European Centre for Medium- Range Weather Forecasts (ECMWF) Integrated Forecast- ing System (IFS). One of the strengths of the CO2 fore- casting system is that the land surface, including vegetation CO2 fluxes, is modelled online within the IFS. Other CO2 fluxes are prescribed from inventories and from off-line sta- tistical and physical models. The CO2 forecast also bene- fits from the transport modelling from a state-of-the-art nu- merical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper de- scribes the capability of the forecast in modelling the vari- ability of CO2 on different temporal and spatial scales com- pared to observations. The modulation of the amplitude of the CO2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO2 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 CO2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cy- cle. However, biases in the modelled CO2 fluxes also lead to accumulating errors in the CO2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO2 fluxes compared to total op-<br/>timized fluxes and the atmospheric CO2 compared to obser- vations. The largest biases in the atmospheric CO2 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 CO2 analy- ses based on the assimilation of CO2 products retrieved from satellite measurements and CO2 in situ observations, as they become available in near-real time. In this way, the accumu- lation of errors in the atmospheric CO2 forecast will be re- duced. Improvements in the CO2 forecast are also expected with the continuous developments in the operational IFS.},
  author       = {Agusti-Panareda, Anna and Chevallier, F. and Boussetta, Souhail and Balsamo, G and Beljaars, Antoon and Ciais, P and Deutscher, N and Jones, L. and Engelen, Richard and Kivi, R. and Paris, J-D and Peuch, V-H and Sherlock, V. and Vermeulen, Alex and Wennberg, P. and Wunch, Debra},
  issn         = {1680-7324},
  language     = {eng},
  month        = {11},
  pages        = {11959--11983},
  publisher    = {Copernicus Gesellschaft mbH},
  series       = {Atmospheric Chemistry and Physics},
  title        = {Forecasting global atmospheric CO2},
  url          = {http://dx.doi.org/10.5194/acp-14-11959-2014},
  volume       = {14},
  year         = {2014},
}