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| Titel |
Forecasting global atmospheric CO2 |
| VerfasserIn |
A. Agusti-Panareda, S. Massart, F. Chevallier, S. Boussetta, G. Balsamo, A. Beljaars, P. Ciais, N. M. Deutscher, R. Engelen, L. Jones, R. Kivi, J.-D. Paris, V.-H. Peuch, V. Sherlock, A. T. Vermeulen, P. O. Wennberg, D. Wunch |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 14, no. 21 ; Nr. 14, no. 21 (2014-11-14), S.11959-11983 |
| Datensatznummer |
250119159
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| Publikation (Nr.) |
 copernicus.org/acp-14-11959-2014.pdf |
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| Zusammenfassung |
| 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 using the
infrastructure of the European Centre for Medium-Range Weather Forecasts
(ECMWF) Integrated Forecasting System (IFS). One of the strengths of the
CO2 forecasting 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 statistical and physical
models. The CO2 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 CO2 on
different temporal and spatial scales compared 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
cycle. 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 optimized fluxes and the atmospheric CO2
compared to observations. 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 analyses 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 accumulation of errors in the atmospheric CO2 forecast will
be reduced. Improvements in the CO2 forecast are also expected with the
continuous developments in the operational IFS. |
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