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Title:
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Forecasting global atmospheric CO2
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Author(s):
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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.; Wunch, D.
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Published by:
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Publication date:
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ECN
Environment & Energy Engineering
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11-11-2014
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ECN report number:
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Document type:
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ECN-W--14-040
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Article (scientific)
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Number of pages:
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27
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Published in: Atmospheric Chemistry and Physics (European Geosciences Union), , 2014, Vol.14, p.11959-11983.
Abstract:
A new global atmospheric carbon dioxide (CO2)
real-time forecast is now available as part of the preoperational
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-today
synoptic variability. In the atmospheric boundary layer,
this skill is significantly enhanced by modelling the day-today
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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