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| Titel |
On the potential of the ICOS atmospheric CO2 measurement network for estimating the biogenic CO2 budget of Europe |
| VerfasserIn |
N. Kadygrov, G. Broquet, F. Chevallier, L. Rivier, C. Gerbig, P. Ciais |
| 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 ; 15, no. 22 ; Nr. 15, no. 22 (2015-11-18), S.12765-12787 |
| Datensatznummer |
250120167
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| Publikation (Nr.) |
 copernicus.org/acp-15-12765-2015.pdf |
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| Zusammenfassung |
| We present a performance assessment of the European Integrated Carbon Observing System (ICOS) atmospheric network for constraining European
biogenic CO2 fluxes (hereafter net ecosystem exchange, NEE). The
performance of the network is assessed in terms of uncertainty in the fluxes,
using a state-of-the-art mesoscale variational atmospheric inversion system
assimilating hourly averages of atmospheric data to solve for NEE at 6 h
and 0.5° resolution. The performance of the ICOS atmospheric
network is also assessed in terms of uncertainty reduction compared to
typical uncertainties in the flux estimates from ecosystem models, which are
used as prior information by the inversion. The uncertainty in inverted
fluxes is computed for two typical periods representative of northern summer
and winter conditions in July and in December 2007, respectively. These
computations are based on a observing system simulation experiment (OSSE)
framework. We analyzed the uncertainty in a 2-week-mean NEE as a function of
the spatial scale with a focus on the model native grid scale
(0.5°), the country scale and the European scale (including
western Russia and Turkey). Several network configurations, going from 23 to
66 sites, and different configurations of the prior uncertainties and
atmospheric model transport errors are tested in order to assess and compare
the improvements that can be expected in the future from the extension of
the network, from improved prior information or transport models.
Assimilating data from 23 sites (a network comparable to present-day
capability) with errors estimated from the present prior information and
transport models, the uncertainty reduction on a 2-week-mean NEE should
range between 20 and 50 % for 0.5° resolution grid cells in
the best sampled area encompassing eastern France and western Germany. At
the European scale, the prior uncertainty in a 2-week-mean NEE is reduced by
50 % (66 %), down to ~ 43 Tg C month−1 (26 Tg C month−1)
in July (December). Using a larger network of 66 stations,
the prior uncertainty of NEE is reduced by the inversion by 64 % (down to
~ 33 Tg C month−1) in July and by 79 % (down to
~ 15 Tg C month−1) in December. When the results are
integrated over the well-observed western European domain, the uncertainty
reduction shows no seasonal variability. The effect of decreasing the
correlation length of the prior uncertainty, or of reducing the transport
model errors compared to their present configuration (when conducting
real-data inversion cases) can be larger than that of the extension of the
measurement network in areas where the 23 station observation network is
the densest. We show that with a configuration of the ICOS atmospheric
network containing 66 sites that can be expected on the long-term, the
uncertainties in a 2-week-mean NEE will be reduced by up to 50–80 % for
countries like Finland, Germany, France and Spain, which could
significantly improvement (and at least a high complementarity to) our
knowledge of NEE derived from biomass and soil carbon inventories at
multi-annual scales. |
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