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| Titel |
Can seasonal and interannual variation in landscape CO2 fluxes be detected by atmospheric observations of CO2 concentrations made at a tall tower? |
| VerfasserIn |
T. L. Smallman, M. Williams, J. B. Moncrieff |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 11, no. 3 ; Nr. 11, no. 3 (2014-02-06), S.735-747 |
| Datensatznummer |
250117193
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| Publikation (Nr.) |
 copernicus.org/bg-11-735-2014.pdf |
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| Zusammenfassung |
| The coupled numerical weather model WRF-SPA (Weather Research and Forecasting
model and Soil-Plant-Atmosphere model) has been used to investigate a 3 yr
time series of observed atmospheric CO2 concentrations from a tall tower
in Scotland, UK. Ecosystem-specific tracers of net CO2 uptake and net
CO2 release were used to investigate the contributions to the tower signal
of key land covers within its footprint, and how contributions varied at
seasonal and interannual timescales. In addition, WRF-SPA simulated
atmospheric CO2 concentrations were compared with two coarse global
inversion models, CarbonTrackerEurope and the National Oceanic and
Atmospheric Administration's CarbonTracker (CTE-CT). WRF-SPA realistically
modelled both seasonal (except post harvest) and daily cycles seen in
observed atmospheric CO2 at the tall tower (R2 = 0.67,
rmse = 3.5 ppm, bias = 0.58 ppm). Atmospheric CO2 concentrations
from the tall tower were well simulated by CTE-CT, but the inverse model
showed a poorer representation of diurnal variation and simulated a larger
bias from observations (up to 1.9 ppm) at seasonal timescales, compared to
the forward modelling of WRF-SPA. However, we have highlighted a consistent
post-harvest increase in the seasonal bias between WRF-SPA and observations.
Ecosystem-specific tracers of CO2 exchange indicate that the increased
bias is potentially due to the representation of agricultural processes
within SPA and/or biases in land cover maps. The ecosystem-specific tracers
also indicate that the majority of seasonal variation in CO2 uptake for
Scotland's dominant ecosystems (forests, cropland and managed grassland) is
detectable in observations within the footprint of the tall tower; however,
the amount of variation explained varies between years. The between years
variation in detectability of Scotland's ecosystems is potentially due to
seasonal and interannual variation in the simulated prevailing wind
direction. This result highlights the importance of accurately representing
atmospheric transport used within atmospheric inversion models used to
estimate terrestrial source/sink distribution and magnitude. |
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