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| Titel |
A data assimilation framework for constraining upscaled cropland carbon flux seasonality and biometry with MODIS |
| VerfasserIn |
O. Sus, M. W. Heuer, T. P. Meyers, M. Williams |
| 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 ; 10, no. 4 ; Nr. 10, no. 4 (2013-04-12), S.2451-2466 |
| Datensatznummer |
250018196
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| Publikation (Nr.) |
 copernicus.org/bg-10-2451-2013.pdf |
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| Zusammenfassung |
| Agroecosystem models are strongly dependent on information on land management patterns for regional
applications. Land management practices play a major role in determining global yield variability,
and add an anthropogenic signal to the observed seasonality of atmospheric CO2
concentrations. However, there is still little knowledge on spatial and temporal variability of
important farmland activities such as crop sowing dates, and thus these remain rather crudely
approximated within carbon cycle studies.
In this study, we present a framework allowing for spatio-temporally resolved simulation of cropland
carbon fluxes under observational constraints on land management and canopy greenness. We apply data
assimilation methodology in order to explicitly account for information on sowing dates and model
leaf area index. MODIS 250 m vegetation index data were assimilated both in batch-calibration for
sowing date estimation and sequentially for improved model state estimation, using the ensemble Kalman
filter (EnKF), into a crop carbon mass balance model (SPAc). In doing so, we are able to quantify
the multiannual (2000–2006) regional carbon flux and biometry seasonality of maize–soybean crop
rotations surrounding the Bondville Ameriflux eddy covariance site, averaged over 104 pixel locations
within the wider area.
(1) Validation at the Bondville site shows that growing season C cycling is simulated accurately with
MODIS-derived sowing dates, and we expect that this framework allows for accurate simulations of C cycling at
locations for which ground-truth data are not available. Thus, this framework enables modellers to simulate current (i.e. last 10 yr) carbon
cycling of major agricultural regions. Averaged over the 104 field patches analysed, relative spatial
variability for biometry and net ecosystem exchange ranges from ∼7% to ∼18%. The
annual sign of net biome productivity is not significantly different from carbon neutrality. (2)
Moreover, observing carbon cycling at one single field with its individual sowing pattern is not
sufficient to constrain large-scale agroecosystem carbon flux seasonality. Study area average growing
season length is 20 days longer than observed at Bondville, primarily because of an earlier
estimated start of season. (3) For carbon budgeting, additional information on cropland soil
management and belowground carbon cycling has to be considered, as such constraints are not provided
by MODIS. |
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