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| Titel |
Causes of variation in soil carbon simulations from CMIP5 Earth system models and comparison with observations |
| VerfasserIn |
K. E. O. Todd-Brown, J. T. Randerson, W. M. Post, F. M. Hoffman, C. Tarnocai, E. A. G. Schuur, S. D. Allison |
| 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. 3 ; Nr. 10, no. 3 (2013-03-13), S.1717-1736 |
| Datensatznummer |
250018151
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| Publikation (Nr.) |
 copernicus.org/bg-10-1717-2013.pdf |
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| Zusammenfassung |
| Stocks of soil organic carbon represent a large component of the carbon cycle
that may participate in climate change feedbacks, particularly on decadal and
centennial timescales. For Earth system models (ESMs), the ability to
accurately represent the global distribution of existing soil carbon stocks
is a prerequisite for accurately predicting future carbon–climate feedbacks.
We compared soil carbon simulations from 11 model centers to empirical data
from the Harmonized World Soil Database (HWSD) and the Northern Circumpolar
Soil Carbon Database (NCSCD). Model estimates of global soil carbon stocks
ranged from 510 to 3040 Pg C, compared to an estimate of 1260 Pg C (with
a 95% confidence interval of 890–1660 Pg C) from the HWSD. Model
simulations for the high northern latitudes fell between 60 and 820 Pg C,
compared to 500 Pg C (with a 95% confidence interval of
380–620 Pg C) for the NCSCD and 290 Pg C for the HWSD. Global soil
carbon varied 5.9 fold across models in response to a 2.6-fold variation in
global net primary productivity (NPP) and a 3.6-fold variation in global soil
carbon turnover times. Model–data agreement was moderate at the biome level
(R2 values ranged from 0.38 to 0.97 with a mean of 0.75); however, the
spatial distribution of soil carbon simulated by the ESMs at the 1°
scale was not well correlated with the HWSD (Pearson correlation coefficients
less than 0.4 and root mean square errors from 9.4 to 20.8 kg C m−2). In northern
latitudes where the two data sets overlapped, agreement between the HWSD and
the NCSCD was poor (Pearson correlation coefficient 0.33), indicating
uncertainty in empirical estimates of soil carbon. We found that a reduced
complexity model dependent on NPP and soil temperature explained much of the
1° spatial variation in soil carbon within most ESMs (R2 values
between 0.62 and 0.93 for 9 of 11 model centers). However, the same reduced
complexity model only explained 10% of the spatial variation in HWSD
soil carbon when driven by observations of NPP and temperature, implying that
other drivers or processes may be more important in explaining observed soil
carbon distributions. The reduced complexity model also showed that
differences in simulated soil carbon across ESMs were driven by differences
in simulated NPP and the parameterization of soil heterotrophic respiration
(inter-model R2 = 0.93), not by structural differences between the
models. Overall, our results suggest that despite fair global-scale agreement
with observational data and moderate agreement at the biome scale, most ESMs
cannot reproduce grid-scale variation in soil carbon and may be missing key
processes. Future work should focus on improving the simulation of driving
variables for soil carbon stocks and modifying model structures to include
additional processes. |
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