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| Titel |
Evaluating uncertainties in the simulated soil carbon in China using a nonlinear method |
| VerfasserIn |
G. Sun, M. Mu |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250059196
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| Zusammenfassung |
| In this study, we explored the maximal uncertainties in the simulated soil carbon in part of
China to climate change, including variations in climatology and climate variability, under
the condition of global warming. A conditional nonlinear optimal perturbation (CNOP)
approach was employed to discuss the above issue to a CNOP-type temperature or
precipitation perturbation using the Lund-Potsdam-Jena (LPJ) model. These uncertainties in
the simulated soil carbon were compared with those caused by a linear temperature or
precipitation perturbation. The key difference between the CNOP-type and the linear
perturbations was whether the perturbations brought the variation in the temperature or the
precipitation variability in comparison with the reference temperature or the precipitation
variability. The model results demonstrated that the uncertainties in the simulated soil carbon
resulted from the CNOP-type and linear temperature perturbations in south of the study
region, which was corresponding to part of South China, had different variations. In the
part of South China, the soil carbon was augmented because of the CNOP-type
temperature perturbations, and the variation in the soil carbon because of the linear
temperature perturbations was minor. In northeast of the study region, which was
corresponding to part of Northeast China, the soil carbon increased, whereas the soil carbon
decreased in north of the study region, which was corresponding to part of North
China and is located in arid and semi-arid regions in China, due to two kinds of
temperature changes. The uncertainties in the simulated soil carbon caused by the two
types of precipitation perturbations were similar. In the arid and semi-arid regions,
the soil carbon increased due to the two types of precipitation perturbations. This
research implies that the variation in temperature variability plays a crucial role in the
uncertainties in the simulated soil carbon and its components in the study region. |
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