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Separation of the effects of land and climate model errors on simulated contemporary land carbon cycle trends in the MPI Earth system model VI

MPG-Autoren
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Dalmonech,  Daniela
Terrestrial Biosphere Modelling & Data assimilation, Dr. S. Zähle, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Zaehle,  Sönke
Terrestrial Biosphere Modelling & Data assimilation, Dr. S. Zähle, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;
Terrestrial Biosphere Modelling, Dr. Sönke Zähle, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Schürmann,  Gregor
Terrestrial Biosphere Modelling & Data assimilation, Dr. S. Zähle, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Zitation

Dalmonech, D., Zaehle, S., Schürmann, G., Brovkin, V., Reick, C., & Schnur, R. (2015). Separation of the effects of land and climate model errors on simulated contemporary land carbon cycle trends in the MPI Earth system model VI. Journal of Climate, 28(1), 272-291. doi:10.1175/JCLI-D-13-00593.1.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0024-260E-8
Zusammenfassung
The capacity of Earth System Models (ESMs) to make reliable projections of future
26 atmospheric CO2 and climate is strongly dependent on the ability of the land surface model
27 to adequately simulate the land carbon (C) cycle. Defining “adequate” performance of the
28 land model requires an understanding of the contributions of climate model and land model
29 errors to the land C cycle. Here, we apply a benchmarking framework based on significant,
30 observed characteristics of the land C cycle for the contemporary period, for which sufficient
31 evaluation data are available, to test the ability of the JSBACH land surface component of the
32 MPI Earth System Model (MPI-ESM), to simulate land C trends. We give particular attention
33 to the role of potential effects caused by climate biases and therefore investigate the results
34 of model configurations in which JSBACH is interactively “coupled” to atmosphere and ocean
35 components, and an “uncoupled” configuration, where JSBACH is driven by reconstructed
36 meteorology.
37 The ability of JSBACH to simulate the observed phase of phenology and seasonal C fluxes is
38 not strongly affected by climate biases. Contrarily, noticeable differences in the simulated
39 gross primary productivity and land C stocks emerge between coupled and uncoupled
40 configurations, leading to significant differences in the decadal terrestrial C balance, and its
41 sensitivity to climate. These differences are strongly controlled by climate biases of the MPI42
ESM, in particular those affecting soil moisture. To effectively characterize model
43 performance, the potential effects of climate biases on the land C dynamics need to be 44 considered during the development and calibration of land surface models.