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How does the terrestrial carbon exchange respond to inter-annual climatic variations? A quantification based on atmospheric CO2 data

MPG-Autoren
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Rödenbeck,  Christian
Inverse Data-driven Estimation, Dr. C. Rödenbeck, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Zaehle,  Sönke
Terrestrial Biosphere Modelling, Dr. Sönke Zähle, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;
Terrestrial Biosphere Modelling, Dr. Sönke Zähle, Department Biogeochemical Integration, Prof. Dr. Martin Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Heimann,  Martin
Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Zitation

Rödenbeck, C., Zaehle, S., Keeling, R., & Heimann, M. (2018). How does the terrestrial carbon exchange respond to inter-annual climatic variations? A quantification based on atmospheric CO2 data. Biogeosciences, 15(8), 2481-2498. doi:10.5194/bg-15-2481-2018.


Zitierlink: http://hdl.handle.net/21.11116/0000-0000-31AA-9
Zusammenfassung
The response of the terrestrial Net Ecosystem Exchange (NEE) of CO2 to climate variations and trends may crucially determine the future climate trajectory. Here we directly quantify this response on interannual time scales, by building a linear regression of interannual NEE anomalies against observed air temperature anomalies into an atmospheric inverse calculation based on long-term atmospheric CO2 observations. This allows us to estimate the sensitivity of NEE to interannual variations in temperature (seen as climate proxy) resolved in space and with season. As this sensitivity comprises both 5 direct temperature effects and effects of other climate variables co-varying with temperature, we interpret it as “interannual climate sensitivity”. We find distinct seasonal patterns of this sensitivity in the northern extratropics, that are consistent with the expected seasonal responses of photosynthesis, respiration, and fire. Within uncertainties, these sensitivity patterns are consistent with independent inferrences from eddy covariance data. On large spatial scales, northern extratropical as well as tropical interannual NEE 10 variations inferred from the NEE-T regression are very similar to the estimates of an atmospheric inversion with explicit interannual degrees of freedom. The results of this study can be used to benchmark ecosystem process models, to gap-fill or extrapolate observational records, or to separate interannual variations from longer-term trends.