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TransCom model simulations of hourly atmospheric CO2: Analysis of synoptic-scale variations for the period 2002-2003

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons62529

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

http://pubman.mpdl.mpg.de/cone/persons/resource/persons62430

Karstens,  U.
Regional Scale Modelling of Atmospheric Trace Gases, Dr. U. Karstens, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Zitation

Patra, P. K., Law, R. M., Peters, W., Rödenbeck, C., Takigawa, M., Aulagnier, C., et al. (2008). TransCom model simulations of hourly atmospheric CO2: Analysis of synoptic-scale variations for the period 2002-2003. Global Biogeochemical Cycles, 22(4), B4013. doi:10.1029/2007GB003081.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000E-D72D-F
Zusammenfassung
The ability to reliably estimate CO2 fluxes from current in situ atmospheric CO2 measurements and future satellite CO2 measurements is dependent on transport model performance at synoptic and shorter timescales. The TransCom continuous experiment was designed to evaluate the performance of forward transport model simulations at hourly, daily, and synoptic timescales, and we focus on the latter two in this paper. Twenty-five transport models or model variants submitted hourly time series of nine predetermined tracers (seven for CO2) at 280 locations. We extracted synoptic-scale variability from daily averaged CO2 time series using a digital filter and analyzed the results by comparing them to atmospheric measurements at 35 locations. The correlations between modeled and observed synoptic CO2 variabilities were almost always largest with zero time lag and statistically significant for most models and most locations. Generally, the model results using diurnally varying land fluxes were closer to the observations compared to those obtained using monthly mean or daily average fluxes, and winter was often better simulated than summer. Model results at higher spatial resolution compared better with observations, mostly because these models were able to sample closer to the measurement site location. The amplitude and correlation of model-data variability is strongly model and season dependent. Overall similarity in modeled synoptic CO2 variability suggests that the first-order transport mechanisms are fairly well parameterized in the models, and no clear distinction was found between the meteorological analyses in capturing the synoptic-scale dynamics. [References: 47]