Atmos. Chem. Phys. Discuss., 13, 19051-19083, 2013
www.atmos-chem-phys-discuss.net/13/19051/2013/
doi:10.5194/acpd-13-19051-2013
© Author(s) 2013. This work is distributed
under the Creative Commons Attribution 3.0 License.
Review Status
This discussion paper has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP.
Biases in regional carbon budgets from covariation of surface fluxes and weather in transport model inversions
I. N. Williams1, W. J. Riley1, M. S. Torn1, S. C. Biraud1, and M. L. Fischer2
1Lawrence Berkeley National Laboratory, Earth Sciences Division, Berkeley, CA, USA
2Lawrence Berkeley National Laboratory, Environmental Energy Technologies Division, Berkeley, CA, USA

Abstract. Recent advances in transport model inversions could significantly reduce uncertainties in land carbon uptake through assimilation of high frequency CO2 concentration measurements. The impact of these measurements depends on the strength of covariation between surface fluxes and atmospheric transport and mixing at weekly and shorter time-scales, and on how well transport models represent this covariation. A stochastic boundary layer model was developed to quantify the effects of synoptic covariation on surface flux inversions at daily to season time-scales, and to compare covariation in transport model simulations to observations at the US Southern Great Plains Atmospheric Radiation Measurement Climate Research Facility. The most significant covariation of surface fluxes and transport occurred on weekly and longer time-scales, suggesting that surface flux inversions would benefit most from improved simulations of dynamics at the lower-frequency end of the synoptic spectrum. Biases in these rectifier effects contributed to surface flux biases of 13% of the seasonal cycle amplitude, estimated from differences between observations and a data assimilation system (CarbonTracker). Biases in simulated covariation of transport and surface fluxes resulted in overestimated boundary layer concentrations during the growing season over the Southern Great Plains, by up to 0.3 ppm CO2. Though small relative to the seasonal cycle, the strength of synoptic rectifier effects strongly varies on inter-annual time-scales, with some years having negligible and others having large vertical concentration gradients during the growing season, due only to differences in covariation of surface fluxes and transport. Inter-annual variability in vertical gradients due to synoptic rectifier effects is of similar magnitude to the inter-annual variability due to carbon sinks alone.

Citation: Williams, I. N., Riley, W. J., Torn, M. S., Biraud, S. C., and Fischer, M. L.: Biases in regional carbon budgets from covariation of surface fluxes and weather in transport model inversions, Atmos. Chem. Phys. Discuss., 13, 19051-19083, doi:10.5194/acpd-13-19051-2013, 2013.
 
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