Constraining the CO<sub>2</sub> budget of the corn belt: exploring uncertainties from the assumptions in a mesoscale inverse system

Abstract

Abstract. We performed an atmospheric inversion of the CO 2 fluxes over Iowa and the surrounding states, from June to December 2007, at 20 km resolution and weekly timescale. Eight concentration towers were used to constrain the carbon balance in a 1000×1000 km 2 domain in this agricultural region of the US upper midwest. The CO 2 concentrations of the boundaries derived from CarbonTracker were adjusted to match direct observations from aircraft profiles around the domain. The regional carbon balance ends up with a sink of 183 Tg C±35 Tg C over the area for the period June-December, 2007. Potential bias from incorrect boundary conditions of about 0.55 ppm over the 7 months was corrected using mixing ratios from four different aircraft profile sites operated at a weekly time scale, acting as an additional source of uncertainty of 24 Tg C. We used two different prior flux estimates, the SiBCrop model and the inverse flux product from the CarbonTracker system. We show that inverse flux estimates using both priors converge to similar posterior estimates (20 Tg C difference), in our reference inversion, but some spatial structures from the prior fluxes remain in the posterior fluxes, revealing the importance of the prior flux resolution and distribution despite the large amount of atmospheric data available. The retrieved fluxes were compared to eddy flux towers in the corn and grassland areas, revealing an improvement in the seasonal cycles between the two compared to the prior fluxes, despite large absolute differences due to representation errors. The uncertainty of 34 Tg C (or 34 g C m 2 ) was derived from the posterior uncertainty obtained with our reference inversion of about 25 to 30 Tg C and from sensitivity tests of the assumptions made in the inverse system, for a mean carbon balance over the region of −183 Tg C, slightly weaker than the reference. Because of the potential large bias (∼24 Tg C in this case) due to choice of background conditions, proportional to the surface but not to the regional flux, this methodology seems limited to regions with a large signal (sink or source), unless additional observations can be used to constrain the boundary inflow.

Network design for mesoscale inversions of CO₂ sources and sinks

“…The method used in the paper was described in the study of Lauvaux et al (2012). The state vector (x) that includes the three components described above (daytime fluxes, nighttime fluxes and boundary inflow) is obtained by the following equation:…”

“…Though errors in the atmospheric transport model and at the boundaries limit the potential of the method (Go¨ckede et al, 2010b;Lauvaux et al, 2012), mesoscale inverse systems have shown consistent improvements from prior fluxes over short periods of time (Lauvaux et al, 2009), and at the annual time scale over the region (Schuh et al, 2010). Over longer time scales, the assessment of the regional flux balance implies the capability of capturing the spatio-temporal variability in the atmospheric CO 2 mixing ratios and avoiding persistent errors from the atmospheric transport models (e.g.…”

Regional data assimilation of multi-spectral MOPITT observations of CO over North America

“…The boundary conditions have also been imposed based on independent data, such as aircraft in situ measurements (e.g. Brioude et al, 2012;Lauvaux et al, 2012;Wecht et al, 2014).…”

Diagnostic methods for atmospheric inversions of long-lived greenhouse gases

“…For example, the fraction of the global CO 2 sink attributable to land versus ocean can be compared between inversions and independent model or mass-balance estimates (e.g., Le Quéré et al, 2015). For specific regions and periods, inversion results can also be compared against detailed inventory estimates of fluxes (e.g., Lauvaux et al, 2012;Schuh et al, 2013). A third example (noted already in Sect.…”