Quantifying and understanding the uncertainty of atmospheric CO2 concentrations determined from calcic paleosols



[1] A computer program (PBUQ) that uses Monte Carlo simulations to propagate uncertainty through regression equations and the equation for the paleosol carbonate CO2 paleobarometer is presented. PBUQ includes options for all of the common approaches to determining values for input variables and incorporates several recent advancements relevant to determining values for soil-respired CO2 concentrations, δ13C values of respired CO2, δ13C values of atmospheric CO2, and temperatures of soil carbonate formation. PBUQ is intended to improve confidence in paleoatmospheric CO2 research by helping researchers draw statistically significant conclusions. PBUQ can also be used to attribute and partition error among various sources and thereby advance this technique. Sensitivity analysis indicates that S(z) is the largest source of uncertainty for most paleosols and that uncertainty is minimized for soils in which CO2 is an evenly balanced mixture between soil-derived and atmospheric components. Evenly balanced mixtures are most likely for paleosols formed in deserts and for weakly developed paleosols. Development of proxies for soil-respired CO2 concentrations and δ13C values of soil-respired CO2 specifically for such soils is perhaps the most crucial next step for improving this technique. Currently, calcic paleosols are best used to test the significance of trends and/or differences among time slices in paleoatmospheric CO2 concentration. Application to quantifying Earth System Sensitivity will require large scale averaging of determinations from individual paleosols and/or reduced uncertainty associated with input variables.