Abstract

Understanding carbon dioxide (CO₂) biospheric processes is of great importance because the terrestrial exchange drives the seasonal and interannual variability of CO₂ in the atmosphere. Atmospheric inversions based on CO₂ concentration measurements alone can only determine net biosphere fluxes, b... Show moreUnderstanding carbon dioxide (CO₂) biospheric processes is of great importance because the terrestrial exchange drives the seasonal and interannual variability of CO₂ in the atmosphere. Atmospheric inversions based on CO₂ concentration measurements alone can only determine net biosphere fluxes, but not differentiate between photosynthesis (uptake) and respiration (production). Carbonyl sulfide (OCS) could provide an important additional constraint: it is also taken up by plants during photosynthesis but not emitted during respiration, and therefore is a potential means to differentiate between these processes. Solar absorption Fourier Transform InfraRed (FTIR) spectrometry allows for the retrievals of the atmospheric concentrations of both CO₂ and OCS from measured solar absorption spectra. Here, we investigate co-located and quasi-simultaneous FTIR measurements of OCS and CO₂ performed at five selected sites located in the Northern Hemisphere. These measurements are compared to simulations of OCS and CO₂ using a chemical transport model (GEOS-Chem). The coupled biospheric fluxes of OCS and CO₂ from the simple biosphere model (SiB) are used in the study. The CO₂ simulation with SiB fluxes agrees with the measurements well, while the OCS simulation reproduced a weaker drawdown than FTIR measurements at selected sites, and a smaller latitudinal gradient in the Northern Hemisphere during growing season when comparing with HIPPO (HIAPER Pole-to-Pole Observations) data spanning both hemispheres. An offset in the timing of the seasonal cycle minimum between SiB simulation and measurements is also seen. Using OCS as a photosynthesis proxy can help to understand how the biospheric processes are reproduced in models and to further understand the carbon cycle in the real world. Show less