Biogeosciences (Jan 2025)
Seasonal and interannual variability in CO<sub>2</sub> fluxes in southern Africa seen by GOSAT
Abstract
The interannual variability in the global carbon sink is heavily influenced by semiarid regions. Southern hemispheric Africa has large semiarid and arid regions. However, there is only a sparse coverage of in situ CO2 measurements in the Southern Hemisphere. This leads to uncertainties in measurement-based carbon flux estimates for these regions. Furthermore, dynamic global vegetation models (DGVMs) show large inconsistencies in semiarid regions. Satellite CO2 measurements offer a spatially extensive and independent source of information about the southern African carbon cycle. We examine Greenhouse Gases Observing Satellite (GOSAT) CO2 concentration measurements from 2009 to 2018 in southern Africa. We infer CO2 land–atmosphere fluxes which are consistent with the GOSAT measurements using the TM5-4DVar atmospheric inversion system. We find systematic differences between atmospheric inversions performed on satellite observations versus inversions that assimilate only in situ measurements. This suggests limited measurement information content in the latter. We use the GOSAT-based fluxes and solar-induced fluorescence (SIF; a proxy for photosynthesis) as atmospheric constraints to select DGVMs of the TRENDYv9 ensemble which show compatible fluxes. The selected DGVMs allow for the study of the vegetation processes driving the southern African carbon cycle. By doing so, our satellite-based process analyses pinpoint photosynthetic uptake in the southern grasslands to be the main driver of the interannual variability in the southern African carbon fluxes, agreeing with former studies based on vegetation models alone. We find that the seasonal cycle, however, is substantially influenced by enhanced soil respiration due to soil rewetting at the beginning of the rainy season. The latter result emphasizes the importance of correctly representing the response of semiarid ecosystems to soil rewetting in DGVMs.