Biogenic CO2 flux uncertainty: numerical experiments and validation over south-eastern South America

Abstract

Understanding carbon dioxide (CO2) surface fluxes is essential in the context of a changingclimate. In particular, agriculture significantly contributes to CO2 fluxes. Recently, some studieshave focused on understanding how synoptic-scale variability modulates CO2 fluxes associatedwith vegetation and agriculture, finding that frontal passages and precipitation events exert astrong influence on these fluxes. This variability is particularly relevant in the Argentinean Pampas,where large CO2 fluxes associated with extensive agriculture combine with strong synopticvariability. Numerical modelling provides a valuable tool for investigating surface CO2 fluxesand their variability, despite the uncertainties associated with the model’s limitations. In thiswork, we investigate simulated CO2 fluxes in the Argentinean Pampas using the WeatherResearch and Forecasting Model (WRF) coupled with the Vegetation, Respiration andPhotosynthesis Model (VPRM) over three case studies representing different synoptic-scaleconditions. In addition, we estimate the uncertainty in the simulations by comparing simulatedCO2 fluxes using various WRF configurations and the ERA5 reanalysis. We found that thesynoptic-scale conditions have a considerable impact on the magnitude of fluxes as well asthe simulation uncertainty. Uncertainties in simulated CO2 fluxes can be as high as 60%, beinglarger at sunrise and sunset. Also, the largest uncertainty is associated with a case with a coldfrontal passage and widespread precipitation. These results allow a more accurate estimation ofCO2 flux uncertainty, which is key to understanding the effects of climate change.