Interannual variability in the Australian carbon cycle over 2015–2019, based on assimilation of Orbiting Carbon Observatory-2 (OCO-2) satellite data

Abstract

In this study, we employ a regional inverse modelling approach to estimate monthly carbon fluxes over the Australian continent for 2015–2019 using the assimilation of the total column-averaged mole fractions of carbon dioxide from the Orbiting Carbon Observatory-2 (OCO-2, version 9) satellite. Subsequently, we study the carbon cycle variations and relate their fluctuations to anomalies in vegetation productivity and climate drivers. Our 5-year regional carbon flux inversion suggests that Australia was a carbon sink averaging −0.46 ± 0.08 PgC yr−1 (excluding fossil fuel emissions), largely influenced by a strong carbon uptake (−1.04 PgC yr−1) recorded in 2016. Australia's semi-arid ecosystems, such as sparsely vegetated regions (in central Australia) and savanna (in northern Australia), were the main contributors to the carbon uptake in 2016. These regions showed relatively high vegetation productivity, high rainfall, and low temperature in 2016. In contrast to the large carbon sink found in 2016, the large carbon outgassing recorded in 2019 coincides with an unprecedented rainfall deficit and higher-than-average temperatures across Australia. Comparison of the posterior column-averaged CO2 concentration with Total Carbon Column Observing Network (TCCON) stations and in situ measurements offers limited insight into the fluxes assimilated with OCO-2. However, the lack of these monitoring stations across Australia, mainly over ecosystems such as savanna and areas with sparse vegetation, impedes us from providing strong conclusions. To a certain extent, we found that the flux anomalies across Australia are consistent with the ensemble means of the OCO-2 Model Intercomparison Project (OCO-2 MIP) and FLUXCOM (2015–2018), which estimate an anomalous carbon sink for Australia in 2016 of −1.09 and −0.42 PgC yr−1 respectively. More accurate estimates of OCO-2 retrievals, with the addition of ocean glint data into our system, and a better understanding of the error in the atmospheric transport modelling will yield further insights into the difference in the magnitude of our carbon flux estimates.