Abstract

Abstract. In this study, we present the assimilation of data from the Orbiting Carbon Observatory-2 (OCO-2) (land nadir and glint data, version 9) to estimate the Australian carbon surface fluxes for the year 2015. To perform this estimation, we used both a regional-scale atmospheric transport–dispersion model and a four-dimensional variational assimilation scheme. Our results suggest that Australia was a carbon sink of −0.41 ± 0.08 PgC yr−1 compared to the prior estimate 0.09 ± 0.20 PgC yr−1 (excluding fossil fuel emissions). Most of the carbon uptake occurred in northern Australia over the savanna ecotype and in the western region over areas with sparse vegetation. Analysis of the enhanced vegetation index (EVI) suggests that the majority of the carbon uptake over the savanna ecosystem was due to an increase of vegetation productivity (positive EVI anomalies) amplified by an anomalous increase of rainfall in summer. Further from this, a slight increase of carbon uptake in Western Australia over areas with sparse vegetation (the largest ecosystem in Australia) was noted due to increased land productivity in the area caused by positive rainfall anomalies. The stronger carbon uptake estimate in this ecosystem was partially due to the land surface model (CABLE-BIOS3) underestimating the gross primary productivity of the ecosystem. To evaluate the accuracy of our carbon flux estimates from OCO-2 retrievals, we compare our posterior concentration fields against the column-averaged carbon retrievals from the Total Carbon Column Observing Network (TCCON) and ground-based in situ monitoring sites located around our domain. The validation analysis against TCCON shows that our system is able to reduce bias mainly in the summer season. Comparison with surface in situ observations was less successful, particularly over oceanic monitoring sites that are strongly affected by oceanic fluxes and subject to less freedom by the inversion. For stations located far from the coast, the comparison with in situ data was more variable, suggesting difficulties matching the column-integrated and surface data by the inversion, most likely linked to model vertical transport. Comparison of our fluxes against the OCO-2 model intercomparison (MIP) was encouraging. The annual carbon uptake estimated by our inversion falls within the ensemble of the OCO-2 MIP global inversions and presents a similar seasonal pattern.

Highlights

  • Australia’s carbon budget has been investigated by several large scale global ecosystem models (Sitch et al, 2015, Carbon cycle model intercomparison project (TRENDY)) and by the REgional Carbon Cycle Assessment and Processes project (RECCAP) (Haverd et al, 2013a)

  • Our findings indicate that the prior concentrations overestimate Orbiting Carbon Observatory-2 (OCO-2) from March to April and from July to September

  • The inversion was based around the Community Multiscale Air Quality (CMAQ) transport–dispersion model and satellite data from the Orbiting Carbon Observatory-2 (OCO2)

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Summary

Introduction

Australia’s carbon budget has been investigated by several large scale global ecosystem models (Sitch et al, 2015, Carbon cycle model intercomparison project (TRENDY)) and by the REgional Carbon Cycle Assessment and Processes project (RECCAP) (Haverd et al, 2013a) They have contributed to a more refined knowledge of the Australian carbon cycle, the estimated fluxes still diverge significantly. A large component of the uncertainty in this carbon budget was attributed to the estimate of net primary productivity (NPP) over grassland (Haverd et al, 2013b), with a large contribution to the land cover type they used to force their simulations (e.g. the Advanced Very High Resolution Radiometer (AVHRR) (1990–2006); Donohue et al, 2009) and the Moderate Resolution Imaging Spectroradiometer (MODIS) (2000–2011) Given this uncertainty, it is essential to bring any other observations we have to bear on the Australian carbon balance. For the same year, Basu et al (2013) inferred it to be a net carbon source (0.4 PgC yr−1)

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