High-Resolution Inversion of GOSAT-2 Retrievals for Sectoral Methane Emission Estimates During 2019–2022: A Consistency Analysis with GOSAT Inversion

We employed a global high-resolution inverse model to estimate sectoral methane emissions, integrating observations from the GOSAT-2 satellite for the first time, along with observations from the surface observation network. A similar set of inversions using GOSAT observations was carried out to evaluate the consistency between emissions estimates derived from these two satellites and to ensure that GOSAT-2 data could seamlessly integrate with the existing data series without disrupting the continuity of flux estimates. This analysis, covering the period from 2019 to 2022, utilized prior anthropogenic emissions data mainly from EDGAR v6 and incorporated additional natural sources and sinks as outlined by Saunois et al. (2020). Our analysis reveals a general agreement between total methane emissions estimates from GOSAT and GOSAT-2. However, on a sectoral basis, we found notable regional differences in the flux estimates. While GOSAT inversion estimates ~8 Tg a-1 more anthropogenic emissions for China and around 4 Tg a-1 more wetland emissions for Brazil and Indonesia, the posterior error distribution suggests that GOSAT-2 inversion is closer to surface observations over Asia. These discrepancies are found in regions with significant differences in XCH4 data from the two satellites, such as East Asia and North America, tropical South America, and tropical Africa. These regional biases persist due to limited representative surface reference sites for Level 2 bias correction. The relatively lower data volume from GOSAT also introduces seasonal biases in the flux estimates when the quality filtering of Level 2 data persistently reduces usable observations during certain seasons, resulting in inadequate representation of the seasonal cycle in regions such as East Asia. Similarly, in tropical South America, where the model is relatively under-constrained by the limited surface observations, the lower data volume of GOSAT-2 suffers. While the two inversions exhibit consistent overall performance across North America and Europe, GOSAT-2-based inversion demonstrates a better performance over East Asia. Therefore, while the two satellite datasets are broadly consistent, considering the fact that the biases in the XCH4 data overlap with regions under-constrained by surface observations, establishing additional surface reference measurement sites is desirable to ensure consistent inversion results.