Global Estimates of Daily Gapless Atmospheric XCH4 Concentrations From Satellite and Reanalysis Data During 2003–2020

Methane is a potent greenhouse gas that significantly drives climate change and affects human health and ecosystems by promoting surface ozone formation. However, the spatial continuity of current satellite-derived column-averaged dry-air mole fraction of methane (XCH4) data remains limited, and the sparse distribution of ground-based observations further hinders our understanding of methane sources and trends. To address this, we developed a novel spatiotemporal Transformer model to fill gaps in satellite retrievals and correct biases, thereby generating a global, daily, gapless XCH4 dataset at $0.1^{\circ } \times 0.1^{\circ }$ ( $\sim 10\times 10$ km near the equator) grid resolution from 2003 to 2020. This model integrates XCH4 retrievals from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) and Greenhouse Gases Observing Satellite (GOSAT), together with XCH4 reanalysis from the Copernicus Atmosphere Monitoring Service (CAMS), meteorological variables, and other auxiliary datasets. Our fused daily XCH4 dataset yielded a mean coefficient of determination ( $R^{2}$ ) value of 0.93, a root-mean-square error (RMSE) of 13.10 ppb, and a bias of 7.45 ppb when independently compared with measurements from the Total Carbon Column Observing Network (TCCON). Furthermore, we performed bias correction on the reconstructed XCH4 data using the TCCON network and supplementary variables to improve consistency across satellites and enhance accuracy, achieving a mean cross-validation $R^{2}$ (CV- $R^{2}$ ) of 0.97, an RMSE of 7.51 ppb, and a bias of 0.51 ppb. We observed a global annual growth rate of 6.09 ppb/yr ( $p \lt 0.001$ ) from 2003 to 2020, with the average annual trends in developed countries being much lower than those in developing countries, at 5.86 and 6.16 ppb/yr ( $p \lt 0.001$ ), respectively. Bangladesh exhibited the highest annual average concentration and trend, with average values of $1850.21~\pm ~41.85$ ppb and 8.07 ppb/yr ( $p \lt 0.001$ ), respectively. This unique global gapless daily XCH4 dataset enables the precise detection of local emissions and provides valuable support for informing methane emission management policies and enhancing our understanding of global methane sources and their spatiotemporal variations.