A global dataset of δ¹³C-CH₄ source signatures and associated uncertainties (1998–2022), with a sensitivity analysis to support isotopic inversions

Abstract. The isotopic composition of atmospheric methane (δ¹³C-CH₄) provides critical constraints for attributing methane emissions to specific sources. In this study, we present updated global maps of δ¹³C-CH₄ source signatures across five major methane-emitting sectors (fossil fuels and geological, agriculture and waste, biomass and biofuel burning, wetlands, and other natural sources) for the period 1998–2022. These maps integrate recent spatially explicit datasets and literature-derived observations, and include explicit quantification of both intrinsic (within-sector) and aggregation-related uncertainties. Building upon previous global compilations, our dataset extends the temporal coverage to 2022, harmonizes sectoral definitions with the Global Methane Budget framework, and provides a consistent and traceable quantification of uncertainties suitable for atmospheric inversions. We assess the influence of these updated source signatures on the modeled atmospheric δ¹³C-CH₄ using forward simulations within the Community Inversion Framework (CIF) coupled to the LMDz transport model. A comprehensive sensitivity analysis quantifies the impacts of key drivers of uncertainty, including emission flux datasets, OH sinks, kinetic isotope effects, and isotopic source signatures. We show that uncertainties in methane oxidation chemistry and source signatures, particularly from agriculture and waste, dominate the variability in the modeled δ¹³C-CH₄ signal, while the impact of flux aggregation choices is comparatively minor. The updated isotopic dataset is provided on a global 1° × 1° grid, supporting future atmospheric inversions and improved methane budget assessments at global and regional scales. Practical guidelines for configuring isotopic inversions, including recommended uncertainty specifications and key parameters to optimize, are also provided, offering a framework for next-generation δ¹³C-CH₄ inversion studies. The final version of the gridded δ¹³C-CH₄ source signature dataset is available at the ESA Open Science Data portal: https://opensciencedata.esa.int/products/d13c-ch4-signatures-smart-ch4/collection.