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Enhanced methane monitoring: a globally harmonized daily 0.1<strong>°</strong> XCH<sub>4</sub> through machine learning-based fusion of GOSAT; GOSAT-2; and TROPOMI
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DOI：10.5194/amt-19-4313-2026.png)
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Abstract
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Abstract. Accurate global monitoring of atmospheric methane (CH4) is essential for tracking progress toward climate mitigation targets such as the Global Methane Pledge (GMP). Ground-based measurement networks are too sparse to provide sufficient spatial coverage; while satellite-derived retrievals are hindered by systematic biases and uncertainties; limiting their reliability for consistent global monitoring. We present the first global fusion of GOSAT; GOSAT-2; and TROPOMI to generate a globally consistent daily 0.1° land dataset for 2020–2023 for enhanced global column-averaged dry-air mole fraction of atmospheric methane (XCH4) mapping. The framework employs a three-step machine-learning (ML) approach: (1) sensor-specific bias correction using TCCON observations; (2) cross-sensor harmonization to GOSAT-2; the sensor with the strongest post-correction TCCON agreement; and (3) priority-based fusion. Tree-based ensemble regressors were trained with satellite retrieval parameters to reduce systematic biases and inter-sensor discrepancies. Independent validation at three withheld TCCON stations demonstrates robust generalization of the Fused product (R2 = 0.81; RMSE = 10.78 ppb); outperforming standard and operational bias-corrected satellite products and previously reported ML-based approaches. Regional assessments show that fusion substantially improves data availability and reduces systematic errors; delivering up to 9.5 % relative coverage gains compared to TROPOMI operational products in challenging regions (South Asia; Amazon Basin; Eastern Siberia). The Fused dataset reveals intensifying positive XCH4 anomalies (+60 ppb) over South Asia; East Asia; and Central Africa during 2020–2023; linked to MODIS-derived agricultural and urban land classes as well as known oil and gas fields. The dataset provides a scalable resource for regional CH4 emissions assessment and continuous monitoring; with the framework extendable to upcoming satellite missions (GOSAT-GW; CO2M) for long-term GMP progress tracking.
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