Articles | Volume 18, issue 6
https://doi.org/10.5194/essd-18-4279-2026
https://doi.org/10.5194/essd-18-4279-2026
Data description article
 | 
24 Jun 2026
Data description article |  | 24 Jun 2026

Reconstructing two-decade daily high-resolution seamless global land XCO2 records using a hybrid Transformer–BiLSTM model

Yu Qu, Xian Shi, Yulong Fan, Zhihui Wang, and Jing Wei

Data sets

GlobalHighXCO2: Global Daily Seamless 10 km XCO2 Dataset Over Land (2003–Present) Yu Qu and Jing Wei https://doi.org/10.5281/zenodo.18220962

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Short summary
We developed a new global dataset that provides daily seamless observations of XCO2 over land from 2003 to 2022. Using artificial intelligence to integrate multiple satellite missions, atmospheric reanalysis, and environmental data, we filled data gaps and ensured continuity across satellite records. The dataset captures both long-term increases in XCO2 and short-term enhancements associated with events such as wildfires, supporting carbon-emission monitoring and climate-change studies.
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