2026-10-06T12:13:19Z https://www.scidb.cn/oai

10.57760/sciencedb.013dl 2026-09-28T11:57:06Z

2026-09-28 Daily 0.1° Seamless XCH₄ Fusion Dataset over Six Continental Regions, 2018–2024 doi:10.57760/sciencedb.013dl en This dataset provides daily 0.1° continuous XCH₄ fields from 2018 to 2024 over six representative continental regions: East Asia, North America, Europe, Africa, Australia, and South America. The dataset is primarily constrained by TROPOMI satellite observations and incorporates ERA5 meteorological variables. A self-supervised gated spatiotemporal convolution framework is used to reconstruct missing satellite observations. CAMS-EGG4 complete XCH₄ fields and observation-derived TROPOMI masks are used for model training, while the final reconstruction is driven by TROPOMI observations, observation masks, a 30-day XCH₄ background field, and meteorological variables. The dataset can support analyses of regional methane variability, long-term trends, and methane enhancement patterns. Methane; TROPOMI; Satellite Remote Sensing; Data Fusion; Deep Learning 徐翼洲 胡启后 李启华 苏文静 田园 薛劲凯 季祥光 刘诚 EMBARGO https://creativecommons.org/licenses/by-nc-sa/4.0/ dataset Science Data Bank