A high-resolution Net Ecosystem Exchange dataset (500m, 8-day intervals) for the Qinghai-Tibet Plateau

We developed a high-resolution NEE dataset (500m, 8-day intervals) for the QTP, utilizing in-situ measurements from 36 plateau sites and 80 forest sites outside it, combined with remote sensing and meteorological data. Various combinations of environmental variables and machine learning algorithms were applied to assess prediction uncertainties. The results indicated that the annual mean NEE for the QTP averaged -147.63 ± 15.03 Tg C yr^-1, with an annual increase of -0.96 Tg C yr^-1 from 2002 to 2022. Meadows contributed most (38.1%) to total NEE, followed by shrubs (26.7%), forests (23%), steppes (11.8%), and wetlands (0.5%). Compared to previous studies, this research utilized more eddy covariance observations and covered all QTP ecosystem types, except for deserts. The updated NEE prediction dataset for the QTP provided essential data for advancing regional carbon cycle research.