Reconstructed daily ground-level O₃ in China over 2005–2021 for climatological, ecological, and health research

Abstract. Accompanied by the continuous declines of PM_2.5, O₃ pollution has become increasingly prominent and has been targeted by the Government of China to protect climate, ecosystem, and human health. Although satellite retrievals of column O₃ have been operated for decades and nationwide monitoring of ground-level O₃ has been offered since 2013 in China, climatological variability of ground-level O₃ remains unknown, which impedes understanding of the long-term driver and impacts of O₃ pollution in China. Here we develop an eXtreme Gradient Boosting (XGBoost) model integrating high-resolution meteorological data, satellite retrievals of trace gases, etc. to provide reconstructed daily ground-level O₃ over 2005–2021 in China. Model validation confirms the robustness of this dataset, with R² of 0.89 for sample-based cross-validation. The accuracy of the long-term variations has also been confirmed with independent historical observations covering the same period from urban, rural and background sites. Our dataset covers the long time period of 2005–2021 with 0.1°×0.1° gap-free grids, which can facilitate climatological, ecological, and health research. The dataset is freely available at Zenodo (https://zenodo.org/record/6507706#.Yo8hKujP13g; Zhou, 2022).