GlobalHighO3: Big Data Seamless 10 km Global Ground-level O3 Dataset over Land

GlobalHighO3 is one of the series of long-term, full-coverage, global high-resolution and high-quality datasets of ground-level air pollutants over land (i.e., GlobalHighAirPollutants, GHAP). It is generated from big data (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence by considering the spatiotemporal heterogeneity of air pollution. 

Here is the first big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 10 km (i.e., D10K, M10K, and Y10K) global ground-level MDA8 O3 dataset over land since 2000 to the present. This dataset yields a high quality with a cross-validation coefficient of determination (CV-R2) of 0.86 and a root-mean-square error (RMSE) of 3.99 ppb on a daily basis.