Global source–receptor-relationship database for integrated tropospheric ozone observations from multiplatform datasets in western North America during 1994–2021

Abstract. Long-term atmospheric ozone observations in Western North America (WNA) provide essential data for assessing tropospheric ozone trends. Backward atmospheric simulations based on these observations establish the source–receptor relationships (SRRs) to improve our understanding of the factors driving ozone trends across different regions, time periods, and atmospheric layers. In this study, we integrated 28 years of ozone observations (1994–2021) from ozonesondes, lidar, commercial aircraft, and aircraft campaigns across WNA, spanning the upper atmospheric boundary layer, free troposphere, and upper troposphere (i.e., 900 to 300 hPa). We integrated the multiplatform datasets using a data fusion framework to generate 553 608 gridded ozone receptors. For each receptor, we use the FLEXible PARTicle (FLEXPART) dispersion model, driven by ERA5 reanalysis data, to produce the SRRs calculations, providing global simulations at high temporal (hourly) and spatial (1°×1°) resolution from the surface up to 20 km a.g.l. (above ground level). This SRR database retains detailed information for each receptor, including the gridded ozone value product, which enables user to illustrate and identify source contributions to various subsets of ozone observations in the troposphere above WNA over nearly 3 decades at different vertical layers and temporal scales, such as diurnal, daily, seasonal, intra-annual, and decadal. More generally, the calculated SRRs are applicable to any study looking to evaluate origins of airmasses reaching WNA. As such, this database can support source contribution analyses for other atmospheric components observed over WNA, if other co-located observations have been made at the spatial and temporal scales defined for some or all of the gridded ozone receptors used here. The entire dataset is publicly available at https://doi.org/10.5067/ASDC/WNA-BackTraj (Cui et al., 2025).