GloPINE dataset: model-ready measurements of INP concentrations using PINE instruments

Ice-nucleating particles (INPs) are a subset of aerosol particles that facilitate the freezing of supercooled cloud droplets heterogeneously and influence the radiative properties of supercooled clouds. The role of INPs in the Earth system remains unquantified in part due to poorly constrained representations of their spatial distributions and properties in global and regional models. In this study, we present a quality controlled dataset (https://doi.org/10.5281/zenodo.16745514, Herbert et al., 2026), called GloPINE, comprising 70 000 h of INP concentrations measured using Portable Ice Nucleation Experiment (PINE) instruments that use an expansion chamber to make automated long-term (months to years) and high temporal resolution (<10 min). We collate measurements from 20 recent ground-based PINE field campaigns in the Northern Hemisphere conducted between January 2018 and December 2023, totaling more than 400 000 expansions, sampling over 800 m$^3$ of ambient air, and performed under conditions relevant for mixed-phase clouds. In the GloPINE dataset, we subset and average the PINE measurements across synoptically relevant time intervals of 6 h and 2 K temperature bins, providing 36 000 INP measurements. Combining PINE expansions over these intervals enhances counting statistics at higher freezing temperatures, decreases the lower limit of measurable INP concentrations, and provides an INP dataset readily applicable to model simulation data and meteorological reanalysis products. Together with complementary INP datasets, GloPINE provides a valuable resource for advancing model evaluation, improving INP source attribution, and informing parameterizations across the full temperature range over which aerosols influence ice formation in clouds.