Satellite ozone observations have been considered poor predictors of ozone at ground level. Here we evaluate the ability of one satellite product to estimate ground-level ozone globally over 18 years. The satellite product shows a modest correlation with ground-level ozone that does not vary strongly with year, season, world region, or ozone level. Using a linear regression, we translate the satellite product into a global monthly ground-level ozone dataset for use in future data fusion studies.

Aerosols affect climate by scattering and absorbing sunlight and heat. Light detection and ranging instruments can track aerosol distributions, but turning their signals into atmospheric information depends on particle size, absorption, and humidity. We developed a ground-measurement method and tested it in Slovenia. The results provide optical constraints that support more reliable retrieval of aerosol profile information when different particle types are mixed.

We connect two very different types of precipitating stratocumulus cloud models. The first model is a high-resolution simulation that can realistically represent clouds. The second model is a simple, 1D equation that interprets clouds as prey and rain as the predator of clouds. We evaluate the extent to which a simplified cloud model can represent selected aspects of a realistic cloud simulation under different meteorological conditions, highlighting both successes and limitations.

This study provides definitive experimental confirmation from space that the observed impact of CO₂ growth on longwave spectral radiances, in the troposphere and stratosphere, follows theory and that the results are independent of CO₂ uncertainties. By refining and extending a new methodology that disentangles the observational effects of CO₂ on Earth’s longwave spectra, from temperature and water vapor, the results conclusively confirm a critical foundation of the science of global warming.