Validation of satellite HCHO over the remote marine regions is relatively low, and modeled HCHO in these regions is usually added as a global satellite HCHO background. This paper intercompares three satellite HCHO retrievals and validates them against in situ observations from the NASA ATom mission. All retrievals are correlated with ATom-integrated columns over remote oceans, with OMI SAO (v004) showing the best agreement. A persistent low bias is found in all retrievals at high latitudes.

Atmospheric chemistry of the diverse pool of reactive organic carbon (ROC; all organic species excluding methane) controls air quality, both indoors and outdoors, and influences Earth's climate. However, many important ROC compounds in the atmosphere are difficult to measure. We demonstrate measurement of diverse ROC compounds in a single instrument at a forested site. This approach can improve our ability to measure a broad range of atmospheric ROC.

The radiative forcing due to contrails is of the same order of magnitude as aviation CO₂ emissions but has a higher uncertainty. Observations are vital to improve our understanding of the contrail lifecycle, improve models, and measure the effect of mitigation action. Here, we use ground-based cameras combined with flight telemetry to track visible contrails and measure their lifetime and width. We evaluate model predictions and demonstrate the capability of this approach.

This work investigates whether machine learning (ML) can offer an alternative to existing methods to map radio occultation (RO) products, allowing the extraction of information not visible in direct observations. ML can further improve the results of Bayesian interpolation, a state-of-the-art method to map RO observations. The results display improvements in horizontal and temporal domains, at heights ranging from the planetary boundary layer up to the lower stratosphere, and for all seasons.