ESA's Arctic Weather Satellite (AWS) is a novel mission to demonstrate the ability of polar-orbiting satellites to improve short-time forecasts and nowcasts of Arctic weather. Although the payload consists of a state-of-the-art microwave radiometer, the mission is designed in a cost-effective manner and, if successful, will serve as a blueprint for the Sterna constellation of satellites, which is under consideration by EUMETSAT. The AWS was launched in August 2024 and this highlight paper describes the mission, the radiometer and the state of the mission towards the end of the commissioning phase.

Low-cost sensors have been increasing used to measure air pollutants in environmental epidemiology. This work investigated the calibration and performance evaluation of PM2.5 and NO2 sensors, and introduced novel methodologies for field sensor validation during deployment. The manuscript is thorough and systematic in data treatment, and could be used a best practice guide for the application of sensors to air pollution and epidemiological studies.

Laitinen et al. demonstrate the remarkable agreement between two independent greenhouse gas observation systems (GAW and ICOS) at the Pallas station in Finnish Lapland, confirming the high accuracy and reliability of long-term CO₂ and CH₄ measurements in the Northern Hemisphere. Their results strengthen confidence in atmospheric monitoring data critical for carbon cycle research.

Obtaining a better understanding of how the fire-perturbed atmosphere may ignite more fuel is important to firefighters, but it is also a topic of interest for the general public. If large enough, fires can grow by feeding themselves. Atmospheric measurements during a fire can help scientists and firefighters better understand how the fire will evolve and whether there is a risk that the fire will run out of control. The authors show that using sonde measurements during the fire enables firefighters to better predict how it will evolve, thereby improving their security. At the same time, such measurements provide a valuable dataset for scientific model testing and development.