This study examined whether adding large volumes of satellite-based atmospheric data can improve weather forecasts in a Navy model. Using a series of controlled experiments, we tested different ways of incorporating the data. Simply adding it introduced biases, but adjusting how the data were used led to clear improvements. All missions contributed positively, with Spire providing the largest total benefit and COSMIC-2 the highest impact per observation.

Quality control of ground-based solar radiation measurements is essential for climate and energy research. The current tests apply a global rule that is often too loose, missing anomalies, or too strict in polar regions, rejecting valid data. Using 75 stations, this study identifies seven radiation climates and configures regime-specific quality-control limits. The new limits better match local conditions, retaining valid polar data while restoring sensitivity in aerosol-polluted regions

A multi-channel fluorescence lidar can effectively analyze smoke–urban aerosol mixtures and retrieve smoke mass concentration in the planetary boundary layer (PBL), with a detection threshold of order 0.1 µg · m⁻³. Measurements over Moscow (2023–2024) detected smoke in 59 of 67 sessions. Long-range transported smoke contributed ∼1 µg · m⁻³ to the PBL, while regional fires from southern Russia caused concentrations up to 50 µg · m⁻³.

CH₄ observations from space are an essential component for improving our estimates of CH₄ emissions from fossil fuels and natural sources. We utilized GHGSat, a CH₄ plume mapping satellite constellation, to update the fossil fuel emission inventory in the Western Siberian Lowlands to understand how including plume observations in models changes emissions estimates. Our approach resulted in a reduction in CH₄ emissions attributed to wetlands.

Understanding air motion within clouds is essential for weather and climate research. A new satellite launched in 2024 can observe how clouds move around the world for the first time. In this study, we compare three observation modes using real satellite data. We find that some modes provide more accurate measurements but reduce the ability to observe very high clouds and increase the risk of false signals. Our results show which observation modes work best in different regions of the world.

In the present study we investigated how aerosols, and specifically dust, affect solar radiation and energy production by investigating several dust events across multiple sites in the Mediterranean Basin between 2021 and 2022 through ground-based observations and model simulations. The results revealed that dust can significantly attenuate solar radiation and, therefore, lead to considerable losses in solar power generation, specifically in the case of solar tracking systems.

Methane is a powerful greenhouse gas, and cutting its emissions can slow climate change in the near term. We have created ML-SPERE, a new machine-learning based method that uses TROPOMI observations and weather data to better estimate emission rates for large methane plumes. It has proved more accurate than the Integrated Mass Enhancement (IME) method when tested on simulated satellite observations. When applied to real TROPOMI plumes, ML-SPERE produces estimates that agree with other methods.

Scarce reliable greenhouse‑gas observations plague inland Antarctica. The low‑power (<350 W) CRUX‑1.0 integrates four subsystems for simultaneous CO₂‑O₃ monitoring. Its one‑month Taishan Station test shows stable performance, with post‑calibration CV  (coefficient of variation) < 5.6 %. Measured mixing ratios exhibit good comparability with South Pole Station data. Capable of unattended operation, CRUX‑1.0 is promising for data‑scarce polar inland deployment.

In this study, maps of the planetary boundary layer over Europe were generated by integrating multiple data sources. The results show higher accuracy compared with the widely used ERA5 reanalysis. The proposed regression kriging method performed well in estimating the height of the boundary layer at 12:00 UTC, and to a lesser extent at 00:00 UTC.

Urban areas account for a substantial share of global greenhouse gas emissions, yet measuring these emissions precisely is challenging due to spatial variability. This study implemented an advanced laser measurement technique, to directly average this spatial variability by measuring over a 3.1 km path, using only commercial parts. The high measurement precision and reliable operation, demonstrates that this technique is now accessible to the broader atmospheric measurement community.

This study explores new ways to better understand urban air pollution by combining traditional monitoring with portable sensors, mobile measurements, and public participation. Using European city case studies, the research shows that these approaches can identify pollution hotspots in greater detail and make air quality information more accessible to communities and decision-makers. The work highlights how improved monitoring supports healthier cities and more effective environmental policies.

This study analyses seven years of dust events over Cyprus to identify their origin and quantify their impact on surface solar radiation. Most events originated from the Sahara. Dust reduces surface solar radiation, leading to surface cooling, while also causing atmospheric heating and cooling at the top of the atmosphere. Surface reductions in solar radiation reach about 5 %–15 % on average, with effects mainly controlled by dust amount.