The Balloonborne Cloud Observing micrOLidar (BeCOOL) is an airborne profiler designed to be operated from the stratosphere. It weights less than 6 kg and requires on average less than 4 W to work automatically onboard a gondola attached below a stratospheric balloon. Given its sensitivity and spatial resolution, this microlidar can be used to characterize the optical properties and the life cycle of cirrus clouds, or to calibrate and validate satellite observations of clouds and aerosol layers.

The vertical distribution of aerosols governs their interactions with solar radiation and clouds, making it a key factor in their climatic and environmental effects. Polarization provides independent constraints that reduce ALH (aerosol layer height)–AOD (aerosol optical depth) coupling. A joint optimal estimation method is developed using HARP2 (Hyper-Angular Rainbow Polarimeter-2) observations.

This study develops a new artificial intelligence method to retrieve daytime aerosol optical parameters using low-cost All-Sky Imagers. By training a model with high-precision data, we successfully estimated the aerosol optical depth and single scattering albedo simultaneously. Our results show high accuracy across different global regions. This approach is much faster than traditional complex calculations, making it easier to deploy dense observation networks to improve climate research.

We present a new structure function model to estimate the turbulence energy dissipation rate using lidar velocities. The model corrects for turbulence filtering due to the lidar probe volume by applying a Gaussian weighting function. By utilizing the high 3 m range-gate resolution of the BEAM 6x pulsed lidar, we achieve excellent agreement between turbulence energy dissipation rate values derived from lidar and sonic anemometer at three heights, with correlation coefficients exceeding 0.9.

A single-scattering formulation of the color index is presented to investigate the physical mechanisms governing the CI maximum observed during twilight in the presence of high-altitude clouds. Within this framework, the maximum is shown to occur at the solar zenith angle (SZA) for which the relative SZA-variations of the zenith intensity become equal at the two selected wavelengths. The formulation is validated against Monte Carlo radiative transfer simulations, showing good agreement.

Cloud properties from three ATLID Level 2 products (A-TC, A-FM, A-CTH) of the EarthCARE satellite mission are validated using independent airborne lidar observations collected during satellite underflights in the tropics and extratropics. The products reliably represent cloud pixel distribution and cloud top height; though ice cloud pixels and cloud top height are slightly overestimated. Comparison with a more recent baseline shows improvements, supporting their use for cloud property studies.

This study investigates how fast-moving air currents close to the ground influence the vertical transport of dust over Hefei in eastern China. Using laser-based wind observations during two dust events, it shows that one event rapidly brings dust down to the surface, whereas the other keeps dust suspended at higher altitudes and delays surface pollution. These findings improve understanding of how dust is redistributed in the lower atmosphere and help improve weather and air-quality forecasts.

Ocean evaporation transfers heat and moisture to the atmosphere, shaping our weather and climate. Yet humidity just above the ocean is difficult to measure from space. Here we show that lasers measuring low cloud base height can infer near-surface humidity. Measurements from ships, aircraft, and weather balloons are used to validate the method. Applied to satellites, this method could help fill gaps in humidity measurements over the ocean.

This study shows that balloon-borne instruments with low-cost particle sensors can reliably measure how airborne particles are distributed with height in the atmosphere. The sensors were tested during field measurements in southeastern Poland which identified particle layers transported over long distances including wildfire smoke and desert dust. The results indicate that this approach can improve aerosol observations and support better representation of aerosol processes in atmospheric models.

Retrieving land surface temperature from thermal radiation is difficult because temperature and emissivity are strongly coupled. We developed a conditioning-controlled method that separates these quantities using paired ground-based longwave measurements. Tests with SURFRAD (Surface Radiation Budget Network) and BSRN (Baseline Surface Radiation Network) observations and known-truth simulations demonstrate stable retrievals and quantify their uncertainty without requiring satellite information.

Accurate measurements of carbon dioxide and water vapour exchanges are essential for understanding climate change. Using data from 38 European observation sites, we compared two commonly used correction methods and found that one provides more robust and consistent results, especially for water vapour. The study also revealed differences with current network processing procedures, highlighting opportunities to improve the reliability of long-term ecosystem observations.

The Earth Cloud, Aerosol, and Radiation Explorer (EarthCARE) satellite was recently launched and its data needs to be validated. This work focus on the comparison of the data observed from the radar of EarthCARE and from the ground radars of the European Aerosol, Clouds and Trace Gases Research Infrastructure network. We find a very small difference between the data observed by the satellite and the data from the ground, confirming the high quality of the satellite’s radar calibration.

We analyzed satellite observations of over 6000 power plants worldwide to determine when their nitrogen dioxide plumes are visible from space. Using machine learning, we found that detectability depends not only on the amount emitted but also on wind, terrain elevation, surface brightness, and satellite viewing angle. Identical emissions can therefore be seen or missed depending on local conditions. Accounting for these factors can improve satellite-based estimates of air pollution.

The new technique for the clouds screening of aerosol optical depth is presented. It employs measurements of the sky radiances at smallest scattering angle to detect cirrus clouds which otherwise are difficult to detect by other methods. The method employs the smoothness of the time series of measurements throughout a day as a criterion for cloud-free conditions.  Sharp spikes in the time series are detected and associated with clouds.

We present a case study that aimed to develop an inexpensive yet precise fast-response carbon dioxide and water vapour sensor. A working prototype was developed and field-tested against a scientific eddy covariance setup. Attention was paid to internal auto-calibration procedure such that signal drifting was avoided and the instrument was capable of measuring fluxes with high correlation relative to the reference setup.

Methane emissions from cities are difficult to quantify using direct measurements. Satellites like TROPOMI can help with this. This study develops new ways to calculate emissions from satellite data and tests new methods for London, New York and Los Angeles in recent years.