Deep convective clouds are difficult to locate precisely in weather satellite images due to viewing-angle distortions. We tested a method that estimates cloud-top heights from infrared temperature data alone — available on weather satellites for over 40 years without need for advanced sensors. The method proved accurate enough to correct these distortions, enabling consistent long-term storm cloud records across all generations of European weather satellites using a single, uniform approach.

For the X-band radar in Bonn, the birdbath method has proven to be insufficient for calibrating differential reflectivity. This study raises awareness of the need for critically applying the birdbath method. A novel technique for calibrating the reflectivity factor is presented and compared with satellite measurements, serving as ground truth, and a known standard calibration method. The offset values agree well with the satellite and even exceed the accuracy of the standard calibration method.

Continuous monitoring of Earth's energy balance from space is essential for understanding climate change. Beyond the next planned mission, continuity of these observations remains uncertain. Earth-viewing observations from a CubeSat designed to observe the Sun were compared to established Earth-observing instruments, showing close agreement. Results suggest CubeSats could reduce the risk of gaps in long-term records and that solar-monitoring instruments could be designed to observe Earth, too.

Better characterization of precipitation characteristics has important implications for simulated storm behaviors and remotely-sensed retrievals of cloud intensity. We use a unique radar technique to estimate the fall speeds of media found within deep tropical clouds. These retrievals can be performed within intense storm conditions that are otherwise impractical to sample. Our observations suggest mixed media or graupel fall speeds are contextually faster than prior references.

This study presents a lidar measurement strategy developed during a one-year offshore campaign. A ship-based scanning lidar provided high-resolution vertical wind measurements used to study turbulent mixing and atmospheric waves, complemented by wind speed profiles from a co-located wind profiler. A scanning lidar on a fixed platform observed turbine wakes, supported by the ship-based profiler. The results demonstrate the value of the strategy and dataset for wind energy and atmospheric science.

Light scattering is important in the atmosphere, oceans, snow, ice, paints, and many other materials. We developed EigenFlux, a new open-source method for simulating how light moves through complex materials. It remains accurate, stable, and efficient even when scattering is extremely strong or highly directional, conditions that can challenge existing methods. This broadens the range of systems that can be modeled reliably.

We monitored nitrous oxide in a pilot wastewater treatment plant in real time to understand how microbes produce and remove this greenhouse gas. We designed and tested a laser-based analytical setup, with which we were able to show that denitrification is the main source of nitrous oxide emissions and that low oxygen concentrations enhances nitrous oxide removal. Our approach offers a new way to monitor the wastewater treatment processes and to cut climate-relevant nitrous oxide emissions.

Cloud radars are used to measure air motion, clouds, and precipitation, but small pointing errors can reduce their accuracy. We developed a method to detect these errors using routine weather balloon observations. Tests with several radar systems in different environments showed that the method can identify small but important pointing biases, helping improve the accuracy and long-term consistency of weather and climate observations.

Radar mosaic data is crucial for accurate and timely disaster weather warnings. However, missing regional data – caused by hardware failures or delayed file transfers, severely limits its quantitative use. Existing methods either struggle with complex and diverse missing patterns; or rely on known missing masks. To address this, We propose a deep learning–based radar echo restoration method that requires no explicit missing-data prior and delivers reliable, real-time performance.

Chemical ionization mass spectrometry is widely used to detect condensable vapors as sulfuric acid and highly oxygenated organic molecules, but results across studies are not always comparable. In summer 2024, an intercomparison campaign involving six instruments was conducted at a boreal forest site. Comparable measurements were achievable when all calibration and correction factors were applied. Instrument behavior depended more on inlet design and operating conditions than reagent ion choice.

To counterbalance human-caused global warming, highly controversial geoengineering techniques, based on stratospheric aerosol injection (SAI), have been proposed as a complement to climate change mitigation. Possible unilateral SAI deployments or tests are a risk. We show that existing satellite instruments do not have the capability to detect unilateral SAI experiments and we propose a future satellite technique, infrared limb emission sounding, that can provide this missing capability.

The dual-frequency radar can retrieve raindrop size distribution but causes ambiguity between dual-frequency ratio and raindrop diameter for small drops. To solve this, our study added a third radar frequency, using scattering simulations based on real raindrop observations. We established clear links between different dual-frequency ratio and raindrop size. Results show the ambiguity is greatly reduced and our method outperforms conventional ones, especially in light rain detection.

CONIOPOL (CONIOlogy + POLarization) is a new algorithm for continuous, real-time classification of aerosols and hydrometeors using a single-wavelength polarization-enabled automatic lidar. Applied to one year of CL61 observations in Belgium, it provides physically consistent aerosol typing and seasonal patterns. Comparisons with CAMS (Copernicus Atmosphere Monitoring Service) and sensitivity tests support its potential for operational monitoring and long-term aerosol climatology.

This study investigates the spectral characteristics of zenith sky radiances under clear- and cloudy-sky conditions using SKYNET sky radiometer observations. It proposes a simple, physically interpretable method for distinguishing sky states and demonstrates that wavelength-dependent radiance information can support reliable sky-state detection across diverse atmospheric environments.

Long-term measurements of atmospheric CO₂ have been conducted at Schauinsland station in southwest Germany since 1972. In order possibly to relocate the air intake line from 12 m to 35 m above ground, we compared three years of parallel CO₂ and CH₄ measurements. We find systematic differences in diurnal and seasonal variations for CO₂, but not for CH₄. The results of our study indicate that measurements should be taken at both heights to ensure consistency with historical records.