Two decades of operations and performance for the MAESTRO instrument are reviewed. Topics addressed include: (a) occultation measurement schemes, (b) MAESTRO's field of view (FOV) on the Sun, (c) FOV changes on the solar disk during occultations and their impact on calculated transmittances, (d) the relation between the MAESTRO and ACE-FTS FOVs, (e) verification of wavelength assignment, and how it has been affected by thermal environment changes, and (f) the determination of MAESTRO tangent heights.

We developed a new photoreactor to study how organic compounds react in water under atmospheric-relevant conditions. Experiments were performed on smoke-related chemicals under controlled light, temperature, and humidity mimicking cloud and haze environments. Our results showed that saltier water speeds particle formation and changes their composition, providing new insights into atmospheric aerosol chemistry.

Entrainment of dry warm air from above the cloud into the cloud layer modulates cloud properties and lifetime. Despite its importance, observations of entrainment remain elusive. Presented here is a technique to derive entrainment velocities using cloud top heights, and horizontal winds from the Multi-angle Imaging Spectro-Radiometer (MISR). The results motivate application of the technique to generate global climatology, and perform process-level and model-evaluation studies.

UV absorption and electrochemical O₃ sensor measurement techniques suffer from interferences, especially from SO₂, which is a main constituent of volcanic plumes. Only chemiluminescence (CL) O₃ monitors have no known interference with SO₂. However, modern CL O₃ monitors are impractical because they are heavy and bulky. We developed and applied a lightweight version of a CL O₃ instrument (l.5 kg, shoebox size) and present the result of those drone based CL O₃ measurements.

This research develops a machine learning approach to estimate atmospheric temperature and relative humidity profiles using satellite and weather data. The results showed that our method could accurately retrieve profiles with a high degree of precision. However, we found some limitations in very humid conditions, suggesting that further improvements to the model are needed. Our findings could help enhance the reliability of atmospheric measurements and contribute to better weather predictions.

Clouds strongly influence weather and climate, yet long-term observations are rare in southern Europe. We analyzed five years of measurements in Granada, Spain, to study how different cloud types vary through the seasons. We developed a new method that improves cloud classification and found clear differences in height, thickness, and water content. These results provide valuable reference data to support satellite observations and climate models.

In this manuscript a new fully polarimetric radiometer for ground-based temperature sounding, TEMPERA-C (Campaign Temperature Radiometer), is presented. The advantages of the fully polarimetric approach are discussed, and a fully polarimetric calibration method is described in detail. The final measurements and the continuous series of temperature retrievals from the high altitude research station on the Jungfraujoch are also shown in this manuscript.

The 17 operational German weather radars regularly point vertical for calibration. We proof that this data also contains valuable scientific information. To demonstrate this, we use it to detect the melting level in clouds and strong snowflake riming. Riming is the collision of a snowflake with liquid droplets, which can create precipitation. We analyze the frequency and temperature dependence of riming for all German weather radar sites and relate it to the local precipitation climatology.

We developed a new way to measure ultrafine particles released by aircraft engines using an aerosol lidar sensor. This method allows us to quickly check emissions from a distance, without needing to collect samples directly from the engines. Our results show that this approach works well and could help airports and regulators better monitor air quality and reduce the environmental impact of aviation.

This study shows that low-cost CO₂ sensors, when individually corrected using multi-point linear regression, can achieve 1–2 % accuracy. Deployed in Seoul, they revealed local pollution patterns like idling emissions at intersections and the "piston effect" in tunnels. With proper correction, these sensors enable affordable, detailed urban CO₂ monitoring.

We introduce BAMF+HS (Bayesian Autocorrelated Matrix Factorisation+Horseshoe), an enhanced Bayesian receptor model for particulate matter (PM) source apportionment. By applying a regularised horseshoe prior to the chemical composition matrix, BAMF+HS enforces sparsity, filtering out irrelevant species and improving source separation. Tests on synthetic and real datasets show BAMF+HS consistently outperforms previous models in accuracy and clarity.

Clouds play a crucial role in the Arctic climate system, particularly cloud liquid water droplets. However, there is currently a measurement gap for cloud liquid water over sea ice. We present a method to estimate cloud liquid water over Arctic sea ice using airborne passive microwave observations from the HALO-(𝒜𝒞)³ campaign. Evaluation with other airborne sensors highlights both the limitations and potential of the retrieval. This approach is promising for future applications to satellites.

We develop a physics-constrained deep-learning framework to retrieve vertical profiles of particulate matter <2.5 µm chemical components from lidar measurements. Comparisons with surface, tower, and aircraft measurements validate the performance of the framework. A six-year vertical profile dataset generated for Beijing reveals that organic matter and nitrate are dominant chemical components. This work offers a new perspective on the lidar inversion of chemical component profiles.

This study introduces the maximum diameter (D_max) of precipitation particles measured by a two-dimensional video disdrometer (2DVD) as a novel parameter. D_max is applied in a cloud seeding study during the Cloudlab campaign and, for the first time, in a MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) case to evaluate the LIRAS (LIdar RAdar Synergy )-ice remote-sensing retrieval of in-cloud ice crystal size and number. Both quantities agreed well with the 2DVD measurements under ideal conditions, highlighting the potential of D_max for precipitation studies.

We present a simple workflow for high-precision δ¹³C-CO₂ analysis from 1 mL air samples using cryogenic pre-concentration and continuous-flow isotope-ratio mass spectrometry (IRMS). The method combines vial conditioning, dual sealing, and −80 °C storage to minimise gas loss. It achieves ±0.1 ‰ precision and stable isotopic values for up to one week of storage. This low-cost approach enables high-frequency δ¹³C-CO₂ measurements in volume-limited systems such as microcosm or chamber experiments.