Information on the energy transported by atmospheric gravity waves (GWs) is crucial for improving atmosphere models. Most space-based studies report the potential energy. We use Aeolus wind data to estimate the kinetic energy (density). However, the data quality is a challenge for such analyses, as the accuracy of the data is in the range of typical GW amplitudes. We find a temporal coincidence between enhanced or breaking planetary waves and enhanced gravity wave kinetic energy density.

This work presents and evaluates an algorithm that automatically conducts the steps of fitting peaks and identifying formulas – necessary but time-consuming steps for most applications of mass spectrometry in atmospheric science. The aim of the algorithm is to save researchers working on these tasks significant amounts of time and allow them to proceed with their analysis. The work demonstrates that this algorithm can achieve the goal of speeding up analysis and provide accurate formulas.

We developed an advanced algorithm for global retrieval of TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO₂ vertical column densities with much improved consistency. Sensitivity tests demonstrate the complexity and nonlinear interactions of auxiliary parameters in the air mass factor calculation. An improved agreement is found with measurements from a global ground-based instrument network. The scientific retrieval provides a useful source of information for studies combining HCHO and NO₂.

We wanted to know how well the Dräger Tube method (DTM) is able to measure ammonia in agricultural experiments on small plots. We therefore compared the accuracy and sensitivity of Dräger Tubes in laboratory tests with more advanced analyzers. Dräger Tubes had a detection limit 3 to 4 times higher than expected. Since there are areas where the use of advanced analyzers is not feasible, the DTM should be improved, or simple and cost-effective measuring methods should be developed.

Sonic anemometers measure wind velocity in three dimensions. They are used worldwide to help assess the trace gas exchange, critical to understanding climate change. However, their physical framework interferes with the flow they measure. We present a new way of correcting measurements from sonic anemometers of several types. The method uses measurements of vertical wind velocity and other turbulent velocities, compares their ratios, and from this yields correction factors for sonic anemometers.

This study demonstrates the ability of a new method delivering the vertical distribution of particle shape to highlight riming and aggregation processes, identifying graupel and aggregates, respectively, as isometric particles. The distinction between these processes can be achieved using lidar or spectral techniques, as demonstrated in the case studies. The capability of the new method to identify rimed particles and aggregates without differentiating them can simplify statistical work.

Air pollutants such as particulate matter with diameters of 10 µm and 2.5 µm or less (PM₁₀ and PM_2.5) can cause adverse public health and environment effects; therefore their regular monitoring is crucial to keep pollutant concentrations under control. Our study demonstrates the potential of high-resolution aerosol optical depth (AOD) data from the Geostationary Environment Monitoring Spectrometer (GEMS) satellite to estimate ground-level PM concentrations using machine learning models. 

Our study presents a new method, the solar background calibration method, which improves temperature determinations in rotational Raman lidar systems. By utilizing background solar radiation, this technique offers more continuous and reliable temperatures independent of external measuring instruments. This new method enhances our ability to monitor and understand atmospheric trends and their association with climate change with greater accuracy.

The drone-based Flying Laboratory FLab was developed to simultaneously measure aerosol (number concentration, size distribution, and black carbon), trace gas (O₃, CO₂), and meteorological variables. FLab was characterized in the field regarding limitations and biases due to different flight maneuvers. Two application cases are presented: analysis of the development of the lowermost troposphere (up to 300 m) and successfully bridging ground-based and aircraft- and radiosonde-based measurements.

This study explores the potential of two newly launched commercial Global Navigation Satellite System (GNSS) radio occultation (RO) satellite missions for advancing Arctic lower-atmospheric studies. The products have a good sampling of the lower Arctic atmosphere and are useful to derive the planetary boundary layer (PBL) height during winter months. This research is a step towards closing the observation gap in polar regions due to the decomissioning of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC-1) GNSS RO mission and the lack of high-latitude coverage by its successor (COSMIC-2).

Multi-layer aerosol optical depth (AOD) is retrieved using the geostationary Spinning Enhanced Visible and Infrared Imager (SEVIRI) and machine learning, trained on Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data. The model provides AOD at a 3 km × 3 km spatial and 15 min temporal resolution over Europe. It accurately captured multi-layer AOD dynamics during Saharan dust transport and the Mount Etna eruption, demonstrating consistent physical accuracy.

A dual-field, integrated lidar system has been developed to detect atmospheric temperatures from the near surface to 60 km over Qingdao, China. Temperature profiles from the near surface to 60 km are derived by pure rotational Raman and Rayleigh scattering techniques using a single integrated lidar system. The results prove the system can make fine measurements of the atmospheric temperature profiles from the near surface to 60 km.

Waves are important as main drivers of different stratispheric patterns (streamers). We analyse changes in waves and infrasound characteristics related to streamers using continuous Doppler soundings and arrays of microbarometers in Czechia. Ground measurements using infrasound arrays showed that gravity wave propagation azimuths were more random during streamers than during calm conditions. Measurements in the ionosphere during streamers did not differ from those expected for the given time.

A Doppler lidar was placed in a highly built-up area in London to measure wakes from tall buildings during a period of 1 year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.

Commercial Global Navigation Satellite System (GNSS) radio occultation (RO) satellites are generally cheap and can generate a large volume of globally distributed observations in a short period of time. To evaluate the practical application value of these data, we must assess their quality. We evaluate the quality of YUNYAO RO data. By using the “three-cornered hat” method and comparing with data from Metop-C and COSMIC-2, it was found that the YUNYAO GNSS-RO data are of high quality. 

This study introduces the JAXA EarthCARE Level 2 (L2) cloud product using satellite observations and simulated EarthCARE data. The outputs from the product feature a 3D global view of the dominant ice habit categories and corresponding microphysics. Habit and size distribution transitions from cloud to precipitation are quantified by the L2 cloud algorithms. With Doppler data, the products can be beneficial for further understanding of the coupling of cloud microphysics, radiation, and dynamics.

Methane is a potent greenhouse gas. Trustable detection and quantification of methane emissions at facility level are critical for identifying the largest sources and prioritizing them for repair. We provide a systematic analysis of several sources of uncertainty in drone-based methane emission surveys based on theoretical considerations and historical data sets. We provide guidelines for industry on how to avoid or minimize errors in drone-based methane emission quantification surveys.

This paper presents a supervised-machine-learning approach for the automatic isolation of nocturnal low-level jets (NLLJs) using observations from a radar wind profiler. This analysis isolated 90 southwesterly NLLJs observed from May to September 2017–2021, highlighting key features in the evolution and morphology of the mid-Atlantic NLLJ.

We developed a ground-based 110.836 GHz radiometer developed to measure the stratospheric ozone profile over Seoul, South Korea. To ensure precise measurements and correct the atmospheric spectrum, we employed hot–cold calibration along with continuous tipping curve calibration. Prior to the retrieval process, both pointing and frequency offsets were corrected. We provide stratospheric ozone profiles from 2016 to 2021, which are compared with collocated satellite observations.

The primary measurement result delivered by a Fourier transform spectrometer is an interferogram, and the spectrum required for further analysis needs to be calculated from the interferogram by Fourier analysis. The paper deals with technical aspects of this process and shows how the reconstruction of the spectrum can be optimized.

The dynamics of thunderclouds are studied using cloud radar. Supercooled liquid water and conical graupel are likely present, while chain-like ice crystals may occur at cloud top. Ice crystals are vertically aligned seconds before lightning and resume their usual horizontal alignment afterwards in some cases. Updrafts and downdrafts are found near cloud core and edges respectively. Turbulence is strong. Radar measurement modes that are more suited for investigating thunderstorms are recommended.

A portable laser-flash photolysis Faraday rotation spectrometer for measuring atmospheric total hydroxyl (OH) reactivity was developed, with optical box dimensions of 130 cm × 40 cm × 35 cm. It features a pump–probe multi-pass cell with a high overlapping factor of 75.4 %. The instrument’s precision and uncertainty are 1.0 s^-1 (1σ, 300 s) and within 2 s^-1, respectively. This portable, cost-effective instrument expands current measurement capabilities and is convenient for field applications.

Over a 3-week period, simultaneous measurements were conducted using a Doppler lidar and a 1.3 GHz radar wind profiler in Japan. Although the instruments had no range overlap, turbulence kinetic energy dissipation rates were estimated through various methods in convective boundary layers. Hourly averaged estimates showed good agreement, within a factor of approximately 2, suggesting that both instruments and methods provide consistent dissipation rate values.