We introduce a new cloud retrieval algorithm using the O₂–O₂ absorption band at 477 nm to generate harmonized cloud datasets from OMI and TROPOMI. The algorithm improves upon the OMI O₂–O₂ operational cloud algorithm in several aspects. The new approach improves consistency in cloud parameters and NO₂​ retrievals between two sensors.

A method is introduced to expand the observational capability of a diode-laser-based lidar system. This method allows the lidar transmitter to change the laser pulse characteristics from one shot to the next. We use this capability to lower the minimum altitude of observation and to observe clouds with higher range resolution.

A novel, reusable ozone filter design for the monitoring of biogenic volatile organic compounds using sorbent tubes and multi-tube samplers was evaluated. The ozone filters proved high efficiency in retaining high recovery rates across different environmentally relevant levels of relative humidity and ozone concentrations while safeguarding the sorbent material in both laboratory and field experiments. The filter design has the advantage of not requiring additional equipment or regular checks.

A large balloon was launched in summer 2021 in the Arctic to carry instruments for trace gas measurements up to 32 km, above the reach of aircraft. The main aims were to evaluate different techniques and atmospheric processes. We focus on halogenated greenhouse gases and ozone-depleting substances. For this, air was collected with the AirCore technique and a cryogenic air sampler and measured after the flight. A companion paper reports observations of major greenhouse gases.

Single-particle soot photometer (SP2) measures the mixing state (D_p/D_c) of coated black carbon (BC) using core-shell Mie theory and coating refractive index is set to 1.50+0i. The retrieved D_p/D_c contains error due to the non-sphericity of BC and coatings with various refractive indices. We reveal the remarkable effects of coatings on the D_p/D_c retrieval accuracy of SP2 based on optical simulation of fractal BC aerosols, and further evaluate the simple radiative forcing efficiency of coated BC.

This study evaluates PM_2.5 and NO₂ sensors for their use in health studies. Sensors were calibrated using data from reference instruments, and regression and machine learning models were evaluated, identifying opportunities and limitations in model transferability in both indoor and outdoor environments and showcasing the importance of integrating metadata such as activity logs and diffusive tubes to improve data validation and interpretation during deployment in the houses of the participants.

Marine boundary layer (MABL) water vapor is among the key factors to couple the ocean and atmosphere, but it is also among the hardest to retrieve from a satellite remote sensing perspective. Here we propose a novel way to retrieve MABL specific humidity profiles using the GNSS (Global Navigation Satellite System) Level-1 signal-to-noise ratio. Using a machine learning approach, we successfully obtained a retrieval product that outperforms the ERA-5 reanalysis and operational Level-2 retrievals globally, except in the deep tropics.

Biomass-burning aerosols (BBAs) from Central Africa are transported above stratocumulus clouds. The absorption of solar energy by aerosols induces warming, altering the cloud dynamics. We developed an approach that combines polarimeter and lidar to quantify this. This methodology is assessed during the AEROCLO-sA (AErosol RadiatiOn and CLOud in Southern Africa) campaign. To validate it, we used irradiance measurements acquired during aircraft spiral descents. A major perspective is the generalization of this method to the global level.

This is a reply to a recent article by Christoph Kiemle et al., critical of CO₂ measurements using continuous-wave (CW) lidar. We show CW lidar is not only capable of measuring range but also capable of measuring range to the required accuracy without the aid of an external altimeter.

Air pollution from airborne particles is a major health and environmental concern, especially in cities. Understanding the particles' sources is key to addressing this issue, but traditional methods require time-consuming sampling, delaying action. Our study introduces a real-time monitoring system that uses advanced instruments and software to track pollution instantly. This technology allows faster, more precise pollution analysis, helping cities create targeted strategies to improve air quality.

In this work, we describe the development of the Carbon monOxide Measurement from Ames (COMA) instrument for measurement of carbon monoxide (CO) and nitrous oxide (N₂O) aboard NASA's WB-57 high-altitude research aircraft. We detail the modifications and testing conducted as well as details of COMA's performance during research flights for NASA’s Asian summer monsoon Chemical & CLImate Project (ACCLIP) 2022 campaign.

Clouds and aerosol are important for weather and climate. Typically, pure water cloud droplets stay liquid until around −35 °C, unless they come into contact with ice-nucleating particles (INPs). INPs are a rare subset of aerosol particles. Using uncrewed aerial vehicles (UAVs), it is possible to collect aerosol particles and analyse their ice-nucleating ability. This study describes the test and validation of a sampling set-up that can be used to collect aerosol particles onto a filter.

The chemical properties of aerosols in the atmosphere significantly influence their impact on global climate and human health. The current study constructed an instrumental system (HEAC (high-efficiency aerosol collector)/ESI (electrospray ionisation)-Orbitrap-MS (mass spectrometer)) for the real-time chemical analysis of aerosol samples. The combined system successfully identified over 30 chemical compounds in aerosol samples in real time, showing the robustness of the technique for the chemical characterisation of aerosols under atmospherically relevant conditions.

This study presents, for the first time, the uncertainty analysis of the Ångström exponent assumption on the full set of retrievable optical properties obtained with Raman lidar. A quantitative comparison between the pure rotational and vibrational–rotational Raman lidar approaches is presented. A minor impact of a wrong Ångström exponent on the determined aerosol optical properties is found.

Global horizontal irradiance retrievals from satellite observations are affected by spatial displacements due to parallax and cloud shadows. We assess different approaches to correct for these displacements and quantify their added value by comparison with a network of ground-based pyranometer observations. The corrections are found to become increasingly important at higher spatial resolutions and are most relevant for variable cloud types.

Clouds affect Earth's energy balance, with high-altitude cirrus clouds contributing to atmospheric warming. While active satellite sensors are the most accurate for detecting cirrus clouds, they are not ideal for long-term studies. This study compares Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data, testing six MODIS methods, one MODIS-based test, and two International Satellite Cloud Climatology Project (ISCCP) tests. The all tests consolidation (ATC) was the most effective, achieving 72.98 % accuracy during daytime and 59.50 % at night, making it relatively accurate for creating a cirrus mask.

This study presents a data processing scheme for the detection and quantification of methane emissions using the MethaneAIR airborne spectrometer. We show that the proposed methods enable the detection of smaller plumes (compared with those detectable using other existing methods) and improve the potential of MethaneAIR to survey methane point sources across large regions.

The study highlights how aerosol measurements from aircraft can be used in synergy with ground-based observations to validate the European Space Agency's Aeolus satellite aerosol product above the tropical Atlantic. For the first time, collocated sections of the troposphere up to 626 km long are crossed. Combining measurements from satellite, aircraft, and ground-based instruments allows characterization of the optical properties of the observed dust particles emitted from the Sahara.

One important property of a cloud is the concentration of cloud drops. This property is relevant to how the cloud interacts with sunlight and how easily the cloud forms precipitation. Measuring this property from satellite observations is one important source of data, but it does require making some assumptions. This study evaluates the accuracy of satellite-derived drop concentration by a comparison with aircraft measurements.

The topic is finding methods to extend climate data records from single-instrument satellite observations, in this case the Advanced Very High Resolution Radiometer (AVHRR). Several modern instruments include AVHRR-heritage channels, but some corrections are necessary to account for some differences. We have simulated AVHRR data from the Visible Infrared Imaging Radiometer Suite (VIIIRS) sensor on National Oceanic and Atmospheric Administration (NOAA) polar satellites. We find that methods based on machine learning are capable of performing these corrections.

Nitryl chloride (ClNO₂) is a reservoir of chlorine atoms and nitrogen oxides, both of which play important roles in atmospheric chemistry. However, all ambient ClNO₂ observations so far have been made by a single technique, mass spectrometry, which needs complex calibrations. Here, we present a laser-based method that detects ClNO₂ (TD-TILDAS – thermal dissociation–tunable infrared laser direct absorption spectrometry) without the need for complicated calibrations. The results show excellent agreement between these two methods from both laboratory and ambient samples.

This study analyzed NaCl and CaCl₂ powder-type hygroscopic materials for cloud seeding, using the Korea Cloud Physics Experimental Chamber (K-CPEC) in South Korea. The aerosol chamber enabled particle analysis in an extremely dry environment, while the cloud chamber, with precise pressure and temperature control, facilitated droplet growth through quasi-adiabatic expansion. Our study provides valuable insights for the development of new seeding materials and advanced cloud seeding experiments.

The Korean Geostationary Environmental Monitoring Spectrometer (GEMS) monitors trace gases over Asia, e.g., NO₂. GEMS provides hourly data, improving the time resolution compared to the daily overpasses by other satellites. For the prediction of hourly surface NO₂ over South Korea from GEMS observations and meteorological data, this study shows that machine learning models benefit from this higher time resolution. This is achieved by using observations from previous hours as additional inputs.

Simulations of storm characteristics and associated radar signatures were improved, especially under the freezing level, using an advanced cloud scheme. Discrepancies between observations and forecasts at and above the melting layer highlighted issues in both the radar forward operator and the microphysics. To overcome some of these issues, different parameterizations of the operator were suggested. This work aligns with the future integration of polarimetric data into assimilation systems.

Clumped-isotope signals obtained through gas source mass spectrometry are typically small and require pressure baseline corrections. While such corrections have been developed for square-shaped peaks, we present an approach for correcting peaks with complex shapes. Our method is demonstrated using oxygen clumped isotopes measured in pure oxygen, where the peak tops are linearly increasing and/or negatively curved.