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This article introduces an experimental system for rapidly acquiring trace gas profiles using multi-channel spectroscopy, significantly enhancing the time resolution of spectral collection. Owing to the improved temporal resolution, the gas profile obtained by the FS MAX-DOAS can show more details than MAX-DOAS. This work can also be integrated with mobile platforms for navigational observation research, which is crucial for achieving mobile MAX-DOAS profile measurements.

Measurements made by three instruments aboard EarthCARE are used to retrieve estimates of cloud and aerosol properties. A radiative closure assessment of these retrievals is performed by the ACMB-DF processor. Radiative transfer models acting on retrieved information produce broadband radiances commensurate with measurements made by EarthCARE’s broadband radiometer. Measured and modelled radiances for small domains are compared and the likelihood of them differing by 10 W/m² defines the closure.

In satellite remote sensing, estimating cloud base height (CBH) is more challenging than estimating cloud top height because the cloud base is obscured by the cloud itself. We developed an algorithm using the specific channel (known as the oxygen A-band channel) of the SGLI instrument on JAXA’s GCOM-C satellite to estimate CBH together with other cloud properties. This algorithm can provide global distributions of CBH across various cloud types, including liquid, ice, and mixed-phase clouds.

Air pollutants such as PM10 or PM2.5 can cause adverse public health and environment effects, therefore their regular monitoring is crucial to keep the 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 a machine learning model. 

Accurate measurement of nanoparticles is crucial for understanding their impact on new particle formation and climate change. In our study, we calibrated the Particle Size Magnifier version 2.0, a novel instrument designed for nanoparticle analysis, using both lab-generated and atmospheric particles. Significant differences were observed in the calibration results, with direct calibration using atmospheric particles enhancing measurement accuracy.

Traveling Ionospheric Disturbances (TIDs) are manifestations of atmospheric waves that are significant for transfer of energy and momentum between atmospheric layers and regions. This work demonstrates that velocities and directions of TIDs can be measured by monitoring the tiny shift in frequency of AM radio signals when they reflect from a moving ionosphere, and that this method can be scaled to use large numbers of radio receivers and transmitters to monitor TIDs on a continental scale.

This study explores how the joints in a weather radar's protective cover affect its measurements. We developed a new method to correct these errors, improving the accuracy of the radar's data. Our method was tested during an intense cyclone on Reunion Island, demonstrating significant improvements in data accuracy. This research is crucial for enhancing weather predictions and understanding, particularly in challenging terrains.

The Fairbanks area experiences severe pollution episodes in winter because of enhanced emissions of pollutants trapped near the surface by strong temperature inversions. Low-cost sensors were deployed onboard a car and a tethered balloon to measure the concentrations of gaseous pollutants (CO, O₃, NOx) in Fairbanks during the winter of 2022. Data calibration with reference measurements and machine learning methods enabled to document pollution at the surface and power plant plumes aloft.

We evaluated how well we can infer air pollutant levels (ozone, carbon monoxide, and nitrogen oxides) between air quality stations throughout South Korea, finding good representation in most densely measured cities in spite of intense small-scale emission hotspots. Comparing observed air quality with gridded model output is desirable, and so we created gridded datasets over South Korea using air quality station measurements, which agreed with airborne measurements around Seoul.

Radiocarbon (¹⁴C) is an optimal tracer of methane (CH₄) emissions, as ¹⁴C measurements enable distinguishing fossil from biogenic methane. However, these measurements are particularly challenging, mainly due to technical difficulties in the sampling procedure. With this work we made the sample extraction much simpler and time efficient, providing a new technology that can be used by any research group, with the goal of expanding ¹⁴C measurements for an improved understanding of methane sources.

Currently measurement of methane from the TROPOMI satellite is biased with respect to surface reflectance. This study demonstrates a new method of correcting for this bias on a seasonal timescale to allow for differences in surface reflectance in areas of intense agriculture where growing seasons may introduce a reflectance bias. We have successfully implemented this technique in the Denver-Julesburg basin where agriculture and methane extraction infrastructure is often co-located.

Hardware and software developments have been made on a 22 GHz microwave radiometer for the measurement of middle atmosphere water vapour near Bern, Switzerland. Previous measurements dating back to 2010 have been re-calibrated and an improved optimal estimation retrieval performed on these measurements, giving a 13 year long dataset. Measurements made with new and improved instrumental hardware are used to correct previous measurements, which show better agreement than the non-corrected dataset.

The MAESTRO instrument has been monitoring ozone and NO₂ since February 2004. A new version of these data products has recently been released; however, these new products must be validated against other datasets to ensure their validity. This study presents such an assessment, using measurements from eleven satellite instruments to characterize the new MAESTRO products. In the stratosphere, good agreement is found for ozone and acceptable agreement is found for NO₂ with these other datasets.

Water vapour isotopes are important tools to better understand processes governing the atmospheric hydrological cycle. In polar regions, their measurement helps to improve the interpretation of water isotopic records in ice cores. However, in situ water vapour isotopic monitoring is an important challenge, especially in dry places of East Antarctica. We present here an alternative laser spectroscopy technique adapted for such measurements, with a limit of detection down to 10 ppm humidity.

Long-term field testing across diverse climatic environments is conducted to identify the optimized calibration conditions for NO₂, NO, CO, and O₃ electrochemical sensors. The results uncovered three factors that influence calibration performance: calibration period, concentration range, and time averaging. We developed a comprehensive framework for the best sensor calibration practices, which serves as a valuable reference for calibrating various sensor types used in air quality monitoring.

Neglecting canopy storage terms results in inaccuracies in crop energy balance closure. Our new multiport profile system simplifies the examination of CO₂ and H₂O storage terms, enhancing the accuracy of energy closure calculations. This system, when incorporating canopy storage, significantly improves energy balance assessments and complements eddy covariance methods over maize canopies. By integrating this system, we can achieve improved energy closure calculations.

Polarimetric radio occultations (PRO) use polarized radio signals from satellites to detect moisture and precipitation in Earth's atmosphere. By applying nonlinear regression and k-means cluster analysis to over two years of PRO and non-PRO data, this study shows how deviations from a refractivity model relate to vertical profiles of water vapor pressure (moisture) and that differences between components of PRO signals correlate directly with vertical profiles of water path (precipitation).

Quantifying the composition-dependent hygroscopicity of aerosol particles is essential for advancing our understanding of atmospheric processes. Existing methods do not integrate chemical composition with hygroscopicity. We developed a novel method to assess the water uptake of particles sampled on aerosol filters at relative humidity levels up to 97 % and link it with their composition. This approach allows for the separation of total water uptake into inorganic and organic components.

This study explores the effectiveness of the Horiba PX-375 monitor for analyzing the elemental composition of airborne particulate matter (PM). Understanding this composition of PM is important for identifying its sources, assessing potential health risks, and developing strategies to reduce air pollution. The PX-375 monitor proved to be a valuable tool for ongoing air quality monitoring studies and could be particularly useful as pollution levels and sources change in the future.

Accurate and comparable measurements of oxygenated organic compounds (OVOCs) are crucial to assess tropospheric ozone burdens and trends. However, monitoring of many OVOCs remains challenging because of their low atmospheric abundance and lack of stable and traceable calibration standards. This research describes the calibration standards developed for selected OVOCs at low amount of substance fractions (<100 nmol mol^-1) to transfer traceability to the international system of units to the field.

Understanding the distribution of water vapour within our atmosphere is vital for understanding the Earth’s energy balance. Observations from the upcoming FORUM satellite are theorised to be particularly sensitive to this distribution. We exploit this sensitivity to extend the RAL Infrared Microwave Sounding retrieval scheme for the FORUM satellite. This scheme is evaluated on both simulated and observed measurements and shows a good agreement to references of the atmospheric state.

This paper describes an Airborne Radio Occultation (ARO) observation system installed on reconnaissance aircraft that uses GPS signal refraction in the atmosphere to retrieve information about the temperature and moisture in the storm environment as far away as 400 km surrounding the flight track. The characteristics and quality of 1700 ARO refractivity profiles were assessed. These observations are collected to help understand atmospheric rivers and improve their forecasting.

Contrails (clouds caused by planes) cause a large part of the climate warming due to aviation. Satellites are a good tool to validate modelled impact estimates. Many contrails are either too narrow or too disperse to detect. This work shows that only around half of contrails are observable, but the most climatically important are easier to detect. It supports the use of satellites for contrail observation, but highlights the need for observability considerations for specific applications.

Understanding the cloud phase and macrophysical properties of Southern Ocean clouds is crucial to enhancing our understanding of the region. The cloud radar and in-situ probes during the SOCRATES aircraft campaign are used to develop a new method to determine cloud boundaries and dominant phase. Low clouds (<3km) are found to be the most dominant cloud type (~90%), with liquid being the most dominant phase type, followed by ice and mixed with a greater incidence of drizzle around the cloud base.

The article gives the descriptions of the Japan Aerospace Exploration Agency (JAXA) level 2 (L2) cloud mask and cloud particle type algorithms for CPR and ATLID onboard Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite. The 355nm-multiple scattering polarization lidar was used to develop ATLID algorithm. Evaluations show the agreements for CPR-only, ATLID-only and CPR-ATLID synergy algorithms to be about 80%, 85% and 80%, respectively on average for about two EarthCARE orbits.

This study quantitatively analyzes and compares weather measurements from planar (PPPAR) and cylindrical polarimetric phased array radars (CPPAR). It examines data quality, potential problems, and clarifies misunderstandings between the configurations. The findings highlight 2D PPPAR’s challenges in making accurate weather measurements when the beam steers off broadside. CPPAR shows promise in obtaining high-quality polarimetric data because of its azimuthal scan invariant beam characteristics.

Carbon dioxide (CO₂) and methane (CH₄) are the main anthropogenic greenhouse gases. The European Copernicus CO₂ monitoring satellite mission CO2M will provide measurements of their atmospheric concentrations, but the accuracy requirements are demanding and conventional retrieval methods computationally expensive. We present a new retrieval algorithm based on artificial neural networks that has the potential to meet the stringent requirements of the CO2M mission with minimal computational effort.

Biomass burning aerosols (BBA) from Central Africa, are transported above stratocumulus clouds. The absorption of solar energy by aerosols induce warming, altering the clouds dynamics. We developed an approach that combines polarimeter and lidar to quantify it. This methodology is assessed during the AEROCLO-SA campaign. To validate it, we used flux measurements acquired during aircraft loop descents. Major perspective is the generalization of this method to the global level.

Our study estimates the SEVIRI AOD profile across Europe with 3 km spatial and 15-minute temporal resolution. Using machine learning models trained on 2017–2019 SEVIRI data and validated with 2020 CALIOP data, we found that RF performs best at higher altitudes, with wind speed and direction playing a crucial role in improving accuracy. Validation with EARLINET data confirms strong agreement with XGB.