This paper explores new techniques based on sparse representations for estimating the spectral response functions of high-resolution spectrometers. The method is highly competitive, with commonly used parametric models yielding more accurate estimates while accounting for wavelength dependence. The resulting normalized estimation errors of the spectrometer spectral responses are less than 1 %, which will allow for better quantification of trace gas concentrations at the Earth surface.

Ice-nucleating particle (INP) observations often differ by 1 order of magnitude, when multiple instruments measure in parallel. As INP measurements are sensitive to the activation conditions, inaccuracies in the temperature measurement may induce significant deviations in the INP concentration. It was found that typical temperature uncertainties reported in intercomparison studies may explain divergences of a factor of 2 (± 0.5 °C) or 5 to 10 (± 1 °C) between two INP counters with opposite bias.

Water-stable isotopes are commonly used in hydrological and ecological research. Until now, measurements have been obtained either destructively or directly in the field. Here, we present a novel, affordable, and easy-to-use approach to measure the stable isotope signatures of soil water. Our gas bag approach demonstrates a high accuracy and extends usability by allowing water vapor samples to be collected and stored in the field without the need for an instrument or a permanent power supply.

Our objective was to enhance understanding of thermally driven convection in terms of small-scale variations in the temperature scalar field. We conducted a small-scale study of the temperature field in the Π Chamber using three different temperature differences (10 K, 15 K, and 20 K). Measurements were carried out using a miniaturized UltraFast Thermometer operating at 2 kHz, allowing undisturbed vertical temperature profiling from 8 cm above the floor to 5 cm below the ceiling.

A method was developed to extract information from airborne lidar observations about the distribution of ice and liquid water within clouds. The method specifically targets signatures of horizontal and vertical gradients in ice and water that appear in the polarization of the lidar signals. The method was tested against direct measurements of the cloud properties collected by a second aircraft.

Sulfur dioxide emitted during volcanic eruptions can be hazardous for aviation safety. A recent development aims at improving the forecasts of volcanic sulfur dioxide quantities made by the chemistry transport model developed at Météo-France by assimilated infrared and ultraviolet satellite instruments. We focus on the eruption event of the La Soufrière Saint Vincent volcano in April 2021. The combined assimilation of these observations always leads to better analyses and forecasts.

The use of active remote sensing instruments to sample the atmospheric environment requires accurate calibration that is stable over time so that measurements are reproducible. This is the case for measurements of atmospheric water vapour using Raman lidar, which are of growing interest in the context of climate risks such as extreme precipitation. This study addresses this issue. It is based on six campaigns spread over a period of 7 years between 2016 and 2022.

This study presents high-precision measurements of ∆^′17O(CO₂). Key findings include the extension of the N₂O–∆^′17O correlation to the upper troposphere and the identification of significant differences in the N₂O–∆^′17O slope in StratoClim samples. Additionally, the ∆^′17O measurements are used to estimate global stratospheric production and surface removal of ∆^′17O, providing an independent estimate of global vegetation CO₂ exchange.

The research investigates methods for detecting deep convective clouds (DCCs) using satellite infrared data, essential for understanding long-term climate trends. By validating three popular detection methods against lidar–radar data, it found moderate accuracy (below 75 %), emphasizing the importance of fine-tuning thresholds regionally. The study shows how small threshold changes significantly affect the climatology of severe storms.

We developed a sampling system that extends the transmission range of the five-stage lens to 10 µm. This innovative design reduces the beam incidence angle and narrows the width. Using polystyrene latex spheres, we validated the high transmission efficiency. Additionally, a standard dust test demonstrated consistency with the aerodynamic particle sizer. This study introduces a novel design framework that not only enhances transmission range and efficiency but also supports instrument miniaturization.

This study provides a detailed description of the radar simulator available within version 13 of the RTTOV (Radiative Transfer for the TIROS Operational Vertical Sounder) software. It is applied to the Météo-France global numerical weather prediction model, with the objective of simulating Dual-frequency Precipitation Radar reflectivity observations. Additionally, the simulation of the bright band is addressed and then successfully applied to model forecasts for the purpose of classifying NWP (numerical weather prediction) model columns between stratiform and convective categories.

Our study improves ice crystal shape classification, key for understanding weather and climate. By adding unsupervised pre-training before supervised classification, our algorithm reduces manual labeling effort while maintaining high accuracy. It outperforms fully supervised models across datasets of varying sizes and categories, showing strong generalization ability. This method improves ice crystal classification techniques, making it adaptable to different environmental datasets.

This work presents an innovative way of sampling and analyzing volcanic clouds using an unoccupied aircraft system (UAS). The UAS can reach hazardous environments to sample volcanic particles and measure in situ key parameters, such as the atmospheric concentration of volcanic aerosols and gases. Acquired data bridge the gap between the existing approaches of ground sampling and remote sensing, thereby contributing to the understanding of volcanic cloud dispersion and impact.