The multiwavelength Mie–Raman–fluorescence lidar of the University of Lille was used to characterize aerosols during the pollen season in the north of France for the period March–June 2020. The results of observations demonstrate that the presence of pollen grains in aerosol mixtures leads to an increase in the depolarization ratio and to the enhancement of the fluorescence backscattering.

The first spaceborne doppler wind lidar (DWL) Aeolus operates on sun-synchronous dawn–dusk orbit to lower the impact of solar background radiation (SBR) on wind observation accuracy. Increased SBR leads to an increment of averaged wind observation uncertainties from 0.19 to 0.27 m s^-1 comparing Aeolus and two added spaceborne DWLs operating on orbits with local ascending times of 15:00 and 12:00 LT. A quantitative design of laser pulse energy according to accuracy requirements is also proposed.

We propose a spectroscopic method for estimating several mixture-averaged molecular properties (carbon number and molecular weight) in particulate matter relevant for understanding its chemical origins. This estimation is enabled by calibration models built and tested using laboratory standards containing molecules with known structure, and can be applied to filter samples of PM_2.5 currently collected in existing air pollution monitoring networks and field campaigns.

Water vapor (WV) is an important variable in the climate system. Satellite measurements are thus crucial to characterize the spatial and temporal variability in WV and how it changed over time. In particular with respect to the observed strong Arctic warming, the role of WV still needs to be better understood. However, as shown in this paper, a detailed understanding is still hampered by large uncertainties in the various satellite WV products, showing the need for improved methods to derive WV.

We performed an intercomparison of seasonal and annual studies of retrievals of integrated precipitable water vapor (IPWV) carried out by INSAT-3DR satellite-borne infrared radiometer sounding and CAMS reanalysis data with ground-based Indian GNSS data. The magnitude and sign of the bias of INSAT-3DR and CAMS with respect to GNSS IPWV differs from station to station and season to season. A statistical evaluation of the collocated data sets was done to improve day-to-day weather forecasting.

Considering nephelometers' major problems of a nonideal Lambertian light source and angle truncation, a new correction method based on a machine learning model is proposed. Our method has the advantage of obtaining data with high accuracy while achieving self-correction, which means that researchers can get more accurate scattering coefficients without the need for additional observation data. This method provides a more precise estimation of the aerosol’s direct radiative forcing.

Multi-wavelength radar measurements provide capabilities to identify ice particle types and growth processes in clouds beyond the capabilities of single-frequency radar measurements. This study introduces Doppler velocity and polarimetric radar observables into the multi-wavelength radar reflectivity measurement to improve identification analysis. The analysis clearly discerns snowflake aggregation and riming processes and even early stages of riming.

We validated two BTS-based systems in a longer-term TOC analysis in the 2019/2020 campaign at Hohenpeißenberg and Davos. The results showed a deviation of the BTS-Solar to Brewers of < 0.1 % with a k = 2 of < 1.5 %. Koherent showed a deviation of 1.7 % with a k = 2 of 2.7 %. Resultingly, the BTS-Solar performance is comparable to Brewers in Hohenpeißenberg. Koherent shows a seasonal variation in Davos due to the sensitivity of its TOC retrieval algorithm to stratospheric temperature.

This paper presents work towards making retrievals on the liquid water content in fog and low clouds. Future retrievals will rely on a radar simulator and high-resolution forecast. In this work, real observations are used to assess the errors associated with the simulator and forecast. A selection method to reduce errors associated with the forecast is proposed. It is concluded that the distribution of errors matches the requirements for future retrievals.

Methods to estimate surface UV radiation from satellite measurements offer the only means to obtain global coverage, and the development of satellite-based UV algorithms has been ongoing since the early 1990s. One of the main challenges in this development has been how to account for the overall effect of absorption by atmospheric aerosols. One such method was suggested roughly a decade ago, and in this study we propose further improvements for this kind of approach.

We show a method for obtaining cloud optical extinction with a lidar system. We use a scheme in which a lidar signal is inverted based on the estimated value of cloud extinction at the far end of the cloud and apply a correction for multiple scattering within the cloud and a range resolution correction. By applying our technique, we show that it is possible to obtain the cloud optical extinction with an error better than 5 % up to 90 m within the cloud.

A cloud particle sensor (CPS) sonde is an observing system to obtain the signals of the phase, size, and the number of cloud particles. Based on the field experiments in the Arctic regions and numerical experiments, we proposed a method to correct the CPS sonde data and found that the CPS sonde system can appropriately observe the liquid cloud if our correction method is applied.

This work presents promising results in the characterization of specific atmospheric pollutants (oxygenated VOCs) present at very low but highly relevant concentrations. We carried out this research at EUPHORE facilities within the framework of the EUROCHAMP project. A new analytical method, with high robustness and precision, also clean in the use of solvents, low cost, and easily adaptable for use in mobile laboratories for air quality monitoring, is presented.

Relative humidity (RH) and hygroscopicity play an important role in regulating the physical, chemical, and optical properties of aerosol. In this work, we develop a new method to characterize hygroscopicity using particle levitation. We levitate two droplets with an electrodynamic balance and measure their size with light-scattering methods using one droplet as a probe of the RH. We demonstrate highly accurate and precise measurements of the RH and hygroscopic growth of a range of samples.

A radar in Svalbard usually used to study meteor trails was used to observe a thin icy layer in the upper atmosphere. New methods used the layer to measure wind speed over short periods of time and found that the layer is most reflective within 6.8 ± 3.3° of vertical. Analysis of meteor trail radar echo durations found that the layer may shorten meteor trail echoes, but more data are needed. This study shows new uses for data collected by meteor radars for other purposes.

In this study, we show how solar radiance observations can be used to validate and further constrain ice cloud microphysics retrieved from the synergy of radar–lidar measurements. Since most radar–lidar retrievals rely on a global assumption about the ice particle shape, ice water content and particle size biases are to be expected in individual cloud regimes. In this work, we identify and correct these biases by reconciling simulated and measured solar radiation reflected from these clouds.

We consider the possibility of using the CRDS Picarro G2201-i instrument, originally designed for isotopic CH₄ and CO₂, for measurements of ethane : methane in near-source conditions. The work involved laboratory tests, a controlled release experiment and mobile measurements. We show the potential of determining ethane : methane with 50 ppb ethane uncertainty. The instrument can correctly estimate the ratio in CH₄ enhancements of 1 ppm and more, as can be found at strongly emitting sites.

Gas fluxes measured by the eddy covariance (EC) technique are subject to filtering due to non-ideal instrumentation. For linear first-order systems this filtering causes also a time lag between vertical wind speed and gas signal which is additional to the gas travel time in the sampling line. The effect of this additional time lag on EC fluxes is ignored in current EC data processing routines. Here we show that this oversight biases EC fluxes and hence propose an approach to rectify this bias.

Vertical turbulent fluxes of gases measured by the eddy covariance (EC) technique are subject to high-frequency losses. There are different methods used to describe this low-pass filtering effect and to correct the measured fluxes. In this study, we analysed the systematic uncertainty related to this correction for various attenuation and signal-to-noise ratios. A new and robust transfer function method is finally proposed.

The SEVIRI instrument flown on the European geostationary Meteosat satellites acquires multi-spectral images at a relatively coarse pixel resolution of 3 × 3 km², but it also has a broadband high-resolution visible channel with 1 × 1 km² spatial resolution. In this study, the modification of an existing cloud property and solar irradiance retrieval to use this channel to improve the spatial resolution of its output products as well as the resulting benefits for applications are described.

Within the MOSAiC expedition, GNSS was used to monitor variations in atmospheric water vapor. Based on 15 months of continuously tracked data, coordinates and hourly zenith total delays (ZTDs) were determined using kinematic precise point positioning. The derived ZTD values agree within few millimeters with ERA5 and terrestrial GNSS and VLBI stations. The derived integrated water vapor corresponds to the frequently launched radiosondes (0.08 ± 0.04 kg m⁻², rms of the differences of 1.47 kg m⁻²).

A monitoring campaign was conducted in Augsburg to determine a suitable noise reduction algorithm for the MA200 Aethalometer. Results showed that centred moving average (CMA) post-processing effectively removed spurious negative concentrations without major bias and reliably highlighted effects from local sources, effectively increasing spatio-temporal resolution in mobile measurements. Evaluation of each method on peak sample reduction and background correction further supports the reliability.

This paper reports on dark current signal anomalies of the detectors used on board the ESA's Earth Explorer satellite Aeolus during the first 1.5 years in orbit. After introducing sophisticated algorithms to classify dark current anomalies according to their characteristics, the impact of the different kinds of anomalies on wind measurements is discussed. In addition, mitigation approaches for the wind retrieval are presented and potential root causes are discussed.

Field measurements of gas flare emissions often assume that combustion species are spatially and temporally correlated in the plume. By measuring black carbon (BC) and water vapour in turbulent lab-scale flare plumes, this study shows that the well-correlated species assumption is not universally valid and that field measurements may be subject to large added uncertainty. Further analysis suggests that this uncertainty is easily avoided, and initial guidance is provided on sampling protocols.

Cloud base height (CBH) is important, e.g., to forecast solar irradiance and, with it, photovoltaic production. All-sky imagers (ASIs), cameras monitoring the sky above their point of installation, can provide such forecasts and also measure CBH. We present a network of ASIs to measure CBH. The network provides numerous readings of CBH simultaneously. We combine these with a statistical procedure. Validation attests to significantly higher accuracy of the combination compared to two ASIs alone.

An experimental assessment of a polarized micro-pulse lidar (P-MPL) in comparison to reference lidars is presented regarding the retrieval of aerosol optical properties. The evaluation is focused on both the optimally determined overlap function and volume linear depolarization ratio. A P-MPL overlap must be regularly estimated to derive suitable aerosol products (backscatter, extinction, and particle depolarization ratio). This methodology can be easily applied to other P-MPL systems.

We present high-resolution regional atmospheric chemistry model simulations focused around Germany. We highlight the importance of spatial resolution of the model itself as well as the input emissions inventory and short-scale temporal variability of emissions for simulations. We propose a consistent approach for evaluating the simulated vertical distribution of NO₂ using MAX-DOAS measurements while also considering its spatial sensitivity volume and change in sensitivity within this volume.