The authors propose a near-real-time procedure for the detection of volcanic clouds by means of Sentinel-3 satellite data and neural networks. The algorithm results in an automatic image classification where ashy pixels are distinguished from other surfaces with remarkable accuracy. The model is considerably faster if compared to other approaches which are time consuming, case specific, and not automatic. The algorithm can be significantly helpful for emergency management during eruption events.

The character of the airflow around and within wind farms has a significant impact on the energy output and longevity of the wind turbines in the farm. For both research and control purposes, accurate measurements of the wind speed are required, and these are often accomplished with remote sensing devices. This article pertains to a field experiment of a lidar mounted to a wind turbine and demonstrates three data post-processing techniques with efficacy at extracting useful airflow information.

In this paper, we describe a new approach to test the consistency of the precipitating ice cloud optical and microphysical properties in Antarctica, Dome C, retrieved from hyperspectral measurements in the far-infrared, with the reflectivity detected by a co-located micro rain radar operating at 24 GHz. The retrieved ice crystal sizes were found in accordance with the direct measurements of an optical imager, also installed at Dome C, which can collect the falling ice particles.

In this study, we first analyze the relationship between the visibility, the extinction coefficient, and atmospheric compositions. Then we propose to use the harmonic average of visibility data as the average visibility, which can better reflect changes in atmospheric extinction coefficients and aerosol concentrations. It is recommended to use the harmonic average visibility in the studies of climate change, atmospheric radiation, air pollution, environmental health, etc.

We present a method for positive matrix factorisation (PMF) analysis on a single dataset that includes measurements from both EESI-TOF and AMS in Zurich, Switzerland. For the first time, we resolved and quantified secondary organic aerosol (SOA) sources. Meanwhile, we also determined the retrieved EESI-TOF factor-dependent sensitivities. This method provides a framework for exploiting semi-quantitative, high-resolution instrumentation for quantitative source apportionment.

In this study, we show how sparse and noisy drone measurements can be combined with an ensemble of turbulence-resolving wind simulations to estimate uncertainty-aware surface energy exchange. We demonstrate the feasibility of this drone data assimilation framework in a series of synthetic and real-world experiments. This new framework can, in future, be applied to estimate energy and gas exchange in heterogeneous landscapes more representatively than conventional methods.

This study presents the new vertically pointing birdbath scan of the German C-band radar network, which provides high-resolution profiles of precipitating clouds above all DWD weather radars since the spring of 2021. Our AI-based postprocessing method for filtering and analyzing the recorded radar data offers a unique quantitative view into a wide range of precipitation events from snowfall over stratiform rain to intense frontal showers and will be used to complement DWD's operational services.

We describe a continuous-flow analysis (CFA) method to measure Δ¹⁷O by laser spectroscopy, and we show that centimeter-scale information can be measured reliably in ice cores by this method. We present seasonally resolved Δ¹⁷O data from Greenland and demonstrate that the measurement precision is not reduced by the CFA process. Our results encourage the development and use of CFA methods for Δ¹⁷O, and they identify calibration strategies as a target for method improvement.

We describe the development and operation of a chemical ionization mass spectrometer using an ammonium–water cluster (NH₄+·H₂O) as a reagent ion. NH₄+·H₂O is a highly versatile reagent ion for measurements of a wide range of oxygenated organic compounds. The major product ion is the cluster with NH₄⁺ produced via ligand-switching reactions. The instrumental sensitivities of analytes depend on the binding energy of the analyte–NH₄⁺ cluster; sensitivities can be estimated using voltage scanning.

Flight testing in icing conditions requires instruments that are able to accurately measure the liquid water content of supercooled large droplets (SLDs). This work finds that the 12 mm cone of the Nevzorov hot-wire probe has excellent collection properties for SLDs. We also derive a correction to compensate for the low collision efficiency of small droplets with the cone. The results provide a procedure to evaluate LWC measurements of the 12 mm cone during wind tunnel and airborne experiments.

The study evaluates a low-cost dryer to avoid the negative effect of hygroscopic growth and fog droplets in the particulate matter (PM) concentrations of sensors. The results show a reduction in the overestimation of the PM but also an underestimation compared to reference devices. Special care is needed when designing a dryer as high temperatures change the sampled air by evaporating the most volatile particulate species. Low-cost dryers are very promising for different sensor applications.

The strong variability in the chemistry of atmospheric particulate matter affects the amount of water aerosols absorb and their effect on climate. We present a remote sensing method to determine the amount of water in particulate matter. Its application to airborne instruments indicates that the observed aerosols have rather low water contents and low fractions of soluble particles. Future satellites will be able to yield global aerosol water uptake data.