Comparison of different droplet measurement techniques in the Braunschweig Icing Wind Tunnel

The generation, transport and characterization of supercooled droplets in multiphase wind tunnel test facilities is of great importance for conducting icing experiments and to better understand cloud microphysical processes such as coalescence, ice nucleation, accretion and riming. To this end, a spray system has been developed, tested and calibrated in the Braunschweig Icing Wind Tunnel. Liquid droplets in the size range of 1 to 150 µm produced by pneumatic atomizers were accelerated to velocities between 10 and 40 m s−1 and supercooled to temperatures between 0 and −20 ∘C. Thereby, liquid water contents between 0.07 and 2.5 g m−3 were obtained in the test section. The wind tunnel conditions were stable and reproducible within 3 % standard variation for median volumetric diameter (MVD) and 7 % standard deviation for liquid water content (LWC). Different instruments were integrated in the icing wind tunnel measuring the particle size distribution (PSD), MVD and LWC. Phase Doppler interferometry (PDI), laser spectroscopy with a fast cloud droplet probe (FCDP) and shadowgraphy were systematically compared for present wind tunnel conditions. MVDs measured with the three instruments agreed within 15 % in the range between 8 and 35 µm and showed high coefficients of determination (R2) of 0.985 for FCDP and 0.799 for shadowgraphy with respect to PDI data. Between 35 and 56 µm MVD, the shadowgraphy data exhibit a low bias with respect to PDI. The instruments' trends and biases for selected droplet conditions are discussed. LWCs determined from mass flow calculations in the range of 0.07–1.5 g m−3 are compared to measurements of the bulk phase rotating cylinder technique (RCT) and the above-mentioned single-particle instruments. For RCT, agreement with the mass flow calculations of approximately 20 % in LWC was achieved. For PDI 84 % of measurement points with LWC<0.5 g m−3 agree with mass flow calculations within a range of ±0.1 g m−3. Using the different techniques, a comprehensive wind tunnel calibration for supercooled droplets was achieved, which is a prerequisite for providing well-characterized liquid cloud conditions for icing tests for aerospace, wind turbines and power networks

Experimental characterization of the COndensation PArticle counting System for high altitude aircraft-borne application

A characterization of the ultra-fine aerosol particle counter COPAS (COndensation PArticle counting System) for operation on board the Russian high altitude research aircraft M-55 Geophysika is presented. The COPAS instrument consists of an aerosol inlet and two dual-channel continuous flow Condensation Particle Counters (CPCs) operated with the chlorofluorocarbon FC-43. It operates at pressures between 400 and 50 hPa for aerosol detection in the particle diameter (dp) range from 6 nm up to 1 micro m. The aerosol inlet, designed for the M-55, is characterized with respect to aspiration, transmission, and transport losses. The experimental characterization of counting efficiencies of three CPCs yields dp50 (50% detection particle diameter) of 6 nm, 11 nm, and 15 nm at temperature differences (DeltaT) between saturator and condenser of 17°C, 30°C, and 33°C, respectively. Non-volatile particles are quantified with a fourth CPC, with dp50=11 nm. It includes an aerosol heating line (250°C) to evaporate H2SO4-H2O particles of 11 nm<dp<200 nm at pressures between 70 and 300 hPa. An instrumental in-flight inter-comparison of the different COPAS CPCs yields correlation coefficients of 0.996 and 0.985. The particle emission index for the M-55 in the range of 1.4–8.4×10 16 kg -1 fuel burned has been estimated based on measurements of the Geophysika's own exhaust

Simulation of denitrification and ozone loss for the Arctic winter 2002/2003

We present simulations with the Chemical Lagrangian Model of the Stratosphere (CLaMS) for the Arctic winter 2002/2003. We integrated a Lagrangian denitrification scheme into the three-dimensional version of CLaMS that calculates the growth and sedimentation of nitric acid trihydrate (NAT) particles along individual particle trajectories. From those, we derive the HNO3 downward flux resulting from different particle nucleation assumptions. The simulation results show a clear vertical redistribution of total inorganic nitrogen (NOy), with a maximum vortex average permanent NOy removal of over 5 ppb in late December between 500 and 550 K and a corresponding increase of NOy of over 2 ppb below about 450 K. The simulated vertical redistribution of NOy is compared with balloon observations by MkIV and in-situ observations from the high altitude aircraft Geophysica. Assuming a globally uniform NAT particle nucleation rate of 3.4·10&#8722;6 cm&#8722;3 h&#8722;1 in the model, the observed denitrification is well reproduced. In the investigated winter 2002/2003, the denitrification has only moderate impact (<=10%) on the simulated vortex average ozone loss of about 1.1 ppm near the 460 K level. At higher altitudes, above 600 K potential temperature, the simulations show significant ozone depletion through NOx-catalytic cycles due to the unusual early exposure of vortex air to sunlight

Regional and Seasonal Dependence of the Potential Contrail Cover and the Potential Contrail Cirrus Cover over Europe

Ambient weather conditions strongly impact contrail formation and persistence. The implementation of contrail avoidance and mitigation strategies, therefore, requires regional and altitude-dependent information on the frequency of contrail occurrence. To this end, we have developed a method to quantify the potential contrail cover based on 10 years of high-resolution reanalysis of climatology and weather data from the European Center for Medium-Range Weather Forecast (ECMWF). We use the Schmidt-Appleman threshold temperature for contrail formation and additionally select thresholds for the relative humidity to evaluate the occurrence of persistent contrails and assess their regional and seasonal variation. We find a potential contrail cirrus cover of 10% to 20% above Europe at higher altitudes of 200 and 250 hPa in the 10-year climatology and a weak seasonal variation. At lower altitudes, near 300 hPa, a steep onset and a high potential contrail cirrus cover of 20% is found in late fall and in winter, decreasing to 2% potential contrail cirrus cover in summer. In comparison to ECMWF data, evaluations using data from the National Centers for Environmental Prediction (NCEP) show a significantly lower potential contrail cirrus cover. Our results help to investigate the seasonal and altitude dependence of contrail mitigation strategies, in particular for warming nighttime contrails that contribute strongly to the total climate impact from aviation

On the Stochasticity of Aerosol-Cloud Interactions within a Data-driven Framework

Aerosol-cloud interactions (ACI) pose the largest uncertainty for climate projections. Among many challenges of understanding ACI, the question of whether ACI is deterministic or stochastic has not been explicitly formulated and asked. Here we attempt to answer this question by predicting cloud droplet number concentration Nc from aerosol number concentration Na and ambient conditions. We use aerosol properties, vertical velocity fluctuation w', and meteorological states (temperature T and water vapor mixing ratio q_v) from the ACTIVATE field observations (2020 to 2022) as predictor variables to estimate Nc. We show that the climatological Nc can be successfully predicted using a machine learning model despite the strongly nonlinear and multi-scale nature of ACI. However, the observation-trained machine learning model fails to predict Nc in individual cases while it successfully predicts Nc of randomly selected data points that cover a broad spatiotemporal scale, suggesting the stochastic nature of ACI at fine spatiotemporal scales

Hydroprocessing of Fossil Fuel-Based Kerosene to Reduce the Climate Impact of Commercial Aviation Technology Options and Mitigation Potentials

Aviation contributes about 4 % of global anthropogenic climate forcing primarily by contrails, CO2 and NOx emissions. Renewably sourced aviation kerosene can help to reduce the climate impact from CO2 and from contrails, but so far, its production capacities are very small. Hence, the climate impact of using fossil fuel-based kerosene with a hydrogen content increased by hydroprocessing as short term mitigation measure is studied here. Increasing the hydroprocessing severity increases the relative climate benefit, which is only slightly affected by the emissions factor for hydroprocessing or the choice of the time horizon. Data limitations about fuel composition and its effect on contrails and climate cause considerable uncertainties and the fuel’s compliance with specification standards needs consideration. This study on the climate effect of hydroprocessed fossil kerosene can help to assess near-term measures to reduce the climate impact from aviation

Pole-to-Pole Connections : Similarities between Arctic and Antarctic Microbiomes and Their Vulnerability to Environmental Change

Acknowledgments JK acknowledges the Carl Zeiss foundation for PhD funding, the Marie-Curie COFUND-BEIPD PostDoc fellowship for PostDoc funding, FNRS travel funding and the logistical and financial support by UNIS. JK and FK acknowledge the Natural Environment Research Council (NERC) Antarctic Funding Initiative AFI-CGS-70 (collaborative gearing scheme) and logistic support from the British Antarctic Survey (BAS) for field work in Antarctica. JK and CZ acknowledge the Excellence Initiative at the University of Tübingen funded by the German Federal Ministry of Education and Research and the German Research Foundation (DFG). FH, AV, and PB received funding from MetaHIT (HEALTH-F4-2007-201052), Microbios (ERC-AdG-502 669830) and the European Molecular Biology Laboratory (EMBL). We thank members of the Bork group at EMBL for helpful discussions. We acknowledge the EMBL Genomics Core Facility for sequencing support and Y. P. Yuan and the EMBL Information Technology Core Facility for support with high-performance computing and EMBL for financial support. PC is supported by NERC core funding to the BAS “Biodiversity, Evolution and Adaptation” Team. MB was funded by Helge Ax:son Johnsons Stiftelse and PUT1317. DRD acknowledges the DFG funded project DI698/18-1 Dietrich and the Marie Curie International Research Staff Exchange Scheme Fellowship (PIRSES-GA-2011-295223). Operations in the Canadian High Arctic were supported by the Natural Sciences and Engineering Research Council of Canada (NSERC), ArcticNet and the Polar Continental Shelf Program (PCSP). We are also grateful to the TOTAL Foundation (Paris) and the UK NERC (WP 4.3 of Oceans 2025 core funding to FCK at the Scottish Association for Marine Science) for funding the expedition to Baffin Island and within this context Olivier Dargent and Dr. Pieter van West for sample collection, and the Spanish Ministry of Science and Technology through project LIMNOPOLAR (POL200606635 and CGL2005-06549-C02-01/ANT to AQ as well as CGL2005-06549-C02-02/ANT to AC, the last of these co-financed by European FEDER funds). We are grateful for funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland), funded by the Scottish Funding Council (HR09011) and contributing institutions. Supplementary Material The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fevo.2017.00137/full#supplementary-materialPeer reviewedPublisher PD

The Lagrangian Atmospheric Radionuclide Transport Model (ARTM) - development, description and sensitivity analysis

Atmospheric dispersion models are applied to describe and predict the dispersion of emitted plumes. Here, we describe the Lagrangian Atmospheric Radionuclide Transport Model (ARTM) 2.8.0 which was developed to simulate the atmospheric dispersion of the emissions of nuclear facilities under routine operation for regulatory purposes over annual time scales. ARTM includes a diagnostic wind field model and a particle dispersion model. It simulates size-dependent wet and dry deposition, plume rise and cloud shine of radioactive exhaust plumes in the simulation domain

How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties

This study investigates the sensitivity of two brightness temperature differences (BTDs) in the infrared (IR) window of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) to various cloud parameters in order to understand their information content, with a focus on cloud thermodynamic phase. To this end, this study presents radiative transfer calculations, providing an overview of the relative importance of all radiatively relevant cloud parameters, including thermodynamic phase, cloud-top temperature (CTT), optical thickness (τ), effective radius (Reff), and ice crystal habit. By disentangling the roles of cloud absorption and scattering, we are able to explain the relationships of the BTDs to the cloud parameters through spectral differences in the cloud optical properties. In addition, an effect due to the nonlinear transformation from radiances to brightness temperatures contributes to the specific characteristics of the BTDs and their dependence on τ and CTT. We find that the dependence of the BTDs on phase is more complex than sometimes assumed. Although both BTDs are directly sensitive to phase, this sensitivity is comparatively small in contrast to other cloud parameters. Instead, the primary link between phase and the BTDs lies in their sensitivity to CTT (or more generally the surface–cloud temperature contrast), which is associated with phase. One consequence is that distinguishing high ice clouds from low liquid clouds is straightforward, but distinguishing mid-level ice clouds from mid-level liquid clouds is challenging. These findings help to better understand and improve the working principles of phase retrieval algorithms

The New Volcanic Ash Satellite Retrieval VACOS Using MSG/SEVIRI and Artificial Neural Networks: 1. Development

Volcanic ash clouds are a threat to air traffic security and, thus, can have significant societal and financial impact. Therefore, the detection and monitoring of volcanic ash clouds to enhance the safety of air traffic is of central importance. This work presents the development of the new retrieval algorithm VACOS (Volcanic Ash Cloud properties Obtained from SEVIRI) which is based on artificial neural networks, the thermal channels of the geostationary sensor MSG/SEVIRI and auxiliary data from a numerical weather prediction model. It derives a pixel classification as well as cloud top height, effective particle radius and, indirectly, the mass column concentration of volcanic ash clouds during day and night. A large set of realistic one-dimensional radiative transfer calculations for typical atmospheric conditions with and without generic volcanic ash clouds is performed to create the training dataset. The atmospheric states are derived from ECMWF data to cover the typical diurnal, annual and interannual variability. The dependence of the surface emissivity on surface type and viewing zenith angle is considered. An extensive dataset of volcanic ash optical properties is used, derived for a wide range of microphysical properties and refractive indices of various petrological compositions, including different silica contents and glass-to-crystal ratios; this constitutes a major innovation of this retrieval. The resulting ash-free radiative transfer calculations at a specific time compare well with corresponding SEVIRI measurements, considering the individual pixel deviations as well as the overall brightness temperature distributions. Atmospheric gas profiles and sea surface emissivities are reproduced with a high agreement, whereas cloudy cases can show large deviations on a single pixel basis (with 95th percentiles of the absolute deviations > 30 K), mostly due to different cloud properties in model and reality. Land surfaces lead to large deviations for both the single pixel comparison (with median absolute deviations > 3 K) and more importantly the brightness temperature distributions, most likely due to imprecise skin temperatures. The new method enables volcanic ash-related scientific investigations as well as aviation security-related applications