A first validation for the European satellite Aeolus is presented. Aeolus is the first satellite that can actively measure horizontal wind profiles from space.
Radiosonde launches on board the German research vessel Polarstern have been utilized to validate Aeolus observations over the Atlantic Ocean, a region where almost no other reference measurements are available. It is shown that Aeolus is able to measure accurately atmospheric winds and thus may significantly improve weather forecasts.
The Balloon Lidar Experiment was the first lidar dedicated to measurements in the mesosphere flown on a balloon. During a 6 d flight, it made high-resolution observations of polar mesospheric clouds which form at high latitudes during summer at ~ 83 km altitude and are the highest clouds in Earth's atmosphere. We describe the instrument and assess its performance. We could detect fainter clouds with higher resolution than what is possible with ground-based instruments.
This paper is about a feasibility study of applying a machine learning technique to derive aerosol properties from a single MAX-DOAS sky scan, which detects sky-scattered UV–visible photons at multiple elevation angles. Evaluation of retrieved aerosol properties shows good performance of the ML algorithm, suggesting several advantages of a ML-based inversion algorithm such as fast data inversion, simple implementation and the ability to extract information not available using other algorithms.
We describe a lightweight (2 kg) mid-IR laser spectrometer for airborne, in situ atmospheric methane (CH4) measurements. The instrument, based on an open-path circular multipass cell, provides fast response (1 Hz) and sub-parts-per-billion precision. It can easily be mounted on a drone, giving access to highly resolved 4D (spatial and temporal) data. The performance was assessed during field deployments involving artificial CH4 releases and vertical concentration gradients in the PBL.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
The paper establishes the fiducial reference of the GAW aerosol network providing the fully characterized value chain to the provision of four climate-relevant aerosol properties from ground-based sites. Data from almost 90 stations worldwide are reported for a reference year, 2017, providing a unique and very robust view of the variability of these variables worldwide. Current gaps in the GAW network are analysed and requirements for the Global Climate Monitoring System are proposed.
This paper overviews the progress in sky radiometer technology and the development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from sky radiometer observations of aerosol, cloud, water vapor, and ozone. The paper also discusses current issues of SKYNET to provide better information for the community.
We use the NASA GEOS-GMI chemistry climate model to construct a climatology of stratospheric ozone diurnal variations as a function of latitude, pressure and month, which can be used in a variety of data analysis tasks involving ozone observations made at different times of the day. The climatology compares well with previous modeling simulations and available observations, and to the authors' knowledge is the first characterization of the diurnal cycle available for general ozone data analyses.
The latest commercial laser spectrometers have the potential to revolutionize N2O isotope analysis. However, to do so, they must be able to produce trustworthy data. Here, we test the performance of widely used laser spectrometers for ambient air applications and identify instrument-specific dependencies on gas matrix and trace gas concentrations. We then provide a calibration workflow to facilitate the operation of these instruments in order to generate reproducible and accurate data.
We report the first demonstration of a humidified cavity-enhanced albedometer (H-CEA) that combines a broadband cavity-enhanced aerosol albedometer with a humidigraph system for simultaneous and accurate measurements of multiple optical hygroscopic parameters (f(RH)ext,scat,abs,ω) at λ = 532 nm. The instrument is suitable for operating under high RH-conditions and has sampling advantages over independent measurements of different parameters with different instruments.
Microwave dual-polarization observations consistently show that larger atmospheric ice particles tend to have a preferred orientation. We provide a publicly available database of microwave and submillimeter wave scattering properties of oriented ice particles based on discrete dipole approximation scattering calculations. Detailed radiative transfer simulations, recreating observed polarization patterns, are additionally presented in this study.
A machine-learning (ML)-based approach that can be used for cloud mask and phase detection is developed. An all-day model that uses infrared (IR) observations and a daytime model that uses shortwave and IR observations from a passive instrument are trained separately for different surface types. The training datasets are selected by using reference pixel types from collocated space lidar. The ML approach is validated carefully and the overall performance is better than traditional methods.
This work reports on the first airborne validation campaign of ESA’s Earth Explorer mission Aeolus, conducted in central Europe during the commissioning phase in November 2018. After presenting the methodology used to compare the data sets from the satellite, the airborne wind lidar and the ECWMF model, the wind results from the underflights performed are analyzed and discussed, providing a first assessment of the accuracy and precision of the preliminary Aeolus wind data.
We present the first validation of the only operational automatic pollen monitoring system based on holography, the Swisens Poleno. The device produces real-time images of coarse aerosols, and by applying a machine learning algorithm we identify a range of pollen taxa with accuracy >90 %. The device was further validated in controlled chamber experiments to verify the counting ability and the performance of additional fluorescence measurements, which can further be used in pollen identification.
Collecting measurements of hail size and shape is difficult due to the infrequent and dangerous nature of hailstorms. To improve upon this, a new technique called HailPixel is introduced for measuring hail using aerial imagery collected by a drone. A combination of machine learning and computer vision methods is used to extract the shape of thousands of hailstones from the aerial imagery. The improved statistics from the much larger HailPixel dataset show significant benefits.
This paper presents a new H2O/HDO data set from TROPOMI short-wave infrared measurements. It is validated against recent ground-based FTIR measurements from the TCCON network. A bias in TCCON HDO (which is not verified) is corrected by fitting a correction factor for the HDO column to match MUSICA δD for common observations. The use of the new TROPOMI data set is demonstrated using a case study of a blocking anticyclone over Europe in July 2018.
We have built a triple-capillary cryostat designed to reduce potential instrumental effects that may have influenced earlier measurements and to improve our understanding of the processes responsible for ice crystal shapes and sizes. In this cryostat, a crystal forms on one of three well-separated and ultrafine capillaries. In this paper we describe the new instrument and present several observations made using the instrument to illustrate the instrument's advantages.
Steven D. Miller, Louie D. Grasso, Qijing Bian, Sonia M. Kreidenweis, Jack F. Dostalek, Jeremy E. Solbrig, Jennifer Bukowski, Susan C. van den Heever, Yi Wang, Xiaoguang Xu, Jun Wang, Annette L. Walker, Ting-Chi Wu, Milija Zupanski, Christine Chiu, and Jeffrey S. Reid
Satellite–based detection of lofted mineral via infrared–window channels, well established in the literature, faces significant challenges in the presence of atmospheric moisture. Here, we consider a case featuring the juxtaposition of two dust plumes embedded within dry and moist air masses. The case is considered from the vantage points of numerical modeling, multi–sensor observations, and radiative transfer theory arriving at a new method for mitigating the water vapor masking effect.
The Geostationary Environment Monitoring Spectrometer (GEMS) will be launched by South Korea in 2019, and it will measure radiances ranging from 300 to 500 nm every hour with a fine spatial resolution of 7 km x 8 km over Seoul in South Korea to monitor column concentrations of air pollutants including O3, NO2, SO2, and HCHO, as well as aerosol optical properties. This paper describes a GEMS formaldehyde retrieval algorithm including a number of sensitivity tests for algorithm evaluation.
This research project assesses biases in traditional, filter-based, aerosol absorption measurements by comparison to state-of-the-art, non-filter-based, or in situ, measurements. We assess biases in traditional absorption measurements for three main aerosol types, including dust and fresh and aged biomass burning aerosols. The main results of this study are that the traditional and state-of-the-art absorption measurements are well correlated and that biases in the former are up to 45 %.
Detecting aerosol layer height from space is challenging. The traditional method relies on active sensors such as lidar that provide the detailed vertical structure of the aerosol profile but is costly with limited spatial coverage (more than 1 year is needed for global coverage). Here we developed a passive remote sensing technique that uses backscattered sunlight to retrieve smoke aerosol layer height over both water and vegetated surfaces from a sensor 1.5 million kilometers from the Earth.
Volatile organic compound (VOC) emissions influence air quality and particulate distributions, particularly in major source regions such as the Amazon. A sampler for collecting VOCs from an unmanned aerial vehicle (UAV) is described. Field tests of its performance and an initial example data set collected in the Amazon are also presented. The low cost, ease of use, and maneuverability of UAVs give this method the potential to significantly advance knowledge of the spatial distribution of VOCs.
Charles A. Brock, Christina Williamson, Agnieszka Kupc, Karl D. Froyd, Frank Erdesz, Nicholas Wagner, Matthews Richardson, Joshua P. Schwarz, Ru-Shan Gao, Joseph M. Katich, Pedro Campuzano-Jost, Benjamin A. Nault, Jason C. Schroder, Jose L. Jimenez, Bernadett Weinzierl, Maximilian Dollner, ThaoPaul Bui, and Daniel M. Murphy
From 2016 to 2018 a NASA aircraft profiled the atmosphere from 180 m to ~12 km from the Arctic to the Antarctic over both the Pacific and Atlantic oceans. This program, ATom, sought to sample atmospheric chemical composition to compare with global climate models. We describe the how measurements of particulate matter were made during ATom, and show that the instrument performance was excellent. Data from this project can be used with confidence to evaluate models and compare with satellites.
The abundance of freezing nuclei in water samples is routinely determined by experiments involving the cooling of sample drops and observing the temperatures at which the drops freeze. This is used for characterizing the nucleating abilities of materials in laboratory preparations or to determine the numbers of nucleating particles in rain, snow, river water or other natural waters. The evaluation of drop-freezing experiments in terms of differential nucleus spectra is advocated in the paper.
We developed a shape model of coated soot particles and created a dataset of their optical properties. To simulate the detailed shape properties of mixtures of soot aggregates and adhered water-soluble substances, we propose a simple model of surface tension derived from the artificial surface potential. The results of some single-scattering properties including lidar backscattering were discussed.
Tobias Borsdorff, Joost aan de Brugh, Haili Hu, Otto Hasekamp, Ralf Sussmann, Markus Rettinger, Frank Hase, Jochen Gross, Matthias Schneider, Omaira Garcia, Wolfgang Stremme, Michel Grutter, Dietrich G. Feist, Sabrina G. Arnold, Martine De Mazière, Mahesh Kumar Sha, David F. Pollard, Matthäus Kiel, Coleen Roehl, Paul O. Wennberg, Geoffrey C. Toon, and Jochen Landgraf
On 13 October 2017, the S5-P satellite was launched with TROPOMI as its only payload. One of the primary products is atmospheric CO observed with daily global coverage and spatial resolution of 7 × 7 km2. The new dataset allows the sensing of CO enhancements above cities and industrial areas and can track pollution transport from biomass burning regions. Through validation with ground-based TCCON measurements we show that the CO data product is already well within the mission requirement.
Ice nucleation commonly studied using droplet freezing measurements suffers from artifacts caused by water impurities or substrate effects. We evaluate a series of substrates and water sources to find methods that reduce the background freezing temperature limit. The best performance was obtained from our new microfluidic device and hydrophobic glass surfaces, using filtered HPLC bottled water. We conclude with recommendations for best practices in droplet freezing experiments and data analysis.
Arno Keppens, Jean-Christopher Lambert, José Granville, Daan Hubert, Tijl Verhoelst, Steven Compernolle, Barry Latter, Brian Kerridge, Richard Siddans, Anne Boynard, Juliette Hadji-Lazaro, Cathy Clerbaux, Catherine Wespes, Daniel R. Hurtmans, Pierre-François Coheur, Jacob C. A. van Peet, Ronald J van der A, Katerina Garane, Maria Elissavet Koukouli, Dimitris S. Balis, Andy Delcloo, Rigel Kivi, Réné Stübi, Sophie Godin-Beekmann, Michel Van Roozendael, and Claus Zehner
This work, performed at the Royal Belgian Institute for Space Aeronomy and the second in a series of four Ozone_cci papers, reports for the first time on data content studies, information content studies, and comparisons with co-located ground-based reference observations for all 13 nadir ozone profile data products that are part of the Climate Research Data Package (CRDP) on atmospheric ozone of the European Space Agency's Climate Change Initiative.
This work reports airborne wind lidar observations performed in a recent field campaign. The deployed lidar system serves as a demonstrator for the satellite instrument ALADIN on board Aeolus, which is scheduled for launch in 2018 and will become the first wind lidar in space. After presenting the measurement principle, operation procedures and wind retrieval algorithm, the obtained wind results are validated and discussed, providing valuable information in preparation for the satellite mission.
Remotely piloted aircraft systems (RPAS), commonly called UAVs, are used in atmospheric science for in situ measurements. The presented work shows wind measurements from a five-hole probe on an RPAS. Comparisons with other instruments (sonic anemometer and cloud radar) show good agreement, validating the RPAS measurements. In situ vertical wind measurements at cloud base are highlighted because they are a major parameter needed for simulating aerosol–cloud interactions, though rarely collected.
Wind information throughout the middle-atmosphere is crucial for the understanding of atmospheric dynamics but became available only recently, thanks to developments in remote sensing and modelling approaches. We present the first thorough assessment of the quality of the wind estimates by comparing co-located observations from lidar and microwave radiometry and opposing them to the major atmospheric models. Moreover we evaluated a new approach for measuring mesopause region wind by radiometry.
Tropical atmospheric variability is often described using proxy indices of the Quasi-Biennial Oscillation and the El Niño–Southern Oscillation. We introduce new proxies derived from GNSS radio occultation (RO) satellite measurements. Using the high vertical resolution of the RO temperature fields we obtain altitude-resolved indices which can improve the description of atmospheric variability patterns and can be used in climate studies where a detailed knowledge of these patterns is required.
Low-cost sensors promise neighborhood-scale air quality monitoring but have been plagued by inconsistent performance for precision, accuracy, and drift. CMU and SenSevere collaborated to develop the RAMP, which uses electrochemical sensors. We present a machine learning algorithm that overcomes previous performance issues and meets US EPA's data quality recommendations for personal exposure for NO2 and tougher "supplemental monitoring" standards for CO & ozone across 19 RAMPs for several months.
Microwave radiometers have the capability of observing temperature and humidity profiles with a few minute time resolution. This study investigates the potential benefit of this instrument to improve weather forecasts thanks to a better initialization of the model. Our results show that a significant improvement can be expected in the model initialization in the first 3 km with potential impacts on weather forecasts.
Alba Lorente, K. Folkert Boersma, Huan Yu, Steffen Dörner, Andreas Hilboll, Andreas Richter, Mengyao Liu, Lok N. Lamsal, Michael Barkley, Isabelle De Smedt, Michel Van Roozendael, Yang Wang, Thomas Wagner, Steffen Beirle, Jin-Tai Lin, Nickolay Krotkov, Piet Stammes, Ping Wang, Henk J. Eskes, and Maarten Krol
Choices and assumptions made to represent the state of the atmosphere introduce an uncertainty of 42 % in the air mass factor calculation in trace gas satellite retrievals in polluted regions. The AMF strongly depends on the choice of a priori trace gas profile, surface albedo data set and the correction method to account for clouds and aerosols. We call for well-designed validation exercises focusing on situations when AMF structural uncertainty has the highest impact on satellite retrievals.
Gaétane Ronsmans, Bavo Langerock, Catherine Wespes, James W. Hannigan, Frank Hase, Tobias Kerzenmacher, Emmanuel Mahieu, Matthias Schneider, Dan Smale, Daniel Hurtmans, Martine De Mazière, Cathy Clerbaux, and Pierre-François Coheur
HNO3 concentrations are obtained from the IASI instrument and the data set is characterized for the first time in terms of vertical profiles, averaging kernels and error profiles. A validation is also conducted through a comparison with ground-based FTIR measurements, with good results. The data set is then used to analyse HNO3 spatial and temporal variability for the year 2011. The latitudinal gradient and the large seasonal variability in polar regions are well represented with IASI data.
Surface-based two-filter radon detectors monitor the ambient concentration of atmospheric radon-222, a natural tracer of mixing and transport. They are sensitive, but respond slowly to ambient changes in radon concentration. In this paper, a deconvolution method is used to successfully correct observations for the instrument response. Case studies demonstrate that it is beneficial, sometimes necessary, to account for the detector response, especially when studying near-surface mixing.
Glynn C. Hulley, Riley M. Duren, Francesca M. Hopkins, Simon J. Hook, Nick Vance, Pierre Guillevic, William R. Johnson, Bjorn T. Eng, Jonathan M. Mihaly, Veljko M. Jovanovic, Seth L. Chazanoff, Zak K. Staniszewski, Le Kuai, John Worden, Christian Frankenberg, Gerardo Rivera, Andrew D. Aubrey, Charles E. Miller, Nabin K. Malakar, Juan M. Sánchez Tomás, and Kendall T. Holmes
Using data from a new airborne Hyperspectral Thermal Emission Spectrometer (HyTES) instrument, we present a technique for the detection and wide-area mapping of emission plumes of methane and other atmospheric trace gas species over challenging and diverse environmental conditions with high spatial resolution, that permits direct attribution to sources in complex environments.
This paper is presenting a feasibility study focused on methods of estimating the turbulence intensity based on a class of navigational messages routinely broadcast by the commercial aircraft (known as ADS-B and Mode-S). Using this kind of information could have potentially significant impact on aviation safety. Three methods have been investigated.
We validate 2-D ionospheric tomography reconstructions against EISCAT incoherent scatter radar measurements. The method is based on Bayesian statistical inversion. We employ ionosonde measurements for the choice of the prior distribution parameters and use a sparse matrix approximation for the computations. This results in a computationally efficient tomography algorithm with clear probabilistic interpretation. We find that ionosonde measurements improve the reconstruction significantly.
We present the development of a new airborne mass spectrometer AIMS-H2O for the fast and accurate measurement of water vapor in the upper troposphere and lower stratosphere. The high accuracy needed for e.g. quantification of atmospheric water vapor transport processes or cloud formation is achieved by an in-flight calibration of the instrument. AIMS-H2O is deployed on the DLR research aircraft HALO and Falcon where it covers a range of water vapor mixing ratios from 1 to 500 ppmv.
Seven gravity-wave-resolving instruments (satellites, radiosondes and a meteor radar) are used to compare gravity-wave energy and vertical wavelength over the Southern Andes hotspot. Several conclusions are drawn, including that limb sounders and the radar show strong positive correlations. Radiosondes and AIRS weakly anticorrelate with other instruments and we see strong correlations with local stratospheric winds. Short-timescale variability is larger than the seasonal cycle.
We describe an innovative instrument based on cavity ring-down spectroscopy that analyzes the stable isotopes of methane in the ambient atmosphere. This instrument was used to study atmospheric emissions from oil and gas extraction activities in the Uintah Basin in Utah. These measurements suggest that 85 ± 7% of the total emissions in the basin are from natural gas production. The easy field deployment of this instrument can enable similar regional attribution studies across the world.
This paper describes the feasibility of using a differential absorption radar technique for the remote sensing of water vapor within clouds near the Earth surface from a spaceborne platform. The proposed methodology is shown to be theoretically achievable and complimentary to existing water vapor remote sensing methods.
The CCA algorithm is applicable to any modern passive microwave radiometer on board polar orbiting satellites; it has been developed using a data set of co-located SSMIS and TRMM-PR measurements and AMSU-MHS and TRMM-PR measurements. The algorithm shows a small rate of false alarms and superior detection capability and can efficiently detect (POD between 0.55 and 0.71) minimum rain rate varying from 0.14 mm/h (AMSU over ocean) to 0.41 (SSMIS over coast).
G. Pappalardo, A. Amodeo, A. Apituley, A. Comeron, V. Freudenthaler, H. Linné, A. Ansmann, J. Bösenberg, G. D'Amico, I. Mattis, L. Mona, U. Wandinger, V. Amiridis, L. Alados-Arboledas, D. Nicolae, and M. Wiegner
B. Hassler, I. Petropavlovskikh, J. Staehelin, T. August, P. K. Bhartia, C. Clerbaux, D. Degenstein, M. De Mazière, B. M. Dinelli, A. Dudhia, G. Dufour, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, J. Granville, N. R. P. Harris, K. Hoppel, D. Hubert, Y. Kasai, M. J. Kurylo, E. Kyrölä, J.-C. Lambert, P. F. Levelt, C. T. McElroy, R. D. McPeters, R. Munro, H. Nakajima, A. Parrish, P. Raspollini, E. E. Remsberg, K. H. Rosenlof, A. Rozanov, T. Sano, Y. Sasano, M. Shiotani, H. G. J. Smit, G. Stiller, J. Tamminen, D. W. Tarasick, J. Urban, R. J. van der A, J. P. Veefkind, C. Vigouroux, T. von Clarmann, C. von Savigny, K. A. Walker, M. Weber, J. Wild, and J. M. Zawodny