Executive editors: Thomas Wagner, Hartwig Harder, Paolo Laj, Andreas Richter & Rebecca Washenfelder
eISSN: AMT 1867-8548, AMTD 1867-8610
Atmospheric Measurement Techniques (AMT) is a not-for-profit international scientific journal dedicated to the publication and discussion of advances in remote sensing, as well as in situ and laboratory measurement techniques for the constituents and properties of the Earth's atmosphere.
The main subject areas comprise the development, intercomparison, and validation of measurement instruments and techniques of data processing and information retrieval for gases, aerosols, and clouds. Papers submitted to AMT must contain atmospheric measurements, laboratory measurements relevant for atmospheric science, and/or theoretical calculations of measurements simulations with detailed error analysis including instrument simulations. The manuscript types considered for peer-reviewed publication are research articles, review articles, and commentaries.
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Copernicus Publications is delighted to announce a new agreement with the UK-based Jisc (Joint Information Systems Committee) to streamline open-access publishing for their members. Read more.
The ETH Domain institutions PSI, Empa, Eawag, WSL and Copernicus Publications have signed an agreement on the central settlement of article processing charges (APCs).
The ETH Domain institutions PSI, Empa, Eawag, WSL and Copernicus Publications have signed an agreement on the central settlement of article processing charges (APCs).
Yu Someya, Yukio Yoshida, Hirofumi Ohyama, Shohei Nomura, Akihide Kamei, Isamu Morino, Hitoshi Mukai, Tsuneo Matsunaga, Joshua L. Laughner, Voltaire A. Velazco, Benedikt Herkommer, Yao Té, Mahesh Kumar Sha, Rigel Kivi, Minqiang Zhou, Young Suk Oh, Nicholas M. Deutscher, and David W. T. Griffith
The updated retrieval algorithm for the Greenhouse gases Observing SATellite level 2 product is presented. The main changes in the algorithm from the previous one are the treatment of cirrus clouds, the degradation model of the sensor, solar irradiance, and gas absorption coefficient tables. The retrieval results showed improvements in fitting accuracy and an increase in the data amount over land. On the other hand, there are still large biases of XCO2 which should be corrected over the ocean.
The Orbiting Carbon Observatory-2 makes space-based measurements of reflected sunlight. Using a retrieval algorithm these measurements are converted to CO2 concentrations in the atmosphere. However, the converted CO2 concentrations contain errors for observations close to clouds. Using a simple machine learning approach, we developed a model to correct these remaining errors. The model is able to reduce errors over land and ocean by 20 % and 40 %, respectively.
Preprint under review for AMT(discussion: open, 0 comments)
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Weather forecasters around the world use uncrewed balloons to measure wind and temperature for their weather models. In these measurements, wind is recorded from the shift of the balloon by the moving air. However, the balloons and the measurement devices also move by themselves in still air. This creates artificial wind measurements that are normally removed from the data. We show new techniques to avoid these movements, increasing the altitude resolution of the wind measurement six times.
Preprint under review for AMT(discussion: open, 0 comments)
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The Earth Clouds and Radiation Explorer mission (EarthCARE) is an upcoming multi-instrument cloud-aerosol-radiation oriented satellite for climate and weather applications. For this satellite mission to be successful, the development and implementation of new techniques for turning the measured raw signals into useful data is required. This paper describes how atmospheric model data was used as the basis for creating realistic high-resolution simulated data sets to facilitate this process.
Preprint under review for AMT(discussion: open, 0 comments)
Short summary
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In order to constrain climate models and better understand how clouds might change in future climates, accurate satellite estimates of cloud liquid water content are important. The satellite currently best suited to this purpose, CloudSat, is not sensitive enough to detect some non-raining low clouds. In this study we show that information from two other satellite instruments, MODIS and CALIOP, can be combined to provide cloud water estimates for many of the clouds that are missed by CloudSat.
Atmospheric ozone can induce artefacts in volatile organic compound measurements. Laboratory tests were made using GC-MS and PTR-MS aircraft systems under tropospheric and stratospheric conditions of humidity and ozone, with and without sodium thiosulfate filter scrubbers. Ozone in dry air produces some carbonyls and degrades alkenes. The scrubber lifetime depends on ozone concentration, flow rate and humidity. For the troposphere with scrubber, no significant artefacts were found over 14 d.
I agree with the handling editor that this paper covers a very good study that would be a very useful for the community, especially for measurements of reactive gases.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
I agree with the handling editor Dr. Laura Bianco and the reviewer Dr. Frank Beyrich that this is a very good paper and that it is of general interest and relevance.
We present a methane flux rate retrieval methodology using the Sentinel-2 mission, validating the algorithm for different scenes and plumes. The detection limit is 1000–2000 kg h−1 for homogeneous scenes and temporally invariant surfaces and above 5000 kg h−1 for heterogeneous ones. Dominant quantification errors are wind-related or plume mask-related. For heterogeneous scenes, the surface structure underlying the methane plume can become a dominant source of uncertainty.
Accurate detection and quantification of methane emissions are urgently needed for climate change mitigation. Multiple observations and measurement approaches can contribute to this challenge. This study shows how Sentinel-2 can provide useful coverage and spatial resolution for methane plumes, despite limited spectral sensitivity for methane absorption.
The true eddy accumulation (TEA) method enables measuring atmospheric exchange with slow-response gas analyzers. TEA is formulated assuming ideal conditions with a zero mean vertical wind velocity during the averaging interval. This core assumption is rarely valid under field conditions. Here, we extend the TEA equation to accommodate nonideal conditions. The new equation allows constraining the systematic error term in the measured fluxes and the possibility to minimize or remove it.
We use numerical models to study field measurements of sea spray aerosol particles and conclude that both the atmospheric state and the methods of instrument sampling are causes for the variation in the production rate of aerosol particles: a critical metric to learn the aerosol's effect on processes like cloud physics and radiation. This work helps field observers improve their experimental design and interpretation of measurements because of turbulence in the atmosphere.
Next to tackling the fundamental problem in the representativeness of point measurements of particles and retrieving the surface flux in a turbulent atmosphere, this manuscript provides a general framework to plan sampling strategies for aerosol field campaigns and provides tools to quantify related uncertainties.
01 Mar 2023–30 Apr 2024 | AMT co-editors: Steffen Beirle, Diego Loyola, and Troy Thornberry | Co-organizers: Owen R. Cooper and Martin G. Schultz
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24 Mar 2022–31 Dec 2024 | Domenico Cimini, Claudia Acquistapace, Joelle Buxmann, Volker Lehmann, Markus Kayser, Stelios Kazadzis, Anca Nemuc, and Klara Jurcakova
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01 Dec 2021–30 Jun 2023 | Sophie Godin-Beekmann, Paul Newman, Irina Petropavlovskikh, Birgit Hassler, Karin Kreher, Corinne Vigouroux, Mark Weber, and Ja-Ho Koo
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