AMT - recent papers

A machine learning method for estimating atmospheric trace gas concentration baselines

2026-08-19T15:32:05+02:00

A machine learning method for estimating atmospheric trace gas concentration baselines
Kirstin Gerrand, Elena Fillola, Alistair J. Manning, Jgor Arduini, Paul B. Krummel, Chris R. Lunder, Jens Mühle, Simon O'Doherty, Sunyoung Park, Ronald G. Prinn, Stefan Reimann, Dickon Young, and Matthew Rigby
Atmos. Meas. Tech., 19, 5387–5400, https://doi.org/10.5194/amt-19-5387-2026, 2026
To analyse long-term trends in atmospheric trace gas concentrations, it is important to identify data points minimally affected by local pollution sources or air masses carried from other latitudes or altitudes. Traditional methods for detecting these “baselines” are computationally expensive or lack a basis in physical principles. This paper introduces a machine-learning method that uses meteorological data and offers significantly lower computational costs compared to physics-based techniques.

Curve fitting algorithm for multimodal particle size distributions – a theoretical basis

2026-08-18T15:32:05+02:00

Curve fitting algorithm for multimodal particle size distributions – a theoretical basis
Christopher N. Rapp, Gerardo Carrillo-Cardenas, Tareq Hussein, Sining Niu, Yue Zhang, Fred J. Brechtel, A. Gannet Hallar, and Daniel J. Cziczo
Atmos. Meas. Tech., 19, 5373–5385, https://doi.org/10.5194/amt-19-5373-2026, 2026
Particles in the atmosphere vary in size and concentration, forming what is known as a particle size distribution (PSD). These distributions rarely consist of a single group of similar particles, known as a mode. Instead, they are often made up multiple overlapping modes. This work introduces an open-source algorithm to separate complex PSDs into their individual modes, enabling characterization of each particle population to provide insight into properties relevant to human health and climate.

Airborne eddy covariance measurements of ocean-air VOC fluxes: Distinguishing signal from noise

2026-08-17T15:32:05+02:00

Airborne eddy covariance measurements of ocean-air VOC fluxes: Distinguishing signal from noise
Xin Chen, Dylan B. Millet, Glenn M. Wolfe, Erin R. Delaria, M. Julian Deventer, Markus Müller, Arne Schiller, Kenneth Lee Thornhill, and Armin Wisthaler
Atmos. Meas. Tech., 19, 5353–5372, https://doi.org/10.5194/amt-19-5353-2026, 2026
Air-sea exchange is a major uncertainty source for many volatile organic compounds (VOCs). Aircraft-based eddy covariance can be used to quantify these fluxes over large regions but such applications have been limited. We used observations over the Atlantic to characterize VOC fluxes and elucidate the drivers of measurement error. Results show how sensor noise and turbulent variability interact to determine flux detectability, and define instrumental priorities for future use of this technique.

Exploring the feasibility of an air sensor array for real-time detection and characterization of VOCs

2026-08-13T15:32:05+02:00

Exploring the feasibility of an air sensor array for real-time detection and characterization of VOCs
Amanda Gao, Matthew B. Goss, Erik Helstrom, David H. Hagan, and Jesse H. Kroll
Atmos. Meas. Tech., 19, 5337–5352, https://doi.org/10.5194/amt-19-5337-2026, 2026
Volatile organic compounds (VOCs) are an important class of compounds in both indoor and outdoor air; they can be directly harmful to human health, and can also react to form a range of harmful secondary pollutants. But because of the sheer number of different VOCs in air, they are not readily measurable using low-cost techniques. Here we show that an array of off-the-shelf low-cost sensors can provide useful information about the amount and composition of VOCs.

Polarization calibration of spaceborne lidar using dense cirrus–scattered solar background with molecular scattering correction

2026-08-13T15:32:05+02:00

Polarization calibration of spaceborne lidar using dense cirrus–scattered solar background with molecular scattering correction
Zhaoyan Liu, Mark A. Vaughan, Pengwang Zhai, Anne Emilie Garnier, Shan Zeng, Sharon D. Rodier, Yongxiang Hu, Ali H. Omar, and Charles R. Trepte
Atmos. Meas. Tech., 19, 5325–5335, https://doi.org/10.5194/amt-19-5325-2026, 2026
Accurate polarization calibration is vital for spaceborne lidars. Optically Thick Ice Cloud (OTIC)-based calibration enables semi-continuous daytime calibration, but molecular scattering at shorter wavelengths biases the signal. We introduce a vector radiative transfer-based Molecular Scattering Correction (MSC) and validate it using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), eliminating ~ 1% daytime bias at 532 nm. MSC is essential for the Atmospheric Lidar (ATLID) at 355 nm.

To what extent are the IASI and ERA5 water vapour profiles representative of the conditions in the autumn 2022 during the WaLiNeAs field campaign

2026-08-12T15:32:05+02:00

To what extent are the IASI and ERA5 water vapour profiles representative of the conditions in the autumn 2022 during the WaLiNeAs field campaign
Patrick Chazette, Andreas Behrendt, Adolfo Comerón, Paolo Di Girolamo, Marco Di Paolantonio, Davide Dionisi, Cyrille Flamant, José Luis Gómez-Amo, Jérémy Lagarrigue, Frédéric Laly, Diego Lange, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Michaël Sicard, Donato Summa, Julien Totems, María Pilar Utrillas, Pedro C. Valdelomar, and Volker Wulfmeyer
Atmos. Meas. Tech., 19, 5223–5242, https://doi.org/10.5194/amt-19-5223-2026, 2026
Between October 2022 and January 2023, the Water Vapour Lidar Network Assimilation (WaLiNeAs) campaign was conducted on the western Mediterranean by four European countries. To improve the forecasting of heavy precipitation events, eight ground-based stations equipped with water vapour Raman lidars were strategically deployed. They offered a valuable chance to verify the consistency of the water vapour products of both the Infrared Atmospheric Sounding Interferometer (IASI) and ERA5 reanalysis.

Evaluation of DMSO as working fluid in condensation particle counters

2026-08-12T15:32:05+02:00

Evaluation of DMSO as working fluid in condensation particle counters
Sarah Kirchhoff, Patrick Weber, Oliver F. Bischof, Gerhard Steiner, Christian Kunath, Lothar Keck, Victoria M. Fruhmann, Helmut Krasa, Alexander Bergmann, Andreas Petzold, and Ulrich Bundke
Atmos. Meas. Tech., 19, 5243–5266, https://doi.org/10.5194/amt-19-5243-2026, 2026
We evaluated dimethyl sulfoxide (DMSO) as a safe, non-flammable working fluid for condensation particle counters, comparing it with butanol under varied pressures, temperatures, and aerosols. Laboratory, field, and simulation results show reliable particle activation, comparable counting efficiency, reduced fluid use, and stable long-term operation. Mixtures with water extend usability, supporting safe monitoring in remote or harsh environments.

Stratospheric aerosol measurements using a Frequency Scanning Lidar method

2026-08-12T15:32:05+02:00

Stratospheric aerosol measurements using a Frequency Scanning Lidar method
Ronald Eixmann, Thorben H. Lüke-Mense, Jan Froh, Michael Gerding, Josef Höffner, Christian Löns, Robin Wing, Christian von Savigny, and Gerd Baumgarten
Atmos. Meas. Tech., 19, 5309–5324, https://doi.org/10.5194/amt-19-5309-2026, 2026
We introduce a new lidar-based measurement technique that can observe small particles in the middle atmosphere, up to 30 km altitude, both during the day and at night. The compact instrument, with a volume of about one cubic meter, provides high-accuracy vertical profiles of aerosols and can be deployed at different locations worldwide. Comparisons with satellite data show strong agreement, highlighting its potential for longterm monitoring of stratospheric aerosols.

An absolute reference frame for nitrous oxide clumped and position-specific isotopes provided by thermal equilibration

2026-08-12T15:32:05+02:00

An absolute reference frame for nitrous oxide clumped and position-specific isotopes provided by thermal equilibration
Paul M. Magyar, Nico Kueter, Simone Brunamonti, Naizhong Zhang, Ivan Prokhorov, Noémy Chénier, Lukas Emmenegger, Béla Tuzson, and Joachim Mohn
Atmos. Meas. Tech., 19, 5267–5280, https://doi.org/10.5194/amt-19-5267-2026, 2026
Human activity drives increases in atmospheric nitrous oxide. Stable isotopes help trace the pathways involved. We developed a reliable way to calibrate measurements of rare isotopic variants of nitrous oxide so results from different labs can be compared. By heating nitrous oxide with a catalyst, the molecules reach well-defined equilibrium patterns suitable as a reference. To measure these isotopic variants quickly and precisely, we improved a laser-based measurement approach.

Impact comparison of different aerosol types on atmospheric correction of Landsat 8 over land

2026-08-12T15:32:05+02:00

Impact comparison of different aerosol types on atmospheric correction of Landsat 8 over land
Shuning Zhang, Hao Zhang, Bing Zhang, and Zhenzhen Cui
Atmos. Meas. Tech., 19, 5281–5307, https://doi.org/10.5194/amt-19-5281-2026, 2026
Landsat 8 images map the land but must be corrected for the atmosphere. The aerosol type assumed in this step affects accuracy. To improve this, we used Landsat 8 data from one hundred sites worldwide to compare three common assumptions. The best choice depends on the situation: one for general use and for aerosol amount, another for bright surfaces like deserts, and the standard one in some bands. The results give guidance on which to use when, so land surface maps can be more accurate.

Measured methane emissions from a metropolitan wastewater treatment lagoon in Victoria Australia are substantially higher than report emissions based on emission factors

2026-08-10T15:32:05+02:00

Measured methane emissions from a metropolitan wastewater treatment lagoon in Victoria Australia are substantially higher than report emissions based on emission factors
Mei Bai, Pieter de Jong, Ellen Tao, and Deli Chen
Atmos. Meas. Tech., 19, 5157–5168, https://doi.org/10.5194/amt-19-5157-2026, 2026
For the first time, real-time methane (CH4) emissions from an open aerated sewage treatment lagoon were measured during winter and summer seasons in Australia. The study found that: 1. The emissions accounted for 25 % of CH4 production at the aeration digestion facilities. 2. The measured CH4 emissions were 2 times higher than estimates based on default emission factors. We recommend that urgent action is needed to mitigate CH4 emissions at wastewater treatment plants.

Radar data smoothing using the Discrete Cosine Transform: a fast spectral domain algorithm

2026-08-10T15:32:05+02:00

Radar data smoothing using the Discrete Cosine Transform: a fast spectral domain algorithm
Jairo M. Valdivia, Will Chapman, and Katja Friedrich
Atmos. Meas. Tech., 19, 5211–5222, https://doi.org/10.5194/amt-19-5211-2026, 2026
Weather radar data often contains significant noise that obscures storm details. Traditional cleaning methods are computationally slow because they must adjust for the complex spreading geometry of radar beams. We developed a new, highly efficient algorithm that solves this by processing data as frequencies. This method reduces hours of computer processing time to seconds and effectively removes noise without distorting features.

Experimental determination of the lidar ratio for cirrus and polar stratospheric clouds at Dome C, Antarctica, using a Young inversion

2026-08-10T15:32:05+02:00

Experimental determination of the lidar ratio for cirrus and polar stratospheric clouds at Dome C, Antarctica, using a Young inversion
Francesco Cairo, Luca Di Liberto, Alessandro Bracci, and Marcel Snels
Atmos. Meas. Tech., 19, 5193–5210, https://doi.org/10.5194/amt-19-5193-2026, 2026
Using three years of laser observations above Dome C, Antarctica, we examined high clouds made of liquid droplets, nitric-acid particles, and ice crystals. We found clear differences in how these clouds scatter light, while ice-rich clouds were the most variable because they are often layered or mixed. The results provide more realistic inputs for satellite checks and climate calculations, improving estimates of how polar clouds affect sunlight, heat, and ozone loss.

Towards a remote sensing solution to quantify nitrous oxide emissions by integrating shortwave and thermal infrared bands

2026-08-10T15:32:05+02:00

Towards a remote sensing solution to quantify nitrous oxide emissions by integrating shortwave and thermal infrared bands
Ayesha Riaz, Kang Sun, Brian D. Baker, Brian Buma, Karen E. Cady-Pereira, Christopher Chan Miller, William C. Eddy III, Betsy M. Farris, Thomas U. Kampe, Eric A. Kort, Nathan P. Leisso, Robert Spurr, Emily R. Stuchiner, and Wendy H. Yang
Atmos. Meas. Tech., 19, 5169–5191, https://doi.org/10.5194/amt-19-5169-2026, 2026
N2O is a powerful greenhouse gas mainly released from agricultural soils, but its emissions are difficult to track as they vary strongly in space and time. We tested whether combining two kind of infrared measurements in one instrument could improve ability of airborne and satellite instruments to observe these emissions. We found that this combined approach improves sensitivity to near-surface emissions with low measurement error and could guide the design of future N2O dedicated missions.

The “Golden Points” and nonequilibrium correction of high-accuracy frost point hygrometers

2026-08-07T15:32:05+02:00

The “Golden Points” and nonequilibrium correction of high-accuracy frost point hygrometers
Yann Poltera, Beiping Luo, Frank G. Wienhold, and Thomas Peter
Atmos. Meas. Tech., 19, 5091–5134, https://doi.org/10.5194/amt-19-5091-2026, 2026
Chilled mirror hygrometers are the most accurate instruments for measuring water vapor in the upper troposphere and lower stratosphere. The “Golden Points” and nonequilibrium correction are a new post-processing technique for these instruments, which can correct frost point data using mirror reflectance information to achieve unprecedented accuracy of better than 4 % in the H2O mixing ratio, even under rapidly changing humidity conditions, from the ground to the middle stratosphere.

An update to the expression of atmospheric refractivity for GNSS signals

2026-08-07T15:32:05+02:00

An update to the expression of atmospheric refractivity for GNSS signals
Josep M. Aparicio
Atmos. Meas. Tech., 19, 5135–5155, https://doi.org/10.5194/amt-19-5135-2026, 2026
Refinement of previous work on atmospheric refractivity, providing an expression as a function of air density, temperature, and composition. Studies with radio occultations in weather prediction show that the formulation of refractivity is critical with large data volumes. Compared to earlier work, this study incorporates updated fundamental measurements, accounts for variability in atmospheric composition, and extends the model to include hydrometeors.

Improving multi-modal wind speed prediction of short and medium term with a bi-clustered machine learning method

2026-08-06T15:32:05+02:00

Improving multi-modal wind speed prediction of short and medium term with a bi-clustered machine learning method
Yan Zhang, Lei Li, Xiong Xiong, Xiang Yin, Xiaojun Zhang, Fuhai Cui, Rui Dang, Wei Liu, Liang Zhai, Pengzhao Wang, Peng Sun, Weixiao Lu, and Wenjie Zhang
Atmos. Meas. Tech., 19, 5071–5089, https://doi.org/10.5194/amt-19-5071-2026, 2026
We developed a Bi-clustered Recursive Bayesian Forest model that improves wind speed forecast accuracy by 48.2 % and reduces error metrics by over 60 %. The model incorporates sea-land breeze, weather stability, and atmospheric circulation indices as features, and uses bi-clustering modal classification to mitigate wind speed magnitude interactions. This machine learning-based correction technique outperforms traditional numerical models, providing more reliable wind speed forecasting.

UCB-GLOBES: an open-access mass spectral database of identified and unidentified atmospheric organic compounds

2026-08-06T15:32:05+02:00

UCB-GLOBES: an open-access mass spectral database of identified and unidentified atmospheric organic compounds
Lindsay D. Yee, Emily B. Franklin, Robin J. Weber, Jessica Zhao, Tiger Zhang, Stephanie Xu, Isaac Santillan, Fangyuan Li, Coty N. Jen, Haofei Zhang, Yutong Liang, Gabriel Isaacman Van-Wertz, Rebecca A. Wernis, John Offenberg, Michael Lewandowski, Taekyu Joo, Masayuki Takeuchi, Gamze Eris, Weiqi Xu, Nga L. Ng, Yuzhi Chen, John E. Shilling, Mary Alice Upshur, Ariana Gray Bé, Regan J. Thomson, Franz M. Geiger, and Allen H. Goldstein
Atmos. Meas. Tech., 19, 5027–5049, https://doi.org/10.5194/amt-19-5027-2026, 2026
An open-access mass spectral database of identified and unidentified compounds in atmospheric and laboratory-generated organic aerosols is released to aid in future molecular discoveries in the environmental sciences. Identification of air pollution sources and origins is improved using the ~27,000 mass spectral records in the University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES) database.

Improving the confidence in retrievals of vertical distributions of cloud condensation nuclei number concentration from ARM supported by aircraft in situ observations

2026-08-06T15:32:05+02:00

Improving the confidence in retrievals of vertical distributions of cloud condensation nuclei number concentration from ARM supported by aircraft in situ observations
Jingjing Tian, Gourihar Kulkarni, Jennifer M. Comstock, John E. Shilling, Damao Zhang, Peng Wu, and Fan Mei
Atmos. Meas. Tech., 19, 5051–5069, https://doi.org/10.5194/amt-19-5051-2026, 2026
Cloud condensation nuclei are tiny particles that attract water vapor and help form clouds. A ground-based lidar method can estimate their number at different heights, but assumes the aerosol type does not change with height. Comparisons with aircraft data show good agreement of this method when aerosols are well mixed, but larger errors when stacked layers occur. We also developed an index to flag these complex conditions and indicate when this estimation method is more reliable.

Automated analysis and quality assurance of ice-nucleating particle data: the PINE INP Analysis software PIA

2026-08-03T15:32:05+02:00

Automated analysis and quality assurance of ice-nucleating particle data: the PINE INP Analysis software PIA
Nicole Büttner, Romy Fösig, Alexander Böhmländer, Larissa Lacher, Franziska Vogel, Mark Tarn, Pia Bogert, Jens Nadolny, Benjamin Murray, and Ottmar Möhler
Atmos. Meas. Tech., 19, 5007–5026, https://doi.org/10.5194/amt-19-5007-2026, 2026
We developed a new Python software tool that standardises and automates the analysis of data from a cloud simulation chamber. It identifies ice-forming particles in the atmosphere and ensures consistent data quality through built-in checks, making results more comparable across studies. We also analysed measurement data to provide recommendations for improving instrument reliability and long-term monitoring of atmospheric ice-forming particles. This helps to better understand how clouds behave.