AMT - recent papers

Bayesian denoising of satellite images using co-registered NO2 images

Wed, 17 Jun 2026 19:14:06 +0200

Bayesian denoising of satellite images using co-registered NO2 images
Erik Franciscus Maria Koene, Gerrit Kuhlmann, and Dominik Brunner
Atmos. Meas. Tech., 19, 3999–4012, https://doi.org/10.5194/amt-19-3999-2026, 2026
We developed methods to reduce noise in satellite images that track air pollution. By using clearer measurements of a related gas, our techniques improve image quality by up to 80 percent, allowing more accurate identification of pollution sources. Tested with simulated and real satellite data, this approach could enhance monitoring of emissions and support better environmental decisions.

Measuring molecular singlet oxygen (1O2*) from atmospheric photosensitizers: Intercomparison of techniques, irradiation setups, data analysis and protocol recommendations

Wed, 17 Jun 2026 19:14:06 +0200

Measuring molecular singlet oxygen (1O2*) from atmospheric photosensitizers: Intercomparison of techniques, irradiation setups, data analysis and protocol recommendations
Keighan J. Gemmell, Laura Marie Dahler Heinlein, Emma A. Petersen-Sonn, Claudia Sardena, Zhongyu Guo, Nory Mariño-Ocampo, Belinda Heyne, Christian George, Cort Anastasio, and Nadine Borduas-Dedekind
Atmos. Meas. Tech., 19, 3961–3982, https://doi.org/10.5194/amt-19-3961-2026, 2026
Molecular singlet oxygen (1O2*) is the first excited state of O2 and is produced when sunlight excites light-absorbing molecules in aerosols in the atmosphere. 1O2* can drive oxidation reactions and impact aerosol properties. This study is an inter-comparison of photoreactors, light sources and data analysis across 3 atmospheric chemistry laboratories, yielding a critical assessment of practices and recommendations for intercomparing 1O2* measurements and extrapolating to ambient particles.

Application of UAV-based methods for quantifying methane point source emissions over an Arctic geological seep

Wed, 17 Jun 2026 19:14:06 +0200

Application of UAV-based methods for quantifying methane point source emissions over an Arctic geological seep
Abdullah Bolek, Meghan N. Beattie, Jalal Norooz Oliaee, Roger MacLeod, June Skeeter, Peter Morse, Martin Heimann, and Mathias Göckede
Atmos. Meas. Tech., 19, 3983–3998, https://doi.org/10.5194/amt-19-3983-2026, 2026
Uncrewed aerial vehicles (UAVs) equipped with greenhouse gas (GHG) analyzers are crucial for monitoring hard-to-reach areas where traditional techniques are impractical. Here, we deployed UAVs with different types of GHG analyzers and applied three different emission rate quantification methods over a known geological methane seep. Our results demonstrate that UAV-based approaches can reliably quantify emissions from remote methane point sources that would otherwise be difficult to measure.

Optimizing airborne emission rate retrievals with sub-hectometre resolution numerical modelling

Tue, 16 Jun 2026 19:14:06 +0200

Optimizing airborne emission rate retrievals with sub-hectometre resolution numerical modelling
Sepehr Fathi, Mark Gordon, and Jingliang Hao
Atmos. Meas. Tech., 19, 3911–3931, https://doi.org/10.5194/amt-19-3911-2026, 2026
Aircraft are often used to measure emissions from industry and other sources by flying downwind of the source and measuring the pollutant winds and concentration. This study uses model simulation to help choose the best flight configuration and parameters for a given source type (e.g. smokestacks, mine faces, or surface emissions). The results provide uncertainty estimates based on downwind flight distances, which helps to plan aircraft-based measurements campaigns.

Persistent EarthCARE underflight studies of the ITCZ and organized convection (PERCUSION): contribution to EarthCARE validation

Tue, 16 Jun 2026 19:14:06 +0200

Persistent EarthCARE underflight studies of the ITCZ and organized convection (PERCUSION): contribution to EarthCARE validation
Silke Groß, Florian Ewald, Bjorn Stevens, Martin Wirth, Georgios Dekoutsidis, André Ehrlich, Dimitra Kouklaki, Konstantin Krüger, Sophie Rosenburg, Lea Volkmer, Jonas von Bismark, Lutz Hirsch, Anna E. Luebke, Eleni Marinou, Bernhard Mayer, Montserrat Pinol Sole, Manfred Wendisch, Julia Windmiller, Vassilis Amiridis, Rob Koopman, Takuji Kubota, and Markus Rapp
Atmos. Meas. Tech., 19, 3933–3959, https://doi.org/10.5194/amt-19-3933-2026, 2026
In May 2024 the joint European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) mission EarthCARE was launched. A similar payload as on the satellite was set up on the German research aircraft HALO, and deployed during an extensive measurement campaign to validated the satellite. We present our instrumentation, the measurements, and its potential for the validation of EarthCARE. We show first validation results and assessments of the EarthCARE data quality.

A new approach to inversion of multi-spectral data with applications to FUV remote sensing

Mon, 15 Jun 2026 19:14:06 +0200

A new approach to inversion of multi-spectral data with applications to FUV remote sensing
Matthew LeDuc, Tomoko Matsuo, and William Kleiber
Atmos. Meas. Tech., 19, 3875–3894, https://doi.org/10.5194/amt-19-3875-2026, 2026
We propose a new approach for inverse problems involving ratios of photon counts. We show that the method is computationally efficient and accurately handles the uncertainty introduced by count data. We demonstrate the method by estimating the temperature in the upper atmosphere in both calm and geomagnetically active conditions. We also present results that suggest this method can allow extension of these techniques to low signal to noise scenarios.

Retrieval of the precipitable water vapor from shipborne multi-GNSS measurements in tropical cyclone-prone regions of the Northwest Pacific during the summer season in 2021

Mon, 15 Jun 2026 19:14:06 +0200

Retrieval of the precipitable water vapor from shipborne multi-GNSS measurements in tropical cyclone-prone regions of the Northwest Pacific during the summer season in 2021
Dong-Hyo Sohn, Byung-Kyu Choi, Junseok Hong, Yosup Park, Hwimin Jang, Byung-Il Lee, and Jong-Kyun Chung
Atmos. Meas. Tech., 19, 3895–3909, https://doi.org/10.5194/amt-19-3895-2026, 2026
We presented the retrieval of atmospheric precipitable water vapor (PWV) from shipborne multi-Global Navigation Satellite System (GNSS) measurements conducted on the research vessel (R/V) ISABU during the summer in tropical cyclone-prone regions of the Northwest Pacific. Validation of the GNSS-derived PWV against radiosonde, geostationary orbit satellite (GK2A-AMI), and low Earth orbit satellite (MetOp-IASI) observations confirmed its reliability for monitoring PWV over oceanic regions.

Estimation of Doppler velocity from incoherent scatter spectra using context-aware transformers

Fri, 12 Jun 2026 19:14:06 +0200

Estimation of Doppler velocity from incoherent scatter spectra using context-aware transformers
Yanlin Li and Qihou Zhou
Atmos. Meas. Tech., 19, 3865–3874, https://doi.org/10.5194/amt-19-3865-2026, 2026
We introduce a transformer-based AI model for estimating Doppler velocity from incoherent scatter radar (ISR) spectra. Inspired by Vision Transformers, the model uses a standard transformer encoder adapted for radar data. Trained solely on simulated spectra, it performs well on real data from the Arecibo radar and significantly outperforms the traditional least-squares fitting (LSF) method. This approach is potentially applicable wherever spectral data can be parameterized.

Processing multiple GNSS RO data using FSI and ROPP: results from the ROMEX

Fri, 12 Jun 2026 19:14:06 +0200

Processing multiple GNSS RO data using FSI and ROPP: results from the ROMEX
Yong Chen, Xinjia Zhou, Xin Jing, Shu-Peng Ho, Xi Shao, and Tung-Chang Liu
Atmos. Meas. Tech., 19, 3781–3800, https://doi.org/10.5194/amt-19-3781-2026, 2026
We developed a Full Spectrum Inversion algorithm to process Global Navigation Satellite System Radio Occultation (RO) data, a key source for weather forecasting. Comparing it with standard systems, we found strong agreement mid-atmosphere but larger differences near the surface and upper levels. This clarifies processing uncertainties and supports improved use of RO data in numerical weather prediction and atmospheric research.

Aerosol optical-to-microphysical conversion factors for lidars and ceilometers from extended AERONET data analyses: POLIPHON update

Fri, 12 Jun 2026 19:14:06 +0200

Aerosol optical-to-microphysical conversion factors for lidars and ceilometers from extended AERONET data analyses: POLIPHON update
Albert Ansmann, Julian Hofer, Rodanthi-Elisavet Mamouri, Moritz Haarig, Holger Baars, and Ulla Wandinger
Atmos. Meas. Tech., 19, 3801–3830, https://doi.org/10.5194/amt-19-3801-2026, 2026
Updated lidar and ceilometer conversion factors are presented. The conversion factors allow us to calculate microphyscial properties from measurned optical properties. One of the main goals is to support 355 nm space lidar observations.

Validation of EarthCARE/ATLID aerosol profiling products with ground-based PollyNET lidars – case studies

Fri, 12 Jun 2026 19:14:06 +0200

Validation of EarthCARE/ATLID aerosol profiling products with ground-based PollyNET lidars – case studies
Holger Baars, Moritz Haarig, Leonard König, Athena A. Floutsi, Elizaveta Basharova, Julian Hofer, Henriette Gebauer, Ronny Engelmann, Dietrich Althausen, Annett Skupin, Benedikt Gast, Felix Fritzsch, Kevin Ohneiser, Cristofer Jimenez, Tom Gaudek, Martin Radenz, Håvard Buholdt, Birgit Heese, Andi Klamt, Patric Seifert, David P. Donovan, Gerd-Jan van Zadelhoff, Sabur F. Abdullaev, Shohina K. Khalifaeva, Dilovar F. Nozirov, and Ulla Wandinger
Atmos. Meas. Tech., 19, 3831–3864, https://doi.org/10.5194/amt-19-3831-2026, 2026
The satellite mission EarthCARE (Earth Cloud, Aerosol, and Radiation Explorer) was launched in May 2024 and has 4 unique instruments on board. We used ground-based PollyNET/ACTRIS (Aerosol, Clouds and Trace gases Research Infrastructure) profiling data to discuss the quality of EarthCARE’s lidar products based on case studies from different geographic locations. Our investigations revealed that the space-borne lidar instrument has remarkable profiling capabilities but currently also still some limitations, however, not preventing first scientific studies when quality checking the data intensively.

Rain gauges and X-band radar hourly comparison under complex orographic conditions in Reunion Island during the passage of the tropical cyclone Batsirai

Thu, 11 Jun 2026 19:14:06 +0200

Rain gauges and X-band radar hourly comparison under complex orographic conditions in Reunion Island during the passage of the tropical cyclone Batsirai
Ambinintsoa Volatiana Ramanamahefa, Thiruvengadam Padmanabhan, Guillaume Lesage, and Joël Van Baelen
Atmos. Meas. Tech., 19, 3741–3759, https://doi.org/10.5194/amt-19-3741-2026, 2026
This study examines quantitative precipitation estimation (QPE) using X-band radar in Reunion, a mountainous island. Rain rate (R) was derived from reflectivity (Z) and specific differential phase (kdp) using the Z(R) and R(kdp) estimators. Z was corrected using the single-polarization Hitschfeld-Bordan (HB) and the dual-polarization philinear methods. Their strengths, limitations, and pre-processing steps were detailed. R(kdp) coefficients were calculated from radar observations.

Accounting for spatiotemporally correlated errors in wind speed for remote surveys of methane emissions

Thu, 11 Jun 2026 19:14:06 +0200

Accounting for spatiotemporally correlated errors in wind speed for remote surveys of methane emissions
Bradley M. Conrad and Matthew R. Johnson
Atmos. Meas. Tech., 19, 3761–3780, https://doi.org/10.5194/amt-19-3761-2026, 2026
This paper demonstrates a method for quantifying wind speed uncertainties in remote emissions surveys that specifically accounts for how wind errors are correlated across time and space. Using independent weather station data, models are presented for oil and gas regions in Canada, the U.S., and Colombia, along with a Python tool to enable broader use. This work enables robust accounting of uncertainties in emissions inventories and provides guidance to minimize uncertainties in remote surveys.

CopterSonde-SWX: development of a UAS-based Vertical Atmospheric Profiler for severe weather

Thu, 04 Jun 2026 19:14:06 +0200

CopterSonde-SWX: development of a UAS-based Vertical Atmospheric Profiler for severe weather
Antonio R. Segales, Tyler M. Bell, Abdullah A. Tasim, Aaron Quiroz, Jeremy D. Simms, Joshua G. Gebauer, and Elizabeth N. Smith
Atmos. Meas. Tech., 19, 3667–3686, https://doi.org/10.5194/amt-19-3667-2026, 2026
Severe weather can change quickly, but routine weather measurements often miss important details near the ground. We built and tested CopterSonde-SWX, a small weather drone designed to collect vertical profiles in strong winds and measure temperature, humidity, and wind. Field tests showed it closely matched trusted instruments and handled stronger winds than earlier versions. This work supports future drone networks to improve storm monitoring, forecasting, and public safety.

Synergistic Fusion of Aerosol Optical Depth over India from multi-sensor satellite retrievals with ground-based measurements

Thu, 04 Jun 2026 19:14:06 +0200

Synergistic Fusion of Aerosol Optical Depth over India from multi-sensor satellite retrievals with ground-based measurements
Shiba Shankar Gouda, Mukunda M. Gogoi, and S. Suresh Babu
Atmos. Meas. Tech., 19, 3687–3712, https://doi.org/10.5194/amt-19-3687-2026, 2026
This study presents fused aerosol optical depth (AOD) from a combination of single-view and multi-angle space-borne sensors with ground-based observations across India using Universal Kriging (UK) and a novel hybrid Residual Kriging–Machine Learning (RK-ML) approach. Both methods improve aerosol representation compared to individual datasets. UK-based fused maps highlight the need for better ground coverage, addressed by the RK-ML approach under data-sparse conditions.

Direct-sun versus sky-scan Pandora formaldehyde retrievals: implications for satellite validation and sampling representativeness in Tropical Southeast Asia

Thu, 04 Jun 2026 19:14:06 +0200

Direct-sun versus sky-scan Pandora formaldehyde retrievals: implications for satellite validation and sampling representativeness in Tropical Southeast Asia
Santanasawry A. L. David Arul, Jackson Hian-Wui Chang, Yong Jie Wong, Maggie Chel-Gee Ooi, Juneng Liew, Fuei Pien Chee, Jedol Dayou, Justin Sentian, Putu Aryastana, and Neng-Huei Lin
Atmos. Meas. Tech., 19, 3713–3739, https://doi.org/10.5194/amt-19-3713-2026, 2026
This study examines how ground-based instruments measure air pollution and how well these measurements match satellite observations over Southeast Asia. We compared two observing methods and found that one captures more detailed short-term changes, while the other provides more stable and representative results. Satellite data improved with newer technology but still showed differences. These findings help improve how scientists interpret satellite data for air quality and climate studies.

Continuing the MLS water vapor record with OMPS LP using neural networks

Wed, 03 Jun 2026 19:14:06 +0200

Continuing the MLS water vapor record with OMPS LP using neural networks
Michael D. Himes, Natalya A. Kramarova, Krzysztof Wargan, Sean M. Davis, and Glen Jaross
Atmos. Meas. Tech., 19, 3601–3624, https://doi.org/10.5194/amt-19-3601-2026, 2026
Stratospheric water vapor (SWV) influences various atmospheric processes. While the Ozone Mapping and Profiler Suite Limb Profiler (OMPS LP) was not designed to measure SWV, we utilized near-coincident measurements by the Aura Microwave Limb Sounder (MLS) and OMPS LP to develop a machine learning method to measure SWV between 11.5–40.5 km. The LP-derived SWV closely agrees with MLS. Our results suggest OMPS LP can continue the global water vapor record following the MLS mission.

From real-time to long-term source apportionment of PM10 using high-time-resolution measurements of aerosol physical properties: methodology and example application at an urban background site (Aosta, Italy)

Wed, 03 Jun 2026 19:14:06 +0200

From real-time to long-term source apportionment of PM10 using high-time-resolution measurements of aerosol physical properties: methodology and example application at an urban background site (Aosta, Italy)
Henri Diémoz, Francesca Barnaba, Luca Ferrero, Ivan K. F. Tombolato, Caterina Mapelli, Annachiara Bellini, Claudia Desandré, Tiziana Magri, and Manuela Zublena
Atmos. Meas. Tech., 19, 3625–3665, https://doi.org/10.5194/amt-19-3625-2026, 2026
RASPBERRY is a new method to identify aerosol emission sources using physical properties (particle size and light absorption) measured at high time resolution by cost-effective optical instruments, instead of labour-intensive chemical analyses. Applied over five years in Aosta, Italy, it identified six main sources – traffic, biomass burning, two types of secondary particles, desert dust, and local resuspension. Validation against chemical apportionment and real-time applications are presented.

Arctic Weather Satellite assessment and assimilation at ECMWF

Tue, 02 Jun 2026 19:14:06 +0200

Arctic Weather Satellite assessment and assimilation at ECMWF
David I. Duncan, Niels Bormann, Marijana Crepulja, Mohamed Dahoui, Alan J. Geer, Christophe Accadia, Sabatino Di Michele, Tim J. Hewison, and Ville Kangas
Atmos. Meas. Tech., 19, 3581–3599, https://doi.org/10.5194/amt-19-3581-2026, 2026
Satellite data used in weather forecast models needs to be of a very high quality. Previously, this has been delivered by bus-sized satellites. The new Arctic Weather Satellite shifts this paradigm, delivering high quality observations from a small satellite. Here we analyse the performance and test its impact with a state-of-the-art weather forecast model. It compares well to heritage instruments and has a positive impact on forecast skill.

Extraction of spatially confined small-scale waves from high-resolution all-sky airglow images based on machine learning

Fri, 29 May 2026 19:14:06 +0200

Extraction of spatially confined small-scale waves from high-resolution all-sky airglow images based on machine learning
Sabine Wüst, Jakob Strutz, Patrick Hannawald, Jonas Steffen, Rainer Lienhart, and Michael Bittner
Atmos. Meas. Tech., 19, 3539–3556, https://doi.org/10.5194/amt-19-3539-2026, 2026
Since June 2019, an infrared camera has been scanning the nearly entire sky (diameter: 500 km) above DLR Oberpfaffenhofen (48.09° N, 11.28° E), Germany, every night providing images of the OH* airglow layer (height: 85–87 km), with a high spatial and temporal resolution (150 m, 2 min). We analysed three years of data for spatially confined small-scale wave structures with a machine learning approach. We derived seasonal variations and deduced that wave breaking is mostly observed in summer.