Articles | Volume 12, issue 7
https://doi.org/10.5194/amt-12-3699-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-12-3699-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Jul 2019
Research article |
| 09 Jul 2019
| 09 Jul 2019
Calibration of a water vapour Raman lidar using GRUAN-certified radiosondes and a new trajectory method
Shannon Hicks-Jalali
CORRESPONDING AUTHOR
Department of Physics and Astronomy, University of Western Ontario, London, Canada
Robert J. Sica
Department of Physics and Astronomy, University of Western Ontario, London, Canada
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Alexander Haefele
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Department of Physics and Astronomy, University of Western Ontario, London, Canada
Giovanni Martucci
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
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Atmos. Chem. Phys., 20, 9619–9640, https://doi.org/10.5194/acp-20-9619-2020, https://doi.org/10.5194/acp-20-9619-2020, 2020
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We have calculated an 11.5-year water vapour climatology using the Raman Lidar for Meteorological Observations (RALMO), located in Payerne, Switzerland. The climatology shows that the highest water vapour concentrations are in the summer months and the lowest in the winter months. We present for the first time height-resolved water vapour trends, which show that water vapour increases specific humidity by between 5 % and 15 % per decade depending on the altitude.
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This paper builds upon the work in von Clarmann and Grabowski (2007) concerning the a priori profile influence in the optimal estimation method applied to active remote sensing measurements, with examples given for lidar retrievals of temperature and water vapor mixing ratio. The optimal estimation method is a new technique for many active remote sensing researchers. This study gives insight into understanding the effect on retrievals of the a priori information.
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This article aims at providing details on the special aerosol properties observed during 2023 Canadian wildfire plume transport and exploring the synergism between remote sensing and in situ measurements for investigating the cause of the occurrence of the observations of special aerosol properties.
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Atmos. Meas. Tech., 18, 3135–3146, https://doi.org/10.5194/amt-18-3135-2025, https://doi.org/10.5194/amt-18-3135-2025, 2025
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PurpleAir sensors provide a low-cost way to monitor air quality, with over 30 000 sensors available worldwide. However, their measurements require calibration with trusted data for accuracy. Our new technique builds on previous calibration methods by also enabling the measurement of a quantity related to how pollutants grow with humidity. Mapping this new quantity will improve air quality forecasting.
Vasura Jayaweera, Robert J. Sica, Giovanni Martucci, and Alexander Haefele
Atmos. Meas. Tech., 18, 1461–1469, https://doi.org/10.5194/amt-18-1461-2025, https://doi.org/10.5194/amt-18-1461-2025, 2025
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EARLINET/ACTRIS organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. The work presented herein focuses on deriving a common methodology for applying a synergistic retrieval that utilizes the network's ground-based passive and active remote sensing measurements and deriving the aerosols from anthropogenic activities over Europe.
Eric Sauvageat, Klemens Hocke, Eliane Maillard Barras, Shengyi Hou, Quentin Errera, Alexander Haefele, and Axel Murk
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In Switzerland, two microwave radiometers can measure continuous ozone profiles in the middle atmosphere. From these instruments, we can study the diurnal variation of ozone, which is difficult to observe otherwise. It is valuable to validate the model simulations of diurnal variations in this region. We present results obtained during the last decade and compare them against various models. For the first time, we also show that the winter diurnal variations have some short-term fluctuations.
Eliane Maillard Barras, Alexander Haefele, René Stübi, Achille Jouberton, Herbert Schill, Irina Petropavlovskikh, Koji Miyagawa, Martin Stanek, and Lucien Froidevaux
Atmos. Chem. Phys., 22, 14283–14302, https://doi.org/10.5194/acp-22-14283-2022, https://doi.org/10.5194/acp-22-14283-2022, 2022
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Intercomparisons of three Dobson and three Brewer spectrophotometers at Arosa/Davos, Switzerland, are used for the homogenization of the longest Umkehr ozone profiles time series worldwide. Dynamic linear modeling (DLM) reveals a significant positive trend after 2004 in the upper stratosphere, a persistent negative trend between 25 and 30 km in the middle stratosphere, and a negative trend at 20 km in the lower stratosphere, with different levels of significance depending on the dataset.
Eric Sauvageat, Eliane Maillard Barras, Klemens Hocke, Alexander Haefele, and Axel Murk
Atmos. Meas. Tech., 15, 6395–6417, https://doi.org/10.5194/amt-15-6395-2022, https://doi.org/10.5194/amt-15-6395-2022, 2022
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We present new harmonized ozone time series from two ground-based microwave radiometers in Switzerland. The new series consist of hourly ozone profiles in the middle atmosphere (~ 20–70 km) from 2009 until 2021. Cross-validation of the new data series shows the benefit of the harmonization process compared to the previous versions. Comparisons with collocated satellite observations is used to further validate these time series for long-term ozone monitoring over central Europe.
Fernando Chouza, Thierry Leblanc, Mark Brewer, Patrick Wang, Giovanni Martucci, Alexander Haefele, Hélène Vérèmes, Valentin Duflot, Guillaume Payen, and Philippe Keckhut
Atmos. Meas. Tech., 15, 4241–4256, https://doi.org/10.5194/amt-15-4241-2022, https://doi.org/10.5194/amt-15-4241-2022, 2022
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The comparison of water vapor lidar measurements with co-located radiosondes and aerosol backscatter profiles indicates that laser-induced aerosol fluorescence in smoke layers injected into the stratosphere can introduce very large and chronic wet biases above 15 km, thus impacting the ability of these systems to accurately estimate long-term water vapor trends. The proposed correction method presented in this work is able to reduce this fluorescence-induced bias from 75 % to under 5 %.
Hugues Brenot, Nicolas Theys, Lieven Clarisse, Jeroen van Gent, Daniel R. Hurtmans, Sophie Vandenbussche, Nikolaos Papagiannopoulos, Lucia Mona, Timo Virtanen, Andreas Uppstu, Mikhail Sofiev, Luca Bugliaro, Margarita Vázquez-Navarro, Pascal Hedelt, Michelle Maree Parks, Sara Barsotti, Mauro Coltelli, William Moreland, Simona Scollo, Giuseppe Salerno, Delia Arnold-Arias, Marcus Hirtl, Tuomas Peltonen, Juhani Lahtinen, Klaus Sievers, Florian Lipok, Rolf Rüfenacht, Alexander Haefele, Maxime Hervo, Saskia Wagenaar, Wim Som de Cerff, Jos de Laat, Arnoud Apituley, Piet Stammes, Quentin Laffineur, Andy Delcloo, Robertson Lennart, Carl-Herbert Rokitansky, Arturo Vargas, Markus Kerschbaum, Christian Resch, Raimund Zopp, Matthieu Plu, Vincent-Henri Peuch, Michel Van Roozendael, and Gerhard Wotawa
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René Stübi, Herbert Schill, Eliane Maillard Barras, Jörg Klausen, and Alexander Haefele
Atmos. Meas. Tech., 14, 4203–4217, https://doi.org/10.5194/amt-14-4203-2021, https://doi.org/10.5194/amt-14-4203-2021, 2021
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Total ozone column has been measured since 1926 in the Swiss Alps station Arosa. These worldwide series are based on Dobson sun spectrophotometers. To assure the continuity of these series, a two-stage project was realized at MeteoSwiss: first, Dobson instruments were automated, and then parallel measurements between Arosa and a nearby site in Davos were carried out. The analysis of the data of the manual-to-automated transition and coincident data between the two sites are presented here.
Giovanni Martucci, Francisco Navas-Guzmán, Ludovic Renaud, Gonzague Romanens, S. Mahagammulla Gamage, Maxime Hervo, Pierre Jeannet, and Alexander Haefele
Atmos. Meas. Tech., 14, 1333–1353, https://doi.org/10.5194/amt-14-1333-2021, https://doi.org/10.5194/amt-14-1333-2021, 2021
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This article presents a validation of 1.5 years of pure rotational temperature data measured by the Raman lidar RALMO installed at the MeteoSwiss station of Payerne. The statistical results are in terms of bias and standard deviation with respect to two well-established radiosounding systems. The statistics are divided into daytime (bias = 0.28 K, SD = 0.62±0.03 K) and nighttime (bias = 0.29 K, SD = 0.66±0.06 K). The lidar temperature profiles are applied to cloud supersaturation studies.
Simone Brunamonti, Giovanni Martucci, Gonzague Romanens, Yann Poltera, Frank G. Wienhold, Maxime Hervo, Alexander Haefele, and Francisco Navas-Guzmán
Atmos. Chem. Phys., 21, 2267–2285, https://doi.org/10.5194/acp-21-2267-2021, https://doi.org/10.5194/acp-21-2267-2021, 2021
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Lidar (light detection and ranging) is a class of remote-sensing instruments that are widely used for the monitoring of aerosol properties in the lower levels of the atmosphere, yet their measurements are affected by several sources of uncertainty. Here we present the first comparison of two lidar systems against a fully independent instrument carried by meteorological balloons. We show that both lidars achieve a good agreement with the high-precision balloon measurements up to 6 km altitude.
Ghazal Farhani, Robert J. Sica, and Mark Joseph Daley
Atmos. Meas. Tech., 14, 391–402, https://doi.org/10.5194/amt-14-391-2021, https://doi.org/10.5194/amt-14-391-2021, 2021
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While it is relatively straightforward to automate the processing of lidar signals, it is difficult to automatically preprocess the measurements to distinguish between
goodand
badscans. It is easy to train humans to perform the task; however, considering the growing number of measurements, it is a time-consuming, on-going process. We have tested some machine learning algorithms for lidar signal classification and had success with both supervised and unsupervised methods.
Martine Collaud Coen, Elisabeth Andrews, Alessandro Bigi, Giovanni Martucci, Gonzague Romanens, Frédéric P. A. Vogt, and Laurent Vuilleumier
Atmos. Meas. Tech., 13, 6945–6964, https://doi.org/10.5194/amt-13-6945-2020, https://doi.org/10.5194/amt-13-6945-2020, 2020
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The Mann–Kendall trend test requires prewhitening in the presence of serially correlated data. The effects of five prewhitening methods and time granularity, autocorrelation, temporal segmentation and length of the time series on the statistical significance and the slope are studies for seven atmospheric datasets. Finally, a new algorithm using three prewhitening methods is proposed in order to optimize the power of the test, the amount of erroneous false positive trends and the slope estimate.
Shannon Hicks-Jalali, Robert J. Sica, Giovanni Martucci, Eliane Maillard Barras, Jordan Voirin, and Alexander Haefele
Atmos. Chem. Phys., 20, 9619–9640, https://doi.org/10.5194/acp-20-9619-2020, https://doi.org/10.5194/acp-20-9619-2020, 2020
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We have calculated an 11.5-year water vapour climatology using the Raman Lidar for Meteorological Observations (RALMO), located in Payerne, Switzerland. The climatology shows that the highest water vapour concentrations are in the summer months and the lowest in the winter months. We present for the first time height-resolved water vapour trends, which show that water vapour increases specific humidity by between 5 % and 15 % per decade depending on the altitude.
Eliane Maillard Barras, Alexander Haefele, Liliane Nguyen, Fiona Tummon, William T. Ball, Eugene V. Rozanov, Rolf Rüfenacht, Klemens Hocke, Leonie Bernet, Niklaus Kämpfer, Gerald Nedoluha, and Ian Boyd
Atmos. Chem. Phys., 20, 8453–8471, https://doi.org/10.5194/acp-20-8453-2020, https://doi.org/10.5194/acp-20-8453-2020, 2020
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To determine the part of the variability of the long-term ozone profile trends coming from measurement timing, we estimate microwave radiometer trends for each hour of the day with a multiple linear regression model. The variation in the trend with local solar time is not significant at the 95 % confidence level either in the stratosphere or in the low mesosphere. We conclude that systematic sampling differences between instruments cannot explain significant differences in trend estimates.
Holger Baars, Albert Ansmann, Kevin Ohneiser, Moritz Haarig, Ronny Engelmann, Dietrich Althausen, Ingrid Hanssen, Michael Gausa, Aleksander Pietruczuk, Artur Szkop, Iwona S. Stachlewska, Dongxiang Wang, Jens Reichardt, Annett Skupin, Ina Mattis, Thomas Trickl, Hannes Vogelmann, Francisco Navas-Guzmán, Alexander Haefele, Karen Acheson, Albert A. Ruth, Boyan Tatarov, Detlef Müller, Qiaoyun Hu, Thierry Podvin, Philippe Goloub, Igor Veselovskii, Christophe Pietras, Martial Haeffelin, Patrick Fréville, Michaël Sicard, Adolfo Comerón, Alfonso Javier Fernández García, Francisco Molero Menéndez, Carmen Córdoba-Jabonero, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Daniele Bortoli, Maria João Costa, Davide Dionisi, Gian Luigi Liberti, Xuan Wang, Alessia Sannino, Nikolaos Papagiannopoulos, Antonella Boselli, Lucia Mona, Giuseppe D'Amico, Salvatore Romano, Maria Rita Perrone, Livio Belegante, Doina Nicolae, Ivan Grigorov, Anna Gialitaki, Vassilis Amiridis, Ourania Soupiona, Alexandros Papayannis, Rodanthi-Elisaveth Mamouri, Argyro Nisantzi, Birgit Heese, Julian Hofer, Yoav Y. Schechner, Ulla Wandinger, and Gelsomina Pappalardo
Atmos. Chem. Phys., 19, 15183–15198, https://doi.org/10.5194/acp-19-15183-2019, https://doi.org/10.5194/acp-19-15183-2019, 2019
Shayamila Mahagammulla Gamage, Robert J. Sica, Giovanni Martucci, and Alexander Haefele
Atmos. Meas. Tech., 12, 5801–5816, https://doi.org/10.5194/amt-12-5801-2019, https://doi.org/10.5194/amt-12-5801-2019, 2019
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We present a new method for retrieving temperature from pure rotational Raman (PRR) lidar measurements using an optimal estimation method. We show that the error due to calibration can be reduced significantly using our method. The new method is tested on PRR temperature measurements from the MeteoSwiss Raman Lidar for Meteorological Observations system in different sky conditions. The next step is to assimilate the temperature profiles into models to help improve weather forecasts.
Stephan Nyeki, Stefan Wacker, Christine Aebi, Julian Gröbner, Giovanni Martucci, and Laurent Vuilleumier
Atmos. Chem. Phys., 19, 13227–13241, https://doi.org/10.5194/acp-19-13227-2019, https://doi.org/10.5194/acp-19-13227-2019, 2019
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The trends of meteorological parameters and surface downward shortwave radiation (DSR) and downward longwave radiation (DLR) were analysed at four stations (between 370 and 3580 m a. s. l.) in Switzerland for the 1996–2015 period. Trends in DSR and DLR were positive during cloudy as well as clear conditions. The trend due to the influence of clouds decreased in magnitude, which implies a reduction in cloud cover and/or a change towards a different cloud type over the four Swiss sites.
Francisco Navas-Guzmán, Giovanni Martucci, Martine Collaud Coen, María José Granados-Muñoz, Maxime Hervo, Michael Sicard, and Alexander Haefele
Atmos. Chem. Phys., 19, 11651–11668, https://doi.org/10.5194/acp-19-11651-2019, https://doi.org/10.5194/acp-19-11651-2019, 2019
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The present study demonstrates the capability of a Raman lidar to monitor aerosol hygroscopic processes. The results showed a higher hygroscopicity and wavelength dependency for smoke particles than for mineral dust. The higher sensitivity of the shortest wavelength to hygroscopic growth found for smoke particles was qualitatively reproduced using Mie simulations. The impact of aerosol hygroscopicity on the Earth's radiative balance has been evaluated using a radiative transfer model.
Ali Jalali, Shannon Hicks-Jalali, Robert J. Sica, Alexander Haefele, and Thomas von Clarmann
Atmos. Meas. Tech., 12, 3943–3961, https://doi.org/10.5194/amt-12-3943-2019, https://doi.org/10.5194/amt-12-3943-2019, 2019
Short summary
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This paper builds upon the work in von Clarmann and Grabowski (2007) concerning the a priori profile influence in the optimal estimation method applied to active remote sensing measurements, with examples given for lidar retrievals of temperature and water vapor mixing ratio. The optimal estimation method is a new technique for many active remote sensing researchers. This study gives insight into understanding the effect on retrievals of the a priori information.
Ghazal Farhani, Robert J. Sica, Sophie Godin-Beekmann, and Alexander Haefele
Atmos. Meas. Tech., 12, 2097–2111, https://doi.org/10.5194/amt-12-2097-2019, https://doi.org/10.5194/amt-12-2097-2019, 2019
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This paper presents a new application of the optimal estimation method (OEM) for the retrieval of ozone density profiles from DIAL measurements. The OEM results show excellent agreement with coincident ozonesonde measurements, with improved resolution over the traditional technique. The method also provides averaging kernels (facilitating comparison with other instruments), the vertical resolution of the retrieval, and a complete random and systematic uncertainty budget.
Christopher Perro, Thomas J. Duck, Glen Lesins, Kimberly Strong, Penny M. Rowe, James R. Drummond, and Robert J. Sica
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-381, https://doi.org/10.5194/amt-2018-381, 2019
Publication in AMT not foreseen
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A satellite retrieval for water vapour column was adapted for use over different surfaces in the wintertime Arctic. The retrieval was validated at multiple locations where there was excellent agreement. Reanalyses were found to be 10–15 % drier compared to our water vapour retrieval. Reanalyses represent the present day understanding of the atmosphere so this discrepancy between reanalyses and our retrieval could have implications for the current understanding of the climate.
Matthias Wiegner, Ina Mattis, Margit Pattantyús-Ábrahám, Juan Antonio Bravo-Aranda, Yann Poltera, Alexander Haefele, Maxime Hervo, Ulrich Görsdorf, Ronny Leinweber, Josef Gasteiger, Martial Haeffelin, Frank Wagner, Jan Cermak, Katerina Komínková, Mike Brettle, Christoph Münkel, and Kornelia Pönitz
Atmos. Meas. Tech., 12, 471–490, https://doi.org/10.5194/amt-12-471-2019, https://doi.org/10.5194/amt-12-471-2019, 2019
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Many ceilometers are influenced by water vapor absorption in the spectral range around 910 nm. Thus, a correction is required to retrieve aerosol optical properties. Validation of this correction scheme was performed in the framework of CeiLinEx2015 for several ceilometers with good agreement for Vaisala's CL51 ceilometer. For future applications we recommend monitoring the emitted wavelength and providing
darkmeasurements on a regular basis to be able to correct for signal artifacts.
Ali Jalali, Robert J. Sica, and Alexander Haefele
Atmos. Meas. Tech., 11, 6043–6058, https://doi.org/10.5194/amt-11-6043-2018, https://doi.org/10.5194/amt-11-6043-2018, 2018
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We use 16 years of lidar (laser radar) temperature measurements of the middle atmosphere to form a climatology for use in studying atmospheric temperature change using an optimal estimation method (OEM). Using OEM allows us to calculate a complete systematic and random uncertainty budget and allows for an additional 10–15 km in altitude for the measurement to be used, improving our ability to detect atmospheric temperature change up to 100 km of altitude.
Fanny Jeanneret, Giovanni Martucci, Simon Pinnock, and Alexis Berne
Atmos. Meas. Tech., 11, 4153–4170, https://doi.org/10.5194/amt-11-4153-2018, https://doi.org/10.5194/amt-11-4153-2018, 2018
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Above mountainous regions, satellites may have difficulty in discriminating snow from clouds: this study proposes a new method that combines different ground-based measurements to assess the sky cloudiness with high temporal resolution. The method's output is used as input to a model capable of identifying false satellite cloud detections. Results show that 62 ± 13 % of these false detections can be identified by the model when applied to the AVHRR-PM and MODIS Aqua data sets of the Cloud_cci.
Stelios Kazadzis, Natalia Kouremeti, Henri Diémoz, Julian Gröbner, Bruce W. Forgan, Monica Campanelli, Victor Estellés, Kathleen Lantz, Joseph Michalsky, Thomas Carlund, Emilio Cuevas, Carlos Toledano, Ralf Becker, Stephan Nyeki, Panagiotis G. Kosmopoulos, Viktar Tatsiankou, Laurent Vuilleumier, Frederick M. Denn, Nozomu Ohkawara, Osamu Ijima, Philippe Goloub, Panagiotis I. Raptis, Michael Milner, Klaus Behrens, Africa Barreto, Giovanni Martucci, Emiel Hall, James Wendell, Bryan E. Fabbri, and Christoph Wehrli
Atmos. Chem. Phys., 18, 3185–3201, https://doi.org/10.5194/acp-18-3185-2018, https://doi.org/10.5194/acp-18-3185-2018, 2018
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Aerosol optical depth measured from ground-based sun photometers is the most important parameter for studying the changes in the Earth's radiation balance due to aerosols. Representatives for various sun photometer types belonging to individual institutions or international aerosol networks gather every 5 years, for 3 weeks, in Davos, Switzerland, in order to compare their aeorosol optical depth retrievals. This work presents the results of the latest (fourth) filter radiometer intercomparison.
Emily M. McCullough, Robert J. Sica, James R. Drummond, Graeme J. Nott, Christopher Perro, and Thomas J. Duck
Atmos. Meas. Tech., 11, 861–879, https://doi.org/10.5194/amt-11-861-2018, https://doi.org/10.5194/amt-11-861-2018, 2018
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Measuring the phase (liquid and ice) of Arctic clouds is essential for understanding the changing global climate. Using a lidar, two polarized signals are usually needed. At CRL lidar, one of these signals is small, so phase measurements have low resolution. Another method can use a large unpolarized signal in place of the small polarized signal. We show how to use the original low-resolution measurement to calibrate the new high-resolution method. At CRL, this gives 20 times higher resolution.
Francisco Navas-Guzmán, Niklaus Kämpfer, Franziska Schranz, Wolfgang Steinbrecht, and Alexander Haefele
Atmos. Chem. Phys., 17, 14085–14104, https://doi.org/10.5194/acp-17-14085-2017, https://doi.org/10.5194/acp-17-14085-2017, 2017
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The paper presents assessment of the stratospheric measurements of a relatively new temperature radiometer (TEMPERA) at 60 GHz. The temperature profiles from TEMPERA have been compared with measurements from different techniques such as radiosondes, MLS satellite and Rayleigh lidar and with the temperature outputs from the SD-WACCM model. The results showed absolute biases and standard deviations lower than 2 K for most of the altitudes and comparisons, proving the good performance of TEMPERA.
Emily M. McCullough, Robert J. Sica, James R. Drummond, Graeme Nott, Christopher Perro, Colin P. Thackray, Jason Hopper, Jonathan Doyle, Thomas J. Duck, and Kaley A. Walker
Atmos. Meas. Tech., 10, 4253–4277, https://doi.org/10.5194/amt-10-4253-2017, https://doi.org/10.5194/amt-10-4253-2017, 2017
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CRL lidar in the Canadian High Arctic uses lasers and a telescope to study polar clouds, essential for understanding the changing global climate. Hardware added to CRL allows it to measure the polarization of returned laser light, indicating whether cloud particles are liquid or frozen. Calibrations show that traditional analysis methods work well, although CRL was not originally set up to make this type of measurement. CRL can now measure cloud particle phase every 5 min, every 37.5 m, 24h/day.
Francesco De Angelis, Domenico Cimini, Ulrich Löhnert, Olivier Caumont, Alexander Haefele, Bernhard Pospichal, Pauline Martinet, Francisco Navas-Guzmán, Henk Klein-Baltink, Jean-Charles Dupont, and James Hocking
Atmos. Meas. Tech., 10, 3947–3961, https://doi.org/10.5194/amt-10-3947-2017, https://doi.org/10.5194/amt-10-3947-2017, 2017
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Modern data assimilation systems require knowledge of the typical differences between observations and model background (O–B). This work illustrates a 1-year O–B analysis for ground-based microwave radiometer (MWR) observations in clear-sky conditions for a prototype network of six MWRs in Europe. Observations are MWR brightness temperatures (TB). Background profiles extracted from the output of a convective-scale model are used to simulate TB through the radiative transfer model RTTOV-gb.
Yann Poltera, Giovanni Martucci, Martine Collaud Coen, Maxime Hervo, Lukas Emmenegger, Stephan Henne, Dominik Brunner, and Alexander Haefele
Atmos. Chem. Phys., 17, 10051–10070, https://doi.org/10.5194/acp-17-10051-2017, https://doi.org/10.5194/acp-17-10051-2017, 2017
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We present the PathfinderTURB algorithm for the analysis of ceilometer backscatter data and the real-time detection of the vertical structure of the planetary boundary layer. PathfinderTURB has been applied to 1 year of data measured by two ceilometers operated at two Swiss stations: the Aerological Observatory of Payerne on the Swiss plateau, and the Alpine Jungfraujoch observatory. The study shows that aerosols from the boundary layer significantly influence the air measured at Jungfraujoch.
Darius Ceburnis, Matteo Rinaldi, Jurgita Ovadnevaite, Giovanni Martucci, Lara Giulianelli, and Colin D. O'Dowd
Atmos. Chem. Phys., 16, 12425–12439, https://doi.org/10.5194/acp-16-12425-2016, https://doi.org/10.5194/acp-16-12425-2016, 2016
Francisco Navas-Guzmán, Niklaus Kämpfer, and Alexander Haefele
Atmos. Meas. Tech., 9, 4587–4600, https://doi.org/10.5194/amt-9-4587-2016, https://doi.org/10.5194/amt-9-4587-2016, 2016
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The paper presents the assessment of the tropospheric measurements of a new temperature radiometer (TEMPERA) at 60 GHz. The temperature profiles from TEMPERA are compared with independent in situ radiosonde measurements. The TEMPERA performance is also compared with that of a commercial microwave radiometer (HATPRO). In addition, the brightness temperatures from both microwave radiometers are compared with the ones simulated using a radiative transfer model, ARTS.
Thierry Leblanc, Robert J. Sica, Joanna A. E. van Gijsel, Sophie Godin-Beekmann, Alexander Haefele, Thomas Trickl, Guillaume Payen, and Frank Gabarrot
Atmos. Meas. Tech., 9, 4029–4049, https://doi.org/10.5194/amt-9-4029-2016, https://doi.org/10.5194/amt-9-4029-2016, 2016
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This article prescribes two standardized formulations for the reporting of vertical resolution of lidar ozone and temperature profiles across an entire atmospheric observation network. Thanks to these standardized definitions, profiles from various instruments and techniques can be compared without ambiguity when interpreting their ability to resolve vertically fine geophysical structures.
Thierry Leblanc, Robert J. Sica, Joanna A. E. van Gijsel, Sophie Godin-Beekmann, Alexander Haefele, Thomas Trickl, Guillaume Payen, and Gianluigi Liberti
Atmos. Meas. Tech., 9, 4051–4078, https://doi.org/10.5194/amt-9-4051-2016, https://doi.org/10.5194/amt-9-4051-2016, 2016
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This article proposes a standardized approach for the treatment of uncertainty in the ozone differential absorption lidar data processing algorithms. The recommendations are designed to be used homogeneously across large atmospheric observation networks such as NDACC, and allow a clear understanding of the uncertainty budget of multiple lidar datasets for a large spectrum of ozone-related science applications (e.g., climatology, long-term trends, air quality).
Thierry Leblanc, Robert J. Sica, Joanna A. E. van Gijsel, Alexander Haefele, Guillaume Payen, and Gianluigi Liberti
Atmos. Meas. Tech., 9, 4079–4101, https://doi.org/10.5194/amt-9-4079-2016, https://doi.org/10.5194/amt-9-4079-2016, 2016
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This article prescribes a standardized approach for the treatment of uncertainty in the backscatter temperature lidar data processing algorithms. The recommendations are designed to be used homogeneously across large atmospheric observation networks such as NDACC, and allow a clear understanding of the uncertainty budget of multiple lidar datasets for a large spectrum of middle atmospheric science applications (e.g., climatology, long-term trends, mesospheric tides, satellite validation).
Maxime Hervo, Yann Poltera, and Alexander Haefele
Atmos. Meas. Tech., 9, 2947–2959, https://doi.org/10.5194/amt-9-2947-2016, https://doi.org/10.5194/amt-9-2947-2016, 2016
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Imperfections in a lidar's overlap function lead to artefacts in the lidar (Light Detection and Ranging) signals. These artefacts can erroneously be interpreted as an aerosol gradient or, in extreme cases, as a cloud base leading to false cloud detection. In this study an algorithm is presented to correct such artefacts.
The algorithm is completely automatic and does not require any intervention on site. It is therefore suited for use in large automatic lidar networks.
M. Sicard, G. D'Amico, A. Comerón, L. Mona, L. Alados-Arboledas, A. Amodeo, H. Baars, J. M. Baldasano, L. Belegante, I. Binietoglou, J. A. Bravo-Aranda, A. J. Fernández, P. Fréville, D. García-Vizcaíno, A. Giunta, M. J. Granados-Muñoz, J. L. Guerrero-Rascado, D. Hadjimitsis, A. Haefele, M. Hervo, M. Iarlori, P. Kokkalis, D. Lange, R. E. Mamouri, I. Mattis, F. Molero, N. Montoux, A. Muñoz, C. Muñoz Porcar, F. Navas-Guzmán, D. Nicolae, A. Nisantzi, N. Papagiannopoulos, A. Papayannis, S. Pereira, J. Preißler, M. Pujadas, V. Rizi, F. Rocadenbosch, K. Sellegri, V. Simeonov, G. Tsaknakis, F. Wagner, and G. Pappalardo
Atmos. Meas. Tech., 8, 4587–4613, https://doi.org/10.5194/amt-8-4587-2015, https://doi.org/10.5194/amt-8-4587-2015, 2015
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In the framework of the ACTRIS summer 2012 measurement campaign (8 June–17 July 2012), EARLINET organized and performed a controlled exercise of feasibility to demonstrate its potential to perform operational, coordinated measurements and deliver products in near-real time. The paper describes the measurement protocol and discusses the delivery of real-time and near-real-time lidar-derived products.
E. Maillard Barras, A. Haefele, R. Stübi, and D. Ruffieux
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-8-3399-2015, https://doi.org/10.5194/amtd-8-3399-2015, 2015
Revised manuscript not accepted
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We report on a method to combine simultaneous radiosonde and microwave radiometer measurements in order to obtain the SASBE of the vertical ozone distribution above Payerne, Switzerland. The two measurements are combined by using the radiosonde ozone profile as a priori information in the optimal estimation retrieval of the microwave radiometer. A comparison of the SASBE ozone profiles with AURA/MLS ozone profiles is presented.
M. Collaud Coen, C. Praz, A. Haefele, D. Ruffieux, P. Kaufmann, and B. Calpini
Atmos. Chem. Phys., 14, 13205–13221, https://doi.org/10.5194/acp-14-13205-2014, https://doi.org/10.5194/acp-14-13205-2014, 2014
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An operational planetary boundary layer height detection method with several remote sensing instruments (wind profiler, Raman lidar, microwave radiometer) and algorithms (Parcel and bulk Richardson number methods, surface-based temperature inversion, aerosol and humidity gradient analysis) was validated against radio sounding. A comparison with the numerical weather prediction model COSMO-2 and the seasonal cycles of the day- and nighttime PBL for two stations on the Swiss plateau are presented.
F. Madonna, M. Rosoldi, J. Güldner, A. Haefele, R. Kivi, M. P. Cadeddu, D. Sisterson, and G. Pappalardo
Atmos. Meas. Tech., 7, 3813–3823, https://doi.org/10.5194/amt-7-3813-2014, https://doi.org/10.5194/amt-7-3813-2014, 2014
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The paper provides the community with criteria to quantify the value of complementary climate measurements and to assess how the uncertainty in a measurement of an ECV is reduced by measurement complementarity. The study demonstrates the potential of entropy and mutual correlation, defined in information theory as metrics for quantifying synergies, and shows that the random uncertainties of a single instrument time series of TCWV can be strongly reduced by including complementary measurements.
E. Brocard, R. Philipona, A. Haefele, G. Romanens, A. Mueller, D. Ruffieux, V. Simeonov, and B. Calpini
Atmos. Meas. Tech., 6, 1347–1358, https://doi.org/10.5194/amt-6-1347-2013, https://doi.org/10.5194/amt-6-1347-2013, 2013
A. Moss, R. J. Sica, E. McCullough, K. Strawbridge, K. Walker, and J. Drummond
Atmos. Meas. Tech., 6, 741–749, https://doi.org/10.5194/amt-6-741-2013, https://doi.org/10.5194/amt-6-741-2013, 2013
P. E. Sheese, K. Strong, E. J. Llewellyn, R. L. Gattinger, J. M. Russell III, C. D. Boone, M. E. Hervig, R. J. Sica, and J. Bandoro
Atmos. Meas. Tech., 5, 2993–3006, https://doi.org/10.5194/amt-5-2993-2012, https://doi.org/10.5194/amt-5-2993-2012, 2012
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
A study of measurement scenarios for the future CO2M mission: avoidance of detector saturation and the impact on XCO2 retrievals
Assimilation of volcanic sulfur dioxide products from IASI and TROPOMI into the chemical transport model MOCAGE: case study of the 2021 La Soufrière Saint Vincent eruption with the March 2022 version of MOCAGE
In-flight estimation of instrument spectral response functions using sparse representations
Robustness of atmospheric trace gas retrievals obtained from low-spectral-resolution Fourier transform infrared absorption spectra under variations of interferogram length
Retrieval of NO2 profiles from 3 years of Pandora MAX-DOAS measurements in Toronto, Canada
A channel selection methodology for enhancing volcanic SO2 monitoring using FY-3E/HIRAS-II hyperspectral data
Predictions of failed satellite retrieval of air quality using machine learning
Deep transfer learning method for seasonal TROPOMI XCH4 albedo correction
Global retrieval of TROPOMI tropospheric HCHO and NO2 columns with improved consistency based on the updated Peking University OMI NO2 algorithm
Tightening-up methane plume source rate estimation in EnMAP and PRISMA images
Quantitative estimate of several sources of uncertainty in drone-based methane emission measurements
Implementation and application of an improved phase spectrum determination scheme for Fourier transform spectrometry
Improved detection of global NOx emissions from shipping in Sentinel-5P TROPOMI data
Remote sensing of lower-middle-thermosphere temperatures using the N2 Lyman–Birge–Hopfield (LBH) bands
Retrievals of water vapour and temperature exploiting the far-infrared: application to aircraft observations in preparation for the FORUM mission
Global decadal measurements of methanol, ethene, ethyne, and HCN from the Cross-track Infrared Sounder
Forward model emulator for atmospheric radiative transfer using Gaussian processes and cross validation
The novel GOME-type Ozone Profile Essential Climate Variable (GOP-ECV) data record covering the past 26 years
Developments on a 22 GHz microwave radiometer and reprocessing of 13-year time series for water vapour studies
Optimal selection of satellite XCO2 images for urban CO2 emission monitoring
Separating and quantifying facility-level methane emissions with overlapping plumes for spaceborne methane monitoring
Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks
Surface reflectance biases in XCH4 retrievals from the 2.3 μm band are enhanced in the presence of aerosols
Remote sensing of methane point sources with the MethaneAIR airborne spectrometer
The differences between remote sensing and in situ air pollutant measurements over the Canadian oil sands
NitroNet – a machine learning model for the prediction of tropospheric NO2 profiles from TROPOMI observations
Improved convective cloud differential (CCD) tropospheric ozone from S5P-TROPOMI satellite data using local cloud fields
Atmospheric propane (C3H8) column retrievals from ground-based FTIR observations in Xianghe, China
Hourly surface nitrogen dioxide retrieval from GEMS tropospheric vertical column densities: Benefit of using time-contiguous input features for machine learning models
Can the remote sensing of combustion phase improve estimates of landscape fire smoke emission rate and composition?
Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS
Troposphere–stratosphere-integrated bromine monoxide (BrO) profile retrieval over the central Pacific Ocean
Local and regional enhancements of CH4, CO, and CO2 inferred from TCCON column measurements
Merging TEMPEST microwave and GOES-16 geostationary IR soundings for improved water vapor profiles
Remote Sensing Estimates of Time-Resolved HONO and NO2 Emission Rates and Lifetimes in Wildfires
Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission
Mapping the CO2 total column retrieval performance from shortwave infrared measurements: synthetic impacts of the spectral resolution, signal-to-noise ratio, and spectral band selection
Assessment of the contribution of the Meteosat Third Generation Infrared Sounder (MTG-IRS) for the characterisation of ozone over Europe
Assessing the potential of free-tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events
Current potential of CH4 emission estimates using TROPOMI in the Middle East
A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument
Estimation of biogenic volatile organic compound (BVOC) emissions in forest ecosystems using drone-based lidar, photogrammetry, and image recognition technologies
Fast retrieval of XCO2 over east Asia based on Orbiting Carbon Observatory-2 (OCO-2) spectral measurements
A new method for estimating megacity NOx emissions and lifetimes from satellite observations
Accounting for the effect of aerosols in GHGSat methane retrieval
A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B
Global retrieval of stratospheric and tropospheric BrO columns from the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on board the Suomi-NPP satellite
IMK–IAA MIPAS retrieval version 8: CH4 and N2O
Report on Landsat 8 and Sentinel-2B observations of the Nord Stream 2 pipeline methane leak
U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers
Michael Weimer, Michael Hilker, Stefan Noël, Max Reuter, Michael Buchwitz, Blanca Fuentes Andrade, Rüdiger Lang, Bernd Sierk, Yasjka Meijer, Heinrich Bovensmann, John P. Burrows, and Hartmut Bösch
Atmos. Meas. Tech., 18, 3321–3340, https://doi.org/10.5194/amt-18-3321-2025, https://doi.org/10.5194/amt-18-3321-2025, 2025
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Optical detectors have a maximum signal (saturation). Exceedance means that the measurement has to be discarded. We investigate where saturation will occur for the future European satellite mission dedicated to CO2 monitoring (CO2M) and strategies to avoid saturation. Saturation impacts coverage and precision, both of which are important for estimation of local CO2 emissions. We find that taking two pictures per sampling should be sufficient to avoid saturation for CO2M, with some impact on CO2 precision.
Mickaël Bacles, Jonathan Améric, and Vincent Guidard
Atmos. Meas. Tech., 18, 2659–2680, https://doi.org/10.5194/amt-18-2659-2025, https://doi.org/10.5194/amt-18-2659-2025, 2025
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Sulfur dioxide emitted during volcanic eruptions can be hazardous for aviation safety. A recent development aims at improving the forecasts of volcanic sulfur dioxide quantities made by the chemistry transport model developed at Météo-France by assimilated infrared and ultraviolet satellite instruments. We focus on the eruption event of the La Soufrière Saint Vincent volcano in April 2021. The combined assimilation of these observations always leads to better analyses and forecasts.
Jihanne El Haouari, Jean-Michel Gaucel, Christelle Pittet, Jean-Yves Tourneret, and Herwig Wendt
Atmos. Meas. Tech., 18, 2573–2590, https://doi.org/10.5194/amt-18-2573-2025, https://doi.org/10.5194/amt-18-2573-2025, 2025
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This paper explores new techniques based on sparse representations for estimating the spectral response functions of high-resolution spectrometers. The method is highly competitive, with commonly used parametric models yielding more accurate estimates while accounting for wavelength dependence. The resulting normalized estimation errors of the spectrometer spectral responses are less than 1 %, which will allow for better quantification of trace gas concentrations at the Earth surface.
Bavo Langerock, Martine De Mazière, Filip Desmet, Pauli Heikkinen, Rigel Kivi, Mahesh Kumar Sha, Corinne Vigouroux, Minqiang Zhou, Gopala Krishna Darbha, and Mohmmed Talib
Atmos. Meas. Tech., 18, 2439–2446, https://doi.org/10.5194/amt-18-2439-2025, https://doi.org/10.5194/amt-18-2439-2025, 2025
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Ground-based Fourier transform interferometer instruments have been used for many decades to measure direct solar light in the infrared to obtain high-resolution spectra from which atmospheric gas profile concentrations can be derived. It is shown that the typical processing chain used to derive atmospheric gas columns can be sensitive to relatively small shortenings of the recorded interferograms. Low-resolution recordings, used in more recent years, are more sensitive to such adaptations.
Ramina Alwarda, Kristof Bognar, Xiaoyi Zhao, Vitali Fioletov, Jonathan Davies, Sum Chi Lee, Debora Griffin, Alexandru Lupu, Udo Frieß, Alexander Cede, Yushan Su, and Kimberly Strong
Atmos. Meas. Tech., 18, 2397–2423, https://doi.org/10.5194/amt-18-2397-2025, https://doi.org/10.5194/amt-18-2397-2025, 2025
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Nitrogen dioxide (NO2) is a pollutant with a short lifetime and large variability, but there are limited measurements of its distribution in the lower atmosphere. We present a new 3-year dataset of NO2 vertical profiles in Toronto, Canada, and evaluate it using NO2 from satellite and surface monitoring networks and simulations by an air quality forecast model. We quantify and explain the differences among the datasets to provide information that can be used to understand NO2 variability.
Xinyu Li, Lin Zhu, Hongfu Sun, Jun Li, Ximing Lv, Chengli Qi, and Huanhuan Yan
Atmos. Meas. Tech., 18, 2333–2352, https://doi.org/10.5194/amt-18-2333-2025, https://doi.org/10.5194/amt-18-2333-2025, 2025
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This paper proposes a novel methodology for selecting sulfur-dioxide-sensitive channels from FY-3E/HIRAS-II hyperspectral IR atmospheric sensors to quantitatively monitor volcanic sulfur dioxide. This methodology considers the interference of atmospheric temperature, humidity, and surface temperature with sulfur dioxide detection and retrieval, laying the groundwork for developing a more accurate and flexible volcanic sulfur dioxide retrieval algorithm under different atmospheric conditions.
Edward Malina, Jure Brence, Jennifer Adams, Jovan Tanevski, Sašo Džeroski, Valentin Kantchev, and Kevin W. Bowman
Atmos. Meas. Tech., 18, 1689–1715, https://doi.org/10.5194/amt-18-1689-2025, https://doi.org/10.5194/amt-18-1689-2025, 2025
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The large fleet of Earth observation satellites in orbit currently generate huge volumes of data, requiring significant computational resources to process these data in a timely manner. We present a method for predicting poor-quality measurements using machine learning. We find that machine learning methods can accurately predict poor-quality measurements and remove them from the processing chain, saving time and computational resources.
Alexander C. Bradley, Barbara Dix, Fergus Mackenzie, J. Pepijn Veefkind, and Joost A. de Gouw
Atmos. Meas. Tech., 18, 1675–1687, https://doi.org/10.5194/amt-18-1675-2025, https://doi.org/10.5194/amt-18-1675-2025, 2025
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Currently, measurement of methane from the TROPOMI satellite is biased with respect to surface reflectance. This study demonstrates a new method of correcting for this bias on a seasonal timescale to allow for differences in surface reflectance in areas of intense agriculture where growing seasons may introduce a reflectance bias. We have successfully implemented this technique in the Denver–Julesburg basin, where agriculture and methane extraction infrastructure is often co-located.
Yuhang Zhang, Huan Yu, Isabelle De Smedt, Jintai Lin, Nicolas Theys, Michel Van Roozendael, Gaia Pinardi, Steven Compernolle, Ruijing Ni, Fangxuan Ren, Sijie Wang, Lulu Chen, Jos Van Geffen, Mengyao Liu, Alexander M. Cede, Martin Tiefengraber, Alexis Merlaud, Martina M. Friedrich, Andreas Richter, Ankie Piters, Vinod Kumar, Vinayak Sinha, Thomas Wagner, Yongjoo Choi, Hisahiro Takashima, Yugo Kanaya, Hitoshi Irie, Robert Spurr, Wenfu Sun, and Lorenzo Fabris
Atmos. Meas. Tech., 18, 1561–1589, https://doi.org/10.5194/amt-18-1561-2025, https://doi.org/10.5194/amt-18-1561-2025, 2025
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We developed an advanced algorithm for global retrieval of TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO2 vertical column densities with much improved consistency. Sensitivity tests demonstrate the complexity and nonlinear interactions of auxiliary parameters in the air mass factor calculation. An improved agreement is found with measurements from a global ground-based instrument network. The scientific retrieval provides a useful source of information for studies combining HCHO and NO2.
Elyes Ouerghi, Thibaud Ehret, Gabriele Facciolo, Enric Meinhardt, Rodolphe Marion, and Jean-Michel Morel
EGUsphere, https://doi.org/10.5194/egusphere-2025-1075, https://doi.org/10.5194/egusphere-2025-1075, 2025
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Reducing methane emissions is essential to tackle climate change. In this paper, we introduce MetFluxNet, a deep learning model for methane plume source rate estimation. This model is trained on a new synthetic dataset designed to avoid network overfit. MetFluxNet can accurately estimate low source rates even in the case of heterogeneous backgrounds. To demonstrate its reliability for real-world plume estimation, we validated its predictions on real plumes with known source rates.
Tannaz H. Mohammadloo, Matthew Jones, Bas van de Kerkhof, Kyle Dawson, Brendan J. Smith, Stephen Conley, Abigail Corbett, and Rutger IJzermans
Atmos. Meas. Tech., 18, 1301–1324, https://doi.org/10.5194/amt-18-1301-2025, https://doi.org/10.5194/amt-18-1301-2025, 2025
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Methane is a potent greenhouse gas. Trustable detection and quantification of methane emissions at facility level are critical for identifying the largest sources and prioritizing them for repair. We provide a systematic analysis of several sources of uncertainty in drone-based methane emission surveys based on theoretical considerations and historical data sets. We provide guidelines for industry on how to avoid or minimize errors in drone-based methane emission quantification surveys.
Frank Hase, Paolo Castracane, Angelika Dehn, Omaira Elena García, David W. T. Griffith, Lukas Heizmann, Nicholas B. Jones, Tomi Karppinen, Rigel Kivi, Martine de Mazière, Justus Notholt, and Mahesh Kumar Sha
Atmos. Meas. Tech., 18, 1257–1267, https://doi.org/10.5194/amt-18-1257-2025, https://doi.org/10.5194/amt-18-1257-2025, 2025
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The primary measurement result delivered by a Fourier transform spectrometer is an interferogram, and the spectrum required for further analysis needs to be calculated from the interferogram by Fourier analysis. The paper deals with technical aspects of this process and shows how the reconstruction of the spectrum can be optimized.
Miriam Latsch, Andreas Richter, John P. Burrows, and Hartmut Bösch
EGUsphere, https://doi.org/10.5194/egusphere-2025-107, https://doi.org/10.5194/egusphere-2025-107, 2025
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This study presents our advanced methods to better detect ship-related nitrogen dioxide (NO2) emissions in TROPOMI satellite data. By applying filtering techniques, we identify numerous global shipping routes, including previously undetectable ones, and emissions from offshore platforms. Additionally, we compare the filtered satellite data with CAMS global model data to estimate the differences between observed and modelled NO2 emissions.
Richard Eastes, J. Scott Evans, Quan Gan, William McClintock, and Jerry Lumpe
Atmos. Meas. Tech., 18, 921–928, https://doi.org/10.5194/amt-18-921-2025, https://doi.org/10.5194/amt-18-921-2025, 2025
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Temperature is essential to understanding the thermosphere. Most temperature measurements have been indirect or had large uncertainties, especially in the lower-middle thermosphere, where data are rarely available. Since October 2018, NASA’s GOLD mission has produced disk images of neutral temperatures near 160 km at locations over the Americas and Atlantic Ocean. This paper discusses both temperature retrieval techniques and issues in interpreting GOLD’s images of thermospheric temperatures.
Sanjeevani Panditharatne, Helen Brindley, Caroline Cox, Richard Siddans, Jonathan Murray, Laura Warwick, and Stuart Fox
Atmos. Meas. Tech., 18, 717–735, https://doi.org/10.5194/amt-18-717-2025, https://doi.org/10.5194/amt-18-717-2025, 2025
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Observations from the upcoming European Space Agency’s Far-Infrared Outgoing Radiation Understanding and Monitoring (FORUM) satellite are theorised to be highly sensitive to distributions of water vapour within Earth’s atmosphere. We exploit this sensitivity and extend the Infrared Microwave Sounding retrieval scheme for use on observations from FORUM. This scheme is evaluated on both simulated and observed measurements and shows good agreement with references of the atmospheric state.
Kelley C. Wells, Dylan B. Millet, Jared F. Brewer, Vivienne H. Payne, Karen E. Cady-Pereira, Rick Pernak, Susan Kulawik, Corinne Vigouroux, Nicholas Jones, Emmanuel Mahieu, Maria Makarova, Tomoo Nagahama, Ivan Ortega, Mathias Palm, Kimberly Strong, Matthias Schneider, Dan Smale, Ralf Sussmann, and Minqiang Zhou
Atmos. Meas. Tech., 18, 695–716, https://doi.org/10.5194/amt-18-695-2025, https://doi.org/10.5194/amt-18-695-2025, 2025
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Atmospheric volatile organic compounds (VOCs) affect both air quality and climate. Satellite measurements can help us to assess and predict their global impacts. We present new decadal (2012–2023) measurements of four key VOCs – methanol, ethene, ethyne, and hydrogen cyanide (HCN) – from the Cross-track Infrared Sounder. The measurements reflect emissions from major forests, wildfires, and industry and provide new information to advance understanding of these sources and their changes over time.
Otto Lamminpää, Jouni Susiluoto, Jonathan Hobbs, James McDuffie, Amy Braverman, and Houman Owhadi
Atmos. Meas. Tech., 18, 673–694, https://doi.org/10.5194/amt-18-673-2025, https://doi.org/10.5194/amt-18-673-2025, 2025
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We develop and demonstrate a fast forward function emulator for remote sensing of greenhouse gases. These forward functions are computationally expensive to evaluate, and as such the key challenge for many satellite missions in their data processing is the time used in these evaluations. Our method is fast and accurate enough, less than 1 % relative error, so that it could be safely used in operational processing.
Melanie Coldewey-Egbers, Diego G. Loyola, Barry Latter, Richard Siddans, Brian Kerridge, Daan Hubert, Michel van Roozendael, and Michael Eisinger
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-196, https://doi.org/10.5194/amt-2024-196, 2025
Preprint under review for AMT
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The GOME-type Ozone Profile Essential Climate Variable (GOP-ECV) data record provides monthly mean ozone profiles with global coverage from 1995 to 2021 at a spatial resolution of 5°x5°. Measurements from five nadir-viewing satellite sensors are first harmonized and then merged into a coherent record. The long-term stability of the data record is further improved through scaling of the profiles using as a reference the GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record.
Alistair Bell, Eric Sauvageat, Gunter Stober, Klemens Hocke, and Axel Murk
Atmos. Meas. Tech., 18, 555–567, https://doi.org/10.5194/amt-18-555-2025, https://doi.org/10.5194/amt-18-555-2025, 2025
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Hardware and software developments have been made on a 22 GHz microwave radiometer for the measurement of middle-atmospheric water vapour near Bern, Switzerland. Previous measurements dating back to 2010 have been re-calibrated and an improved optimal estimation retrieval performed on these measurements, giving a 13-year dataset. Measurements made with new and improved instrumental hardware are used to correct previous measurements, which show better agreement than the non-corrected dataset.
Alexandre Danjou, Grégoire Broquet, Andrew Schuh, François-Marie Bréon, and Thomas Lauvaux
Atmos. Meas. Tech., 18, 533–554, https://doi.org/10.5194/amt-18-533-2025, https://doi.org/10.5194/amt-18-533-2025, 2025
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We study the capacity of XCO2 spaceborne imagery to estimate urban CO2 emissions with synthetic data. We define automatic and standard methods and objective criteria for image selection. The wind variability and urban emission budget guide the emission estimation error. Images with low wind variability and high urban emissions account for 47 % of images and give a bias in the emission estimation of −7 % and a spread of 56 %. Other images give a bias of −31 % and a spread of 99 %.
Yiguo Pang, Longfei Tian, Denghui Hu, Shuang Gao, and Guohua Liu
Atmos. Meas. Tech., 18, 455–470, https://doi.org/10.5194/amt-18-455-2025, https://doi.org/10.5194/amt-18-455-2025, 2025
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The spatial adjacency of methane point sources can result in plume overlapping, presenting challenges for quantification from space. A separation and quantification method combining the Gaussian plume model and the integrated mass enhancement method is proposed. A modern parameter estimation technique is introduced to separate the overlapping plumes from satellite observations. The proposed method is evaluated with synthesized observations and real satellite observations.
Maximilian Reuter, Michael Hilker, Stefan Noël, Antonio Di Noia, Michael Weimer, Oliver Schneising, Michael Buchwitz, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 18, 241–264, https://doi.org/10.5194/amt-18-241-2025, https://doi.org/10.5194/amt-18-241-2025, 2025
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Carbon dioxide (CO2) and methane (CH4) are the main anthropogenic greenhouse gases. The European Copernicus CO2 monitoring satellite mission CO2M will provide measurements of their atmospheric concentrations, but the accuracy requirements are demanding and conventional retrieval methods computationally expensive. We present a new retrieval algorithm based on artificial neural networks that has the potential to meet the stringent requirements of the CO2M mission with minimal computational effort.
Peter Somkuti, Greg M. McGarragh, Christopher O'Dell, Antonio Di Noia, Leif Vogel, Sean Crowell, Lesley E. Ott, and Hartmut Bösch
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-145, https://doi.org/10.5194/amt-2024-145, 2025
Revised manuscript accepted for AMT
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In space-based estimates of atmospheric methane concentrations, one can often observe biases that look like imprints of surface features. We performed realistic simulation experiments and find the root cause to be unaccounted aerosols. Since good knowledge of aerosols is difficult to achieve for operational science data processing, we conclude that a comprehensive surface bias correction scheme is highly important for missions utilizing the 2.3 µm spectral band for methane retrievals.
Luis Guanter, Jack Warren, Mark Omara, Apisada Chulakadabba, Javier Roger, Maryann Sargent, Jonathan E. Franklin, Steven C. Wofsy, and Ritesh Gautam
EGUsphere, https://doi.org/10.5194/egusphere-2024-3577, https://doi.org/10.5194/egusphere-2024-3577, 2025
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This study presents a data processing scheme for the detection and quantification of methane emissions using the MethaneAIR airborne spectrometer. We show that the proposed methods enable the detection of smaller plumes than other existing methods, and that improves the potential of MethaneAIR to survey methane point sources across large regions
Xiaoyi Zhao, Vitali Fioletov, Debora Griffin, Chris McLinden, Ralf Staebler, Cristian Mihele, Kevin Strawbridge, Jonathan Davies, Ihab Abboud, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, and Robert Swap
Atmos. Meas. Tech., 17, 6889–6912, https://doi.org/10.5194/amt-17-6889-2024, https://doi.org/10.5194/amt-17-6889-2024, 2024
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This study explores differences between remote sensing and in situ instruments in terms of their vertical, horizontal, and temporal sampling differences. Understanding and resolving these differences are critical for future analyses linking satellite, ground-based remote sensing, and in situ observations in air quality monitoring. It shows that the meteorological conditions (wind directions, speed, and boundary layer conditions) will strongly affect the agreement between the two measurements.
Leon Kuhn, Steffen Beirle, Sergey Osipov, Andrea Pozzer, and Thomas Wagner
Atmos. Meas. Tech., 17, 6485–6516, https://doi.org/10.5194/amt-17-6485-2024, https://doi.org/10.5194/amt-17-6485-2024, 2024
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This paper presents a new machine learning model that allows us to compute NO2 concentration profiles from satellite observations. A neural network was trained on synthetic data from the regional chemistry and transport model WRF-Chem. This is the first model of its kind. We present a thorough model validation study, covering various seasons and regions of the world.
Swathi Maratt Satheesan, Kai-Uwe Eichmann, John P. Burrows, Mark Weber, Ryan Stauffer, Anne M. Thompson, and Debra Kollonige
Atmos. Meas. Tech., 17, 6459–6484, https://doi.org/10.5194/amt-17-6459-2024, https://doi.org/10.5194/amt-17-6459-2024, 2024
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CHORA, an advanced cloud convective differential technique, enhances the accuracy of tropospheric-ozone retrievals. Unlike the traditional Pacific cloud reference sector scheme, CHORA introduces a local-cloud reference sector and an alternative approach (CLCT) for precision. Analysing monthly averaged TROPOMI data from 2018 to 2022 and validating with SHADOZ ozonesonde data, CLCT outperforms other methods and so is the preferred choice, especially in future geostationary satellite missions.
Minqiang Zhou, Pucai Wang, Bart Dils, Bavo Langerock, Geoff Toon, Christian Hermans, Weidong Nan, Qun Cheng, and Martine De Mazière
Atmos. Meas. Tech., 17, 6385–6396, https://doi.org/10.5194/amt-17-6385-2024, https://doi.org/10.5194/amt-17-6385-2024, 2024
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Solar absorption spectra near 2967 cm−1 recorded by a ground-based FTIR with a high spectral resolution of 0.0035 cm-1 are applied to retrieve C3H8 columns for the first time in Xianghe, China, within the NDACC-IRWG. The mean and standard deviation of the C3H8 columns are 1.80 ± 0.81 (1σ) × 1015 molec. cm-2. Good correlations are found between C3H8 and other non-methane hydrocarbons, such as C2H6 (R = 0.84) and C2H2 (R = 0.79), as well as between C3H8 and CO (R = 0.72).
Janek Gödeke, Andreas Richter, Kezia Lange, Peter Maaß, Hyunkee Hong, Hanlim Lee, and Junsung Park
EGUsphere, https://doi.org/10.5194/egusphere-2024-3145, https://doi.org/10.5194/egusphere-2024-3145, 2024
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The Korean Geostationary Environmental Monitoring Spectrometer (GEMS) monitors trace gases over Asia, e.g., NO2. GEMS provides hourly data, improving the time-resolution compared to the daily overpasses by other satellites. For the prediction of hourly surface NO2 over Korea from GEMS observations and meteorological data, this study shows that machine learning models benefit from this higher time-resolution. This is achieved by using observations from previous hours as additional inputs.
Farrer Owsley-Brown, Martin J. Wooster, Mark J. Grosvenor, and Yanan Liu
Atmos. Meas. Tech., 17, 6247–6264, https://doi.org/10.5194/amt-17-6247-2024, https://doi.org/10.5194/amt-17-6247-2024, 2024
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Landscape fires produce vast amounts of smoke, affecting the atmosphere locally and globally. Whether a fire is flaming or smouldering strongly impacts the rate at which smoke is produced as well as its composition. This study tested two methods to determine these combustion phases in laboratory fires and compared them to the smoke emitted. One of these methods improved estimates of smoke emission significantly. This suggests potential for improvement in global emission estimates.
Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Víctor Molina García, Diego Loyola, Hanlim Lee, and Jhoon Kim
Atmos. Meas. Tech., 17, 6163–6191, https://doi.org/10.5194/amt-17-6163-2024, https://doi.org/10.5194/amt-17-6163-2024, 2024
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In this study, we developed an advanced retrieval algorithm for tropospheric NO2 columns from geostationary satellite spectrometers and applied it to GEMS measurements. The DLR GEMS NO2 retrieval algorithm follows the heritage from previous and existing algorithms, but improved approaches are applied to reflect the specific features of geostationary satellites. The DLR GEMS NO2 retrievals demonstrate a good capability for monitoring diurnal variability with a high spatial resolution.
Theodore K. Koenig, François Hendrick, Douglas Kinnison, Christopher F. Lee, Michel Van Roozendael, and Rainer Volkamer
Atmos. Meas. Tech., 17, 5911–5934, https://doi.org/10.5194/amt-17-5911-2024, https://doi.org/10.5194/amt-17-5911-2024, 2024
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Atmospheric bromine destroys ozone, impacts oxidation capacity, and oxidizes mercury into its toxic form. We constrain bromine by remote sensing of BrO from a mountaintop. Previous measurements retrieved two to three pieces of information vertically; we apply new methods to get five and a half vertically and two more in time. We compare with aircraft measurements to validate the methods and look at variations in BrO over the Pacific.
Kavitha Mottungan, Chayan Roychoudhury, Vanessa Brocchi, Benjamin Gaubert, Wenfu Tang, Mohammad Amin Mirrezaei, John McKinnon, Yafang Guo, David W. T. Griffith, Dietrich G. Feist, Isamu Morino, Mahesh K. Sha, Manvendra K. Dubey, Martine De Mazière, Nicholas M. Deutscher, Paul O. Wennberg, Ralf Sussmann, Rigel Kivi, Tae-Young Goo, Voltaire A. Velazco, Wei Wang, and Avelino F. Arellano Jr.
Atmos. Meas. Tech., 17, 5861–5885, https://doi.org/10.5194/amt-17-5861-2024, https://doi.org/10.5194/amt-17-5861-2024, 2024
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A combination of data analysis techniques is introduced to separate local and regional influences on observed levels of carbon dioxide, carbon monoxide, and methane from an established ground-based remote sensing network. We take advantage of the covariations in these trace gases to identify the dominant type of sources driving these levels. Applying these methods in conjunction with existing approaches to other datasets can better address uncertainties in identifying sources and sinks.
Chia-Pang Kuo and Christian Kummerow
Atmos. Meas. Tech., 17, 5637–5653, https://doi.org/10.5194/amt-17-5637-2024, https://doi.org/10.5194/amt-17-5637-2024, 2024
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A small satellite about the size of a shoe box, named TEMPEST, carries only a microwave sensor and is designed to measure the water cycle of the Earth from space in an economical way compared with traditional satellites, which have additional infrared sensors. To overcome the limitation, extra infrared signals from GOES-R ABI are combined with TEMPEST microwave measurements. Compared with ground observations, improved humidity information is extracted from the merged TEMPEST and ABI signals.
Carley D. Fredrickson, Scott J. Janz, Lok N. Lamsal, Ursula A. Jongebloed, Joshua L. Laughner, and Joel A. Thornton
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-158, https://doi.org/10.5194/amt-2024-158, 2024
Revised manuscript accepted for AMT
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We present an analysis of high-resolution remote sensing measurements of nitrogen-containing trace gases emitted by wildfires. The measurements were made using an instrument on the NASA ER-2 aircraft in the summer of 2019. We find that time-resolved fire intensity is critical to quantify trace gas emissions over a fire’s entire lifespan. These findings have implications for improving air pollution forecasts downwind of wildfires using computer models of atmospheric chemistry and meteorology.
Christopher Chan Miller, Sébastien Roche, Jonas S. Wilzewski, Xiong Liu, Kelly Chance, Amir H. Souri, Eamon Conway, Bingkun Luo, Jenna Samra, Jacob Hawthorne, Kang Sun, Carly Staebell, Apisada Chulakadabba, Maryann Sargent, Joshua S. Benmergui, Jonathan E. Franklin, Bruce C. Daube, Yang Li, Joshua L. Laughner, Bianca C. Baier, Ritesh Gautam, Mark Omara, and Steven C. Wofsy
Atmos. Meas. Tech., 17, 5429–5454, https://doi.org/10.5194/amt-17-5429-2024, https://doi.org/10.5194/amt-17-5429-2024, 2024
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MethaneSAT is an upcoming satellite mission designed to monitor methane emissions from the oil and gas (O&G) industry globally. Here, we present observations from the first flight campaign of MethaneAIR, a MethaneSAT-like instrument mounted on an aircraft. MethaneAIR can map methane with high precision and accuracy over a typically sized oil and gas basin (~200 km2) in a single flight. This paper demonstrates the capability of the upcoming satellite to routinely track global O&G emissions.
Matthieu Dogniaux and Cyril Crevoisier
Atmos. Meas. Tech., 17, 5373–5396, https://doi.org/10.5194/amt-17-5373-2024, https://doi.org/10.5194/amt-17-5373-2024, 2024
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Many CO2-observing satellite concepts, with very different design choices and trade-offs, are expected to be put into orbit during the upcoming decade. This work uses numerical simulations to explore the impact of critical design parameters on the performance of upcoming CO2-observing satellite concepts.
Francesca Vittorioso, Vincent Guidard, and Nadia Fourrié
Atmos. Meas. Tech., 17, 5279–5299, https://doi.org/10.5194/amt-17-5279-2024, https://doi.org/10.5194/amt-17-5279-2024, 2024
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The future Meteosat Third Generation Infrared Sounder (MTG-IRS) will represent a major innovation for the monitoring of the chemical state of the atmosphere. MTG-IRS will have the advantage of being based on a geostationary platform and acquiring data with a high temporal frequency. This work aims to evaluate its potential impact over Europe within a chemical transport model (MOCAGE). The results indicate that the assimilation of these data always has a positive impact on ozone analysis.
Matthias Schneider, Kinya Toride, Farahnaz Khosrawi, Frank Hase, Benjamin Ertl, Christopher J. Diekmann, and Kei Yoshimura
Atmos. Meas. Tech., 17, 5243–5259, https://doi.org/10.5194/amt-17-5243-2024, https://doi.org/10.5194/amt-17-5243-2024, 2024
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Despite its importance for extreme weather and climate feedbacks, atmospheric convection is not well constrained. This study assesses the potential of novel tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events. We find that the impact of the isotopologues is small for stable atmospheric conditions but significant for unstable conditions, which have the strongest societal impacts (e.g. storms and flooding).
Mengyao Liu, Ronald van der A, Michiel van Weele, Lotte Bryan, Henk Eskes, Pepijn Veefkind, Yongxue Liu, Xiaojuan Lin, Jos de Laat, and Jieying Ding
Atmos. Meas. Tech., 17, 5261–5277, https://doi.org/10.5194/amt-17-5261-2024, https://doi.org/10.5194/amt-17-5261-2024, 2024
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A new divergence method was developed and applied to estimate methane emissions from TROPOMI observations over the Middle East, where it is typically challenging for a satellite to measure methane due to its complicated orography and surface albedo. Our results show the potential of TROPOMI to quantify methane emissions from various sources rather than big emitters from space after objectively excluding the artifacts in the retrieval.
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, https://doi.org/10.5194/amt-17-5147-2024, 2024
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We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
Xianzhong Duan, Ming Chang, Guotong Wu, Suping Situ, Shengjie Zhu, Qi Zhang, Yibo Huangfu, Weiwen Wang, Weihua Chen, Bin Yuan, and Xuemei Wang
Atmos. Meas. Tech., 17, 4065–4079, https://doi.org/10.5194/amt-17-4065-2024, https://doi.org/10.5194/amt-17-4065-2024, 2024
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Accurately estimating biogenic volatile organic compound (BVOC) emissions in forest ecosystems has been challenging. This research presents a framework that utilizes drone-based lidar, photogrammetry, and image recognition technologies to identify plant species and estimate BVOC emissions. The largest cumulative isoprene emissions were found in the Myrtaceae family, while those of monoterpenes were from the Rubiaceae family.
Fengxin Xie, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang, Kei Shiomi, and Isamu Morino
Atmos. Meas. Tech., 17, 3949–3967, https://doi.org/10.5194/amt-17-3949-2024, https://doi.org/10.5194/amt-17-3949-2024, 2024
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This study demonstrates a new machine learning approach to efficiently and accurately estimate atmospheric carbon dioxide levels from satellite data. Rather than using traditional complex physics-based retrieval methods, neural network models are trained on simulated data to rapidly predict CO2 concentrations directly from satellite spectral measurements.
Steffen Beirle and Thomas Wagner
Atmos. Meas. Tech., 17, 3439–3453, https://doi.org/10.5194/amt-17-3439-2024, https://doi.org/10.5194/amt-17-3439-2024, 2024
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We present a new method for estimating emissions and lifetimes for nitrogen oxides emitted from large cities by using satellite NO2 observations combined with wind fields. The estimate is based on the simultaneous evaluation of the downwind plumes for opposing wind directions. This allows us to derive seasonal mean emissions and lifetimes for 100 cities around the globe.
Qiurun Yu, Dylan Jervis, and Yi Huang
Atmos. Meas. Tech., 17, 3347–3366, https://doi.org/10.5194/amt-17-3347-2024, https://doi.org/10.5194/amt-17-3347-2024, 2024
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This study estimated the effects of aerosols on GHGSat satellite methane retrieval and investigated the performance of simultaneously retrieving aerosol and methane information using a multi-angle viewing method. Results suggested that the performance of GHGSat methane retrieval improved when aerosols were considered, and the multi-angle viewing method is insensitive to the satellite angle setting. This performance assessment is useful for improving future GHGSat-like instruments.
Zhonghua He, Ling Gao, Miao Liang, and Zhao-Cheng Zeng
Atmos. Meas. Tech., 17, 2937–2956, https://doi.org/10.5194/amt-17-2937-2024, https://doi.org/10.5194/amt-17-2937-2024, 2024
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Using Gaofen-5B satellite data, this study detected 93 methane plume events from 32 coal mines in Shanxi, China, with emission rates spanning from 761.78 ± 185.00 to 12729.12 ± 4658.13 kg h-1, showing significant variability among sources. This study highlights Gaofen-5B’s capacity for monitoring large methane point sources, offering valuable support in reducing greenhouse gas emissions.
Heesung Chong, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Alfonso Saiz-Lopez, Rafael P. Fernandez, Hyeong-Ahn Kwon, Zolal Ayazpour, Huiqun Wang, Amir H. Souri, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Jhoon Kim, Ja-Ho Koo, William R. Simpson, François Hendrick, Richard Querel, Glen Jaross, Colin Seftor, and Raid M. Suleiman
Atmos. Meas. Tech., 17, 2873–2916, https://doi.org/10.5194/amt-17-2873-2024, https://doi.org/10.5194/amt-17-2873-2024, 2024
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We present a new bromine monoxide (BrO) product derived using radiances measured from OMPS-NM on board the Suomi-NPP satellite. This product provides nearly a decade of global stratospheric and tropospheric column retrievals, a feature that is currently rare in publicly accessible datasets. Both stratospheric and tropospheric columns from OMPS-NM demonstrate robust performance, exhibiting good agreement with ground-based observations collected at three stations (Lauder, Utqiagvik, and Harestua).
Norbert Glatthor, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 17, 2849–2871, https://doi.org/10.5194/amt-17-2849-2024, https://doi.org/10.5194/amt-17-2849-2024, 2024
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We present global atmospheric methane (CH4) and nitrous oxide (N2O) distributions retrieved from measurements of the MIPAS instrument on board the Environmental Satellite (Envisat) during 2002 to 2012. Monitoring of these gases is of scientific interest because both of them are strong greenhouse gases. We analyze the latest, improved version of calibrated MIPAS measurements. Further, we apply a new retrieval scheme leading to an improved CH4 and N2O data product .
Matthieu Dogniaux, Joannes D. Maasakkers, Daniel J. Varon, and Ilse Aben
Atmos. Meas. Tech., 17, 2777–2787, https://doi.org/10.5194/amt-17-2777-2024, https://doi.org/10.5194/amt-17-2777-2024, 2024
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We analyze Landsat 8 (L8) and Sentinel-2B (S-2B) observations of the 2022 Nord Stream 2 methane leak and show how challenging this case is for usual data analysis methods. We provide customized calibrations for this Nord Stream 2 case and assess that no firm conclusion can be drawn from L8 or S-2B single overpasses. However, if we opportunistically assume that L8 and S-2B results are independent, we find an averaged L8 and S-2B combined methane leak rate of 502 ± 464 t h−1.
Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob
Atmos. Meas. Tech., 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, https://doi.org/10.5194/amt-17-2625-2024, 2024
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Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.
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Short summary
Water vapour trend calculations with lidars require rigorous calibrations. Here, we improve water vapour lidar calibrations using GCOS Reference Upper Air Network (GRUAN) radiosondes and a new trajectory method. The trajectory method improved the lidar calibration and more consistently agreed with the radiosonde measurement compared to the traditional method. Using GRUAN radiosondes enabled the calculation, for the first time, of a complete uncertainty budget of the calibration constant.
Water vapour trend calculations with lidars require rigorous calibrations. Here, we improve...
