Articles | Volume 12, issue 1
https://doi.org/10.5194/amt-12-371-2019
© 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-12-371-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Jan 2019
Research article |
| 18 Jan 2019
| 18 Jan 2019
The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) version 2: algorithm evolution, dataset description and performance improvements
Elisa Castelli
CORRESPONDING AUTHOR
Instituto di Scienze dell'Atmosfera e del Clima, ISAC-CNR, Via
Gobetti 101, 40129 Bologna, Italy
Enzo Papandrea
Serco s.p.a., Via Sciadonna
24–26, 00044 Frascati, Italy
Instituto di Scienze dell'Atmosfera e del Clima, ISAC-CNR, Via
Gobetti 101, 40129 Bologna, Italy
Alessio Di Roma
Dipartimento di Fisica e Astronomia,
DIFA, Universita' di Bologna, Viale Berti Pichat 6/2, 40127, Bologna, Italy
Bianca Maria Dinelli
Instituto di Scienze dell'Atmosfera e del Clima, ISAC-CNR, Via
Gobetti 101, 40129 Bologna, Italy
Stefano Casadio
Serco s.p.a., Via Sciadonna
24–26, 00044 Frascati, Italy
Bojan Bojkov
EUMETSAT, Eumetsat Allee 1, 64295 Darmstadt, Germany
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The level-2 v8 database from the measurements of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), aboard the European Space Agency Envisat satellite, containing atmospheric fields of pressure, temperature, and volume mixing ratio of 21 trace gases, is described in this paper. The database covers all the measurements acquired by MIPAS (from July 2002 to April 2012). The number of species included makes it of particular importance for the studies of stratospheric chemistry.
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Marc Schröder, Maarit Lockhoff, Frank Fell, John Forsythe, Tim Trent, Ralf Bennartz, Eva Borbas, Michael G. Bosilovich, Elisa Castelli, Hans Hersbach, Misako Kachi, Shinya Kobayashi, E. Robert Kursinski, Diego Loyola, Carl Mears, Rene Preusker, William B. Rossow, and Suranjana Saha
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MIPAS is a satellite-borne limb emission sounder. The algorithm used to infer atmospheric composition from its measurements exploits the assumption that the atmosphere is horizontally homogeneous. This assumption can cause significant errors. We use synthetic observations to quantify these errors. Furthermore we show that the inclusion of any kind of horizontal variability model improves all the retrieval targets and that the two-dimensional approach implies the smallest errors.
Ugo Cortesi, Samuele Del Bianco, Simone Ceccherini, Marco Gai, Bianca Maria Dinelli, Elisa Castelli, Hermann Oelhaf, Wolfgang Woiwode, Michael Höpfner, and Daniel Gerber
Atmos. Meas. Tech., 9, 2267–2289, https://doi.org/10.5194/amt-9-2267-2016, https://doi.org/10.5194/amt-9-2267-2016, 2016
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Pierre Gramme, Cedric Busschots, Emmanuel Dekemper, Didier Pieroux, Noel C. Baker, Stefano Casadio, Anna Maria lannarelli, Nicola Ferrante, Annalisa Di Bernardino, Paolo Pettinari, Elisa Castelli, Luca di Liberto, and Francesco Cairo
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We present a new remote sensing instrument using hyperspectral imaging to observe the variability in space and time of the nitrogen dioxide concentration. We also show the results of its validation campaign in a challenging urban setting in Rome, showing very good agreement with two reference instruments. Having an imaging instrument rather than the currently state-of-the-art unidirectional spectrometers brings promising capability in the context of satellite products validation.
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Piera Raspollini, Enrico Arnone, Flavio Barbara, Massimo Bianchini, Bruno Carli, Simone Ceccherini, Martyn P. Chipperfield, Angelika Dehn, Stefano Della Fera, Bianca Maria Dinelli, Anu Dudhia, Jean-Marie Flaud, Marco Gai, Michael Kiefer, Manuel López-Puertas, David P. Moore, Alessandro Piro, John J. Remedios, Marco Ridolfi, Harjinder Sembhi, Luca Sgheri, and Nicola Zoppetti
Atmos. Meas. Tech., 15, 1871–1901, https://doi.org/10.5194/amt-15-1871-2022, https://doi.org/10.5194/amt-15-1871-2022, 2022
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The MIPAS instrument onboard the ENVISAT satellite provided 10 years of measurements of the atmospheric emission al limb that allow for the retrieval of latitude- and altitude-resolved atmospheric composition. We describe the improvements implemented in the retrieval algorithm used for the full mission reanalysis, which allows for the generation of the global distributions of 21 atmospheric constituents plus temperature with increased accuracy with respect to previously generated data.
Bianca Maria Dinelli, Piera Raspollini, Marco Gai, Luca Sgheri, Marco Ridolfi, Simone Ceccherini, Flavio Barbara, Nicola Zoppetti, Elisa Castelli, Enzo Papandrea, Paolo Pettinari, Angelika Dehn, Anu Dudhia, Michael Kiefer, Alessandro Piro, Jean-Marie Flaud, Manuel López-Puertas, David Moore, John Remedios, and Massimo Bianchini
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The level-2 v8 database from the measurements of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), aboard the European Space Agency Envisat satellite, containing atmospheric fields of pressure, temperature, and volume mixing ratio of 21 trace gases, is described in this paper. The database covers all the measurements acquired by MIPAS (from July 2002 to April 2012). The number of species included makes it of particular importance for the studies of stratospheric chemistry.
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Phosgene (COCl2) is a toxic gas whose presence is a consequence of human activity. Besides its direct injection in the troposphere, stratospheric COCl2 is produced from the decomposition of CCl4, an anthropogenic gas regulated by the Montreal Protocol. As a consequence, COCl2 negative trends characterize the lower and part of the middle stratosphere. However, we find positive trends in the upper troposphere, demonstrating the non-negligible role of other Cl-containing species not yet regulated.
Henri Diémoz, Anna Maria Siani, Stefano Casadio, Anna Maria Iannarelli, Giuseppe Rocco Casale, Vladimir Savastiouk, Alexander Cede, Martin Tiefengraber, and Moritz Müller
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A 20-year (1996–2017) record of nitrogen dioxide column densities collected in Rome by a Brewer spectrophotometer is presented, together with the novel algorithm employed to re-evaluate the series. The high quality of the data is demonstrated by comparison with reference instrumentation, including a co-located Pandora spectrometer. The data can be used for satellite validation and identification of NO2 trends. The method can be replicated on other instruments of the international Brewer network.
Enzo Papandrea, Stefano Casadio, Elisa Castelli, Bianca Maria Dinelli, and Mario Marcello Miglietta
Atmos. Meas. Tech., 12, 6683–6693, https://doi.org/10.5194/amt-12-6683-2019, https://doi.org/10.5194/amt-12-6683-2019, 2019
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Short summary
Lee waves have been detected in clear-sky conditions over the Mediterranean Sea using the total column water vapour (TCWV) fields. The products were generated applying the Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) retrieval algorithm to the thermal infrared measurements of the Along Track Scanning Radiometer (ATSR) instrument series. A subset of the occurrences has been compared with both independent observations and model simulations.
Luca Brocca, Paolo Filippucci, Sebastian Hahn, Luca Ciabatta, Christian Massari, Stefania Camici, Lothar Schüller, Bojan Bojkov, and Wolfgang Wagner
Earth Syst. Sci. Data, 11, 1583–1601, https://doi.org/10.5194/essd-11-1583-2019, https://doi.org/10.5194/essd-11-1583-2019, 2019
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SM2RAIN–ASCAT is a new 12-year (2007–2018) global-scale rainfall dataset obtained by applying the SM2RAIN algorithm to ASCAT soil moisture data. The dataset has a spatiotemporal sampling resolution of 12.5 km and 1 d. Results show that the new dataset performs particularly well in Africa and South America, i.e. in the continents in which ground observations are scarce and the need for satellite rainfall data is high. SM2RAIN–ASCAT is available at http://doi.org/10.5281/zenodo.340556.
Stefan Lossow, Farahnaz Khosrawi, Michael Kiefer, Kaley A. Walker, Jean-Loup Bertaux, Laurent Blanot, James M. Russell, Ellis E. Remsberg, John C. Gille, Takafumi Sugita, Christopher E. Sioris, Bianca M. Dinelli, Enzo Papandrea, Piera Raspollini, Maya García-Comas, Gabriele P. Stiller, Thomas von Clarmann, Anu Dudhia, William G. Read, Gerald E. Nedoluha, Robert P. Damadeo, Joseph M. Zawodny, Katja Weigel, Alexei Rozanov, Faiza Azam, Klaus Bramstedt, Stefan Noël, John P. Burrows, Hideo Sagawa, Yasuko Kasai, Joachim Urban, Patrick Eriksson, Donal P. Murtagh, Mark E. Hervig, Charlotta Högberg, Dale F. Hurst, and Karen H. Rosenlof
Atmos. Meas. Tech., 12, 2693–2732, https://doi.org/10.5194/amt-12-2693-2019, https://doi.org/10.5194/amt-12-2693-2019, 2019
Norbert Glatthor, Thomas von Clarmann, Gabriele P. Stiller, Michael Kiefer, Alexandra Laeng, Bianca M. Dinelli, Gerald Wetzel, and Johannes Orphal
Atmos. Meas. Tech., 11, 4707–4723, https://doi.org/10.5194/amt-11-4707-2018, https://doi.org/10.5194/amt-11-4707-2018, 2018
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We report differences in ozone retrievals in channels A and AB of the space-borne Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which amount to up to 8 %. We provide strong evidence that the bias is caused by inconsistencies in different spectroscopic databases (MIPAS, HITRAN, GEISA). We show that a major part of the differences can be attributed to inconsistent air-broadening coefficients of the ozone lines contained in the databases.
Marc Schröder, Maarit Lockhoff, Frank Fell, John Forsythe, Tim Trent, Ralf Bennartz, Eva Borbas, Michael G. Bosilovich, Elisa Castelli, Hans Hersbach, Misako Kachi, Shinya Kobayashi, E. Robert Kursinski, Diego Loyola, Carl Mears, Rene Preusker, William B. Rossow, and Suranjana Saha
Earth Syst. Sci. Data, 10, 1093–1117, https://doi.org/10.5194/essd-10-1093-2018, https://doi.org/10.5194/essd-10-1093-2018, 2018
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This publication presents results achieved within the GEWEX Water Vapor Assessment (G-VAP). An overview of available water vapour data records based on satellite observations and reanalysis is given. If a minimum temporal coverage of 10 years is applied, 22 data records remain. These form the G-VAP data archive, which contains total column water vapour, specific humidity profiles and temperature profiles. The G-VAP data archive is designed to ease intercomparison and climate model evaluation.
Gerald E. Nedoluha, Michael Kiefer, Stefan Lossow, R. Michael Gomez, Niklaus Kämpfer, Martin Lainer, Peter Forkman, Ole Martin Christensen, Jung Jin Oh, Paul Hartogh, John Anderson, Klaus Bramstedt, Bianca M. Dinelli, Maya Garcia-Comas, Mark Hervig, Donal Murtagh, Piera Raspollini, William G. Read, Karen Rosenlof, Gabriele P. Stiller, and Kaley A. Walker
Atmos. Chem. Phys., 17, 14543–14558, https://doi.org/10.5194/acp-17-14543-2017, https://doi.org/10.5194/acp-17-14543-2017, 2017
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As part of the second SPARC (Stratosphere–troposphere Processes And their Role in Climate) water vapor assessment (WAVAS-II), we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. In the lower mesosphere, we quantify instrumental differences in the observed trends and annual variations at six sites. We then present a range of observed trends in water vapor over the past 20 years.
Alexandra Laeng, Thomas von Clarmann, Gabriele Stiller, Bianca Maria Dinelli, Anu Dudhia, Piera Raspollini, Norbert Glatthor, Udo Grabowski, Viktoria Sofieva, Lucien Froidevaux, Kaley A. Walker, and Claus Zehner
Atmos. Meas. Tech., 10, 1511–1518, https://doi.org/10.5194/amt-10-1511-2017, https://doi.org/10.5194/amt-10-1511-2017, 2017
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A MIPAS instrument was flown in 2002–2012 on the Envisat satellite and measured atmospheric composition. There exist four processors retrieving atmospheric profiles from MIPAS spectra. We performed a mathematically clean merging of 2007–2008 datasets of ozone from these four processors. The merged product was compared with ozone datasets from ACE-FTS and MLS instruments. The advantages and the shortcomings of this merged product are discussed.
Ralf Bennartz, Heidrun Höschen, Bruno Picard, Marc Schröder, Martin Stengel, Oliver Sus, Bojan Bojkov, Stefano Casadio, Hannes Diedrich, Salomon Eliasson, Frank Fell, Jürgen Fischer, Rainer Hollmann, Rene Preusker, and Ulrika Willén
Atmos. Meas. Tech., 10, 1387–1402, https://doi.org/10.5194/amt-10-1387-2017, https://doi.org/10.5194/amt-10-1387-2017, 2017
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The microwave radiometers (MWR) on board ERS-1, ERS-2, and Envisat provide a continuous time series of brightness temperature observations between 1991 and 2012. Here we report on a new total column water vapour (TCWV) and wet tropospheric correction (WTC) dataset that builds on this time series. The dataset is publicly available under doi:10.5676/DWD_EMIR/V001.
Stefan Lossow, Farahnaz Khosrawi, Gerald E. Nedoluha, Faiza Azam, Klaus Bramstedt, John. P. Burrows, Bianca M. Dinelli, Patrick Eriksson, Patrick J. Espy, Maya García-Comas, John C. Gille, Michael Kiefer, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Gabriele P. Stiller, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 10, 1111–1137, https://doi.org/10.5194/amt-10-1111-2017, https://doi.org/10.5194/amt-10-1111-2017, 2017
Massimo Carlotti, Bianca Maria Dinelli, Giada Innocenti, and Luca Palchetti
Atmos. Meas. Tech., 9, 5853–5867, https://doi.org/10.5194/amt-9-5853-2016, https://doi.org/10.5194/amt-9-5853-2016, 2016
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We introduce a strategy for the measurement of CO2 in the stratosphere. We use an orbiting limb sounder to measure both the thermal infrared (TIR) and far-infrared (FIR) atmospheric emissions. The rotational transitions of O2 in the FIR are exploited to derive the temperature and pressure fields that are needed to retrieve the CO2 from its spectrum in the TIR. The proposed experiment can determine two-dimensional distributions of the CO2 with precision of 1 ppm at altitudes between 10 and 50 km.
Elisa Castelli, Marco Ridolfi, Massimo Carlotti, Björn-Martin Sinnhuber, Oliver Kirner, Michael Kiefer, and Bianca Maria Dinelli
Atmos. Meas. Tech., 9, 5499–5508, https://doi.org/10.5194/amt-9-5499-2016, https://doi.org/10.5194/amt-9-5499-2016, 2016
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MIPAS is a satellite-borne limb emission sounder. The algorithm used to infer atmospheric composition from its measurements exploits the assumption that the atmosphere is horizontally homogeneous. This assumption can cause significant errors. We use synthetic observations to quantify these errors. Furthermore we show that the inclusion of any kind of horizontal variability model improves all the retrieval targets and that the two-dimensional approach implies the smallest errors.
Massimo Valeri, Massimo Carlotti, Jean-Marie Flaud, Piera Raspollini, Marco Ridolfi, and Bianca Maria Dinelli
Atmos. Meas. Tech., 9, 4655–4663, https://doi.org/10.5194/amt-9-4655-2016, https://doi.org/10.5194/amt-9-4655-2016, 2016
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Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) measurements have been analysed to measure the vertical distribution of phosgene (COCl2) in the UTLS using new spectroscopic data. To highlight its seasonal and latitudinal variability, MIPAS measurements of 2 days/month during 2008 have been analysed. The results show a strong latitudinal variability of COCl2 with the largest VMR values observed in the tropical regions. The seasonality is fairly low, apart from the polar regions.
Ugo Cortesi, Samuele Del Bianco, Simone Ceccherini, Marco Gai, Bianca Maria Dinelli, Elisa Castelli, Hermann Oelhaf, Wolfgang Woiwode, Michael Höpfner, and Daniel Gerber
Atmos. Meas. Tech., 9, 2267–2289, https://doi.org/10.5194/amt-9-2267-2016, https://doi.org/10.5194/amt-9-2267-2016, 2016
L. Di Liberto, R. Lehmann, I. Tritscher, F. Fierli, J. L. Mercer, M. Snels, G. Di Donfrancesco, T. Deshler, B. P. Luo, J-U. Grooß, E. Arnone, B. M. Dinelli, and F. Cairo
Atmos. Chem. Phys., 15, 6651–6665, https://doi.org/10.5194/acp-15-6651-2015, https://doi.org/10.5194/acp-15-6651-2015, 2015
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We investigated chemical and microphysical processes in the late winter Antarctic stratosphere, for the first time (to our knowledge) coupling a detailed microphysical box model to a chemistry model.
Model results have been compared with in situ and remote sensing measurements of particles along trajectories.
Our goal is to contribute to the most recent discussion of the relative role of PSC and liquid (background) aerosol in the ozone depletion.
B. Hassler, I. Petropavlovskikh, J. Staehelin, T. August, P. K. Bhartia, C. Clerbaux, D. Degenstein, M. De Mazière, B. M. Dinelli, A. Dudhia, G. Dufour, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, J. Granville, N. R. P. Harris, K. Hoppel, D. Hubert, Y. Kasai, M. J. Kurylo, E. Kyrölä, J.-C. Lambert, P. F. Levelt, C. T. McElroy, R. D. McPeters, R. Munro, H. Nakajima, A. Parrish, P. Raspollini, E. E. Remsberg, K. H. Rosenlof, A. Rozanov, T. Sano, Y. Sasano, M. Shiotani, H. G. J. Smit, G. Stiller, J. Tamminen, D. W. Tarasick, J. Urban, R. J. van der A, J. P. Veefkind, C. Vigouroux, T. von Clarmann, C. von Savigny, K. A. Walker, M. Weber, J. Wild, and J. M. Zawodny
Atmos. Meas. Tech., 7, 1395–1427, https://doi.org/10.5194/amt-7-1395-2014, https://doi.org/10.5194/amt-7-1395-2014, 2014
E. Castelli, B. M. Dinelli, S. Del Bianco, D. Gerber, B. P. Moyna, R. Siddans, B. J. Kerridge, and U. Cortesi
Atmos. Meas. Tech., 6, 2683–2701, https://doi.org/10.5194/amt-6-2683-2013, https://doi.org/10.5194/amt-6-2683-2013, 2013
P. Raspollini, B. Carli, M. Carlotti, S. Ceccherini, A. Dehn, B. M. Dinelli, A. Dudhia, J.-M. Flaud, M. López-Puertas, F. Niro, J. J. Remedios, M. Ridolfi, H. Sembhi, L. Sgheri, and T. von Clarmann
Atmos. Meas. Tech., 6, 2419–2439, https://doi.org/10.5194/amt-6-2419-2013, https://doi.org/10.5194/amt-6-2419-2013, 2013
M. Carlotti, E. Arnone, E. Castelli, B. M. Dinelli, and E. Papandrea
Atmos. Meas. Tech., 6, 419–429, https://doi.org/10.5194/amt-6-419-2013, https://doi.org/10.5194/amt-6-419-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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
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
A study of measurement scenarios for the future CO2M mission: avoidance of detector saturation and the impact on XCO2 retrievals
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
CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
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.
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-3857, https://doi.org/10.5194/egusphere-2024-3857, 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. It impacts coverage and precision, both 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 the CO2 precision.
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.
Anna Vaughan, Gonzalo Mateo-García, Luis Gómez-Chova, Vít Růžička, Luis Guanter, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 2583–2593, https://doi.org/10.5194/amt-17-2583-2024, https://doi.org/10.5194/amt-17-2583-2024, 2024
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Methane is a potent greenhouse gas that has been responsible for around 25 % of global warming since the industrial revolution. Consequently identifying and mitigating methane emissions comprise an important step in combating the climate crisis. We develop a new deep learning model to automatically detect methane plumes from satellite images and demonstrate that this can be applied to monitor large methane emissions resulting from the oil and gas industry.
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Short summary
The total column water vapour (TCWV) is a key atmospheric variable. The AIRWAVE (Advanced Infra-Red WAter Vapour Estimator) v1 algorithm was developed to retrieve TCWV from satellite measurements. Comparisons with independent TCWV show good agreement with an overall bias of 0.72 kg m−2 due to the polar and coastal regions. Here, we describe the AIRWAVEv2 dataset, which shows significant improvements with a global bias of 0.02 kg m−2. This dataset was used to produce a climatology from 1991 to 2012.
The total column water vapour (TCWV) is a key atmospheric variable. The AIRWAVE (Advanced...
