Articles | Volume 15, issue 22
https://doi.org/10.5194/amt-15-6585-2022
© Author(s) 2022. 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-15-6585-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Nov 2022
Research article |
| 17 Nov 2022
| 17 Nov 2022
Evaluation of the methane full-physics retrieval applied to TROPOMI ocean sun glint measurements
Earth Science Group, SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Tobias Borsdorff
Earth Science Group, SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Mari C. Martinez-Velarte
Earth Science Group, SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Andre Butz
Institute of Environmental Physics, University of Heidelberg, Heidelberg, Germany
Heidelberg Center for the Environment, University of Heidelberg, Heidelberg, Germany
Otto P. Hasekamp
Earth Science Group, SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Lianghai Wu
Earth Science Group, SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Jochen Landgraf
Earth Science Group, SRON Netherlands Institute for Space Research, Leiden, the Netherlands
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Atmos. Chem. Phys., 23, 8039–8057, https://doi.org/10.5194/acp-23-8039-2023, https://doi.org/10.5194/acp-23-8039-2023, 2023
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Daniel J. Varon, Daniel J. Jacob, Benjamin Hmiel, Ritesh Gautam, David R. Lyon, Mark Omara, Melissa Sulprizio, Lu Shen, Drew Pendergrass, Hannah Nesser, Zhen Qu, Zachary R. Barkley, Natasha L. Miles, Scott J. Richardson, Kenneth J. Davis, Sudhanshu Pandey, Xiao Lu, Alba Lorente, Tobias Borsdorff, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 7503–7520, https://doi.org/10.5194/acp-23-7503-2023, https://doi.org/10.5194/acp-23-7503-2023, 2023
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Atmos. Chem. Phys., 23, 5945–5967, https://doi.org/10.5194/acp-23-5945-2023, https://doi.org/10.5194/acp-23-5945-2023, 2023
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We quantify methane emissions from individual countries in the Middle East and North Africa by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We show that the ability to simply relate oil/gas emissions to activity metrics is compromised by stochastic nature of local infrastructure and management practices. We find that the industry target for oil/gas methane intensity is achievable through associated gas capture, modern infrastructure, and centralized operations.
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Atmos. Meas. Tech., 16, 1597–1608, https://doi.org/10.5194/amt-16-1597-2023, https://doi.org/10.5194/amt-16-1597-2023, 2023
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Xueying Yu, Dylan B. Millet, Daven K. Henze, Alexander J. Turner, Alba Lorente Delgado, A. Anthony Bloom, and Jianxiong Sheng
Atmos. Chem. Phys., 23, 3325–3346, https://doi.org/10.5194/acp-23-3325-2023, https://doi.org/10.5194/acp-23-3325-2023, 2023
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Zichong Chen, Daniel J. Jacob, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Elise Penn, and Xueying Yu
Atmos. Chem. Phys., 22, 10809–10826, https://doi.org/10.5194/acp-22-10809-2022, https://doi.org/10.5194/acp-22-10809-2022, 2022
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We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current
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Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
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We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Daniel J. Varon, Daniel J. Jacob, Melissa Sulprizio, Lucas A. Estrada, William B. Downs, Lu Shen, Sarah E. Hancock, Hannah Nesser, Zhen Qu, Elise Penn, Zichong Chen, Xiao Lu, Alba Lorente, Ashutosh Tewari, and Cynthia A. Randles
Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022, https://doi.org/10.5194/gmd-15-5787-2022, 2022
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Reducing atmospheric methane emissions is critical to slow near-term climate change. Globally surveying satellite instruments like the TROPOspheric Monitoring Instrument (TROPOMI) have unique capabilities for monitoring atmospheric methane around the world. Here we present a user-friendly cloud-computing tool that enables researchers and stakeholders to quantify methane emissions across user-selected regions of interest using TROPOMI satellite observations.
Jonas Hachmeister, Oliver Schneising, Michael Buchwitz, Alba Lorente, Tobias Borsdorff, John P. Burrows, Justus Notholt, and Matthias Buschmann
Atmos. Meas. Tech., 15, 4063–4074, https://doi.org/10.5194/amt-15-4063-2022, https://doi.org/10.5194/amt-15-4063-2022, 2022
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Sentinel-5P trace gas retrievals rely on elevation data in their calculations. Outdated or inaccurate data can lead to significant errors in e.g. dry-air mole fractions of methane (XCH4). We show that the use of inadequate elevation data leads to strong XCH4 anomalies in Greenland. Similar problems can be expected for other regions with inaccurate elevation data. However, we expect these to be more localized. We show that updating elevation data used in the retrieval solves this issue.
Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Alba Lorente, Franziska Aemisegger, David Noone, Dean Henze, Rigel Kivi, and Jochen Landgraf
Atmos. Meas. Tech., 15, 2251–2275, https://doi.org/10.5194/amt-15-2251-2022, https://doi.org/10.5194/amt-15-2251-2022, 2022
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Qiansi Tu, Frank Hase, Matthias Schneider, Omaira García, Thomas Blumenstock, Tobias Borsdorff, Matthias Frey, Farahnaz Khosrawi, Alba Lorente, Carlos Alberti, Juan J. Bustos, André Butz, Virgilio Carreño, Emilio Cuevas, Roger Curcoll, Christopher J. Diekmann, Darko Dubravica, Benjamin Ertl, Carme Estruch, Sergio Fabián León-Luis, Carlos Marrero, Josep-Anton Morgui, Ramón Ramos, Christian Scharun, Carsten Schneider, Eliezer Sepúlveda, Carlos Toledano, and Carlos Torres
Atmos. Chem. Phys., 22, 295–317, https://doi.org/10.5194/acp-22-295-2022, https://doi.org/10.5194/acp-22-295-2022, 2022
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We use different methane ground- and space-based remote sensing data sets for investigating the emission strength of three waste disposal sites close to Madrid. We present a method that uses wind-assigned anomalies for deriving emission strengths from satellite data and estimate their uncertainty to 9–14 %. The emission strengths estimated from the remote sensing data sets are significantly larger than the values published in the official register.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
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This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
Zhen Qu, Daniel J. Jacob, Lu Shen, Xiao Lu, Yuzhong Zhang, Tia R. Scarpelli, Hannah Nesser, Melissa P. Sulprizio, Joannes D. Maasakkers, A. Anthony Bloom, John R. Worden, Robert J. Parker, and Alba L. Delgado
Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, https://doi.org/10.5194/acp-21-14159-2021, 2021
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The recent launch of TROPOMI offers an unprecedented opportunity to quantify the methane budget from a top-down perspective. We use TROPOMI and the more mature GOSAT methane observations to estimate methane emissions and get consistent global budgets. However, TROPOMI shows biases over regions where surface albedo is small and provides less information for the coarse-resolution inversion due to the larger error correlations and spatial variations in the number of observations.
Jérôme Barré, Ilse Aben, Anna Agustí-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Peter Dueben, Richard Engelen, Antje Inness, Alba Lorente, Joe McNorton, Vincent-Henri Peuch, Gabor Radnoti, and Roberto Ribas
Atmos. Chem. Phys., 21, 5117–5136, https://doi.org/10.5194/acp-21-5117-2021, https://doi.org/10.5194/acp-21-5117-2021, 2021
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This study presents a new approach to the systematic global detection of anomalous local CH4 concentration anomalies caused by rapid changes in anthropogenic emission levels. The approach utilises both satellite measurements and model simulations, and applies novel data analysis techniques (such as filtering and classification) to automatically detect anomalous emissions from point sources and small areas, such as oil and gas drilling sites, pipelines and facility leaks.
Alba Lorente, Tobias Borsdorff, Andre Butz, Otto Hasekamp, Joost aan de Brugh, Andreas Schneider, Lianghai Wu, Frank Hase, Rigel Kivi, Debra Wunch, David F. Pollard, Kei Shiomi, Nicholas M. Deutscher, Voltaire A. Velazco, Coleen M. Roehl, Paul O. Wennberg, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, https://doi.org/10.5194/amt-14-665-2021, 2021
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TROPOMI aboard Sentinel-5P satellite provides methane (CH4) measurements with exceptional temporal and spatial resolution. The study describes a series of improvements developed to retrieve CH4 from TROPOMI. The updated CH4 product features (among others) a more accurate a posteriori correction derived independently of any reference data. The validation of the improved data product shows good agreement with ground-based and satellite measurements, which highlights the quality of the TROPOMI CH4.
Sudhanshu Pandey, Sander Houweling, Alba Lorente, Tobias Borsdorff, Maria Tsivlidou, A. Anthony Bloom, Benjamin Poulter, Zhen Zhang, and Ilse Aben
Biogeosciences, 18, 557–572, https://doi.org/10.5194/bg-18-557-2021, https://doi.org/10.5194/bg-18-557-2021, 2021
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We use atmospheric methane observations from the novel TROPOspheric Monitoring Instrument (TROPOMI; Sentinel-5p) to estimate methane emissions from South Sudan's wetlands. Our emission estimates are an order of magnitude larger than the estimate of process-based wetland models. We find that this underestimation by the models is likely due to their misrepresentation of the wetlands' inundation extent and temperature dependences.
Qiansi Tu, Frank Hase, Thomas Blumenstock, Rigel Kivi, Pauli Heikkinen, Mahesh Kumar Sha, Uwe Raffalski, Jochen Landgraf, Alba Lorente, Tobias Borsdorff, Huilin Chen, Florian Dietrich, and Jia Chen
Atmos. Meas. Tech., 13, 4751–4771, https://doi.org/10.5194/amt-13-4751-2020, https://doi.org/10.5194/amt-13-4751-2020, 2020
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Two COCCON instruments are used to observe multiyear greenhouse gases in boreal areas and are compared with the CAMS analysis and S5P satellite data. These three datasets predict greenhouse gas gradients with reasonable agreement. The results indicate that the COCCON instrument has the capability of measuring gradients on regional scales, and observations performed with the portable spectrometers can contribute to inferring sources and sinks and to validating spaceborne greenhouse gases.
Srijana Lama, Sander Houweling, K. Folkert Boersma, Henk Eskes, Ilse Aben, Hugo A. C. Denier van der Gon, Maarten C. Krol, Han Dolman, Tobias Borsdorff, and Alba Lorente
Atmos. Chem. Phys., 20, 10295–10310, https://doi.org/10.5194/acp-20-10295-2020, https://doi.org/10.5194/acp-20-10295-2020, 2020
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Rapid urbanization has increased the consumption of fossil fuel, contributing the degradation of urban air quality. Burning efficiency is a major factor determining the impact of fuel burning on the environment. We quantify the burning efficiency of fossil fuel use over six megacities using satellite remote sensing data. City governance can use these results to understand air pollution scenarios and to formulate effective air pollution control strategies.
Steven Compernolle, Tijl Verhoelst, Gaia Pinardi, José Granville, Daan Hubert, Arno Keppens, Sander Niemeijer, Bruno Rino, Alkis Bais, Steffen Beirle, Folkert Boersma, John P. Burrows, Isabelle De Smedt, Henk Eskes, Florence Goutail, François Hendrick, Alba Lorente, Andrea Pazmino, Ankie Piters, Enno Peters, Jean-Pierre Pommereau, Julia Remmers, Andreas Richter, Jos van Geffen, Michel Van Roozendael, Thomas Wagner, and Jean-Christopher Lambert
Atmos. Chem. Phys., 20, 8017–8045, https://doi.org/10.5194/acp-20-8017-2020, https://doi.org/10.5194/acp-20-8017-2020, 2020
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Tropospheric and stratospheric NO2 columns from the OMI QA4ECV NO2 satellite product are validated by comparison with ground-based measurements at 11 sites. The OMI stratospheric column has a small negative bias, and the OMI tropospheric column has a stronger negative bias relative to the ground-based data. Discrepancies are attributed to comparison errors (e.g. difference in horizontal smoothing) and measurement errors (e.g. clouds, aerosols, vertical smoothing and a priori profile assumptions).
Tobias Borsdorff, Joost aan de Brugh, Andreas Schneider, Alba Lorente, Manfred Birk, Georg Wagner, Rigel Kivi, Frank Hase, Dietrich G. Feist, Ralf Sussmann, Markus Rettinger, Debra Wunch, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 12, 5443–5455, https://doi.org/10.5194/amt-12-5443-2019, https://doi.org/10.5194/amt-12-5443-2019, 2019
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The study presents possible improvements of the TROPOMI CO dataset, which is a primary product of ESA's Sentinel-5P mission. We discuss the use of different molecular spectroscopic databases in the CO retrieval, the induced biases between TROPOMI CO and TCCON validation measurements, and the latitudinally dependent bias between TROPOMI CO and the CAMS-IFS model. Additionally, two methods for the stripe correction of single TROPOMI CO orbits are presented.
K. Folkert Boersma, Henk J. Eskes, Andreas Richter, Isabelle De Smedt, Alba Lorente, Steffen Beirle, Jos H. G. M. van Geffen, Marina Zara, Enno Peters, Michel Van Roozendael, Thomas Wagner, Joannes D. Maasakkers, Ronald J. van der A, Joanne Nightingale, Anne De Rudder, Hitoshi Irie, Gaia Pinardi, Jean-Christopher Lambert, and Steven C. Compernolle
Atmos. Meas. Tech., 11, 6651–6678, https://doi.org/10.5194/amt-11-6651-2018, https://doi.org/10.5194/amt-11-6651-2018, 2018
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This paper describes a new, improved data record of 22+ years of coherent nitrogen dioxide (NO2) pollution measurements from different satellite instruments. Our work helps to ensure that climate data are of sufficient quality to draw reliable conclusions and shape decisions. It shows how dedicated intercomparisons of retrieval sub-steps have led to improved NO2 measurements from the GOME, SCIAMACHY, GOME-2(A), and OMI sensors, and how quality assurance of the new data product is achieved.
Alba Lorente, K. Folkert Boersma, Piet Stammes, L. Gijsbert Tilstra, Andreas Richter, Huan Yu, Said Kharbouche, and Jan-Peter Muller
Atmos. Meas. Tech., 11, 4509–4529, https://doi.org/10.5194/amt-11-4509-2018, https://doi.org/10.5194/amt-11-4509-2018, 2018
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Light reflected by Earth’s surface is different in each direction: it appears brighter or darker in certain viewing directions. Currently this effect is not accounted for in satellite retrievals; thus surface reflectance climatologies and cloud fractions show an east-west bias across orbits (GOME2,OMI). The effect for NO2 measurements in partly cloudy scenes is substantial. We recommend that this effect in UV/Vis sensors coherently accounted for, and will be especially beneficial for TROPOMI.
Alba Lorente, K. Folkert Boersma, Huan Yu, Steffen Dörner, Andreas Hilboll, Andreas Richter, Mengyao Liu, Lok N. Lamsal, Michael Barkley, Isabelle De Smedt, Michel Van Roozendael, Yang Wang, Thomas Wagner, Steffen Beirle, Jin-Tai Lin, Nickolay Krotkov, Piet Stammes, Ping Wang, Henk J. Eskes, and Maarten Krol
Atmos. Meas. Tech., 10, 759–782, https://doi.org/10.5194/amt-10-759-2017, https://doi.org/10.5194/amt-10-759-2017, 2017
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Choices and assumptions made to represent the state of the atmosphere introduce an uncertainty of 42 % in the air mass factor calculation in trace gas satellite retrievals in polluted regions. The AMF strongly depends on the choice of a priori trace gas profile, surface albedo data set and the correction method to account for clouds and aerosols. We call for well-designed validation exercises focusing on situations when AMF structural uncertainty has the highest impact on satellite retrievals.
Aurélien Sicsik-Paré, Audrey Fortems-Cheiney, Isabelle Pison, Grégoire Broquet, Alvin Opler, Elise Potier, Adrien Martinez, Oliver Schneising, Michael Buchwitz, Joannes D. Maasakkers, Tobias Borsdorff, and Antoine Berchet
EGUsphere, https://doi.org/10.5194/egusphere-2025-2622, https://doi.org/10.5194/egusphere-2025-2622, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Assimilating satellite observations from TROPOMI provides top-down quantification of regional methane emissions. This study compares European emissions in 2019 estimated from the inversion of three TROPOMI datasets. We find inconsistencies in national budgets and spatial patterns, with no product clearly superior. We disentangle drivers of the differences, highlighting the impact of differences in coverage, observations and associated errors on the consistency of methane emission estimates.
Yusuf Bhatti, Duncan Watson-Parris, Leighton Regayre, Hailing Jia, David Neubauer, Ulas Im, Carl Svenhag, Nick Schutgens, Athanasios Tsikerdekis, Athanasios Nenes, Irfan Muhammed, Bastiaan van Diedenhoven, Ardit Arifi, Guangliang Fu, and Otto Hasekamp
EGUsphere, https://doi.org/10.5194/egusphere-2025-2848, https://doi.org/10.5194/egusphere-2025-2848, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Aerosols (small airborne particles) impact Earth's climate, but their extent is unknown. By running climate model simulations and emulating millions of additional variants with different settings, we found that natural emissions like sea spray and sulfur are key sources of uncertainty in climate predictions. Our work shows that understanding these natural processes better can help improve climate models and make future climate projections more accurate.
Andrew Gerald Barr, Jochen Landgraf, Mari Martinez-Velarte, Mihalis Vrekoussis, Ralf Sussmann, Isamu Morino, Kimberly Strong, Minqiang Zhou, Voltaire A. Velazco, Hirofumi Ohyama, Thorsten Warneke, Frank Hase, and Tobias Borsdorff
EGUsphere, https://doi.org/10.5194/egusphere-2024-3990, https://doi.org/10.5194/egusphere-2024-3990, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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In 2019 GOSAT-2 was launched, to realise the second in a series of satellites dedicated to measuring concentrations of greenhouse gases from space. The datasets obtained from GOSAT-2 are used in the Copernicus atmospheric services to monitor the climate, in light of the Paris Agreement. Over the five years the increase of CH4 and CO2 concentration in the atmosphere is clear. Here we present three robust datasets from GOSAT-2, including a novel machine learning approach to data quality filtering.
Zihao Yuan, Guangliang Fu, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp
EGUsphere, https://doi.org/10.5194/egusphere-2025-1488, https://doi.org/10.5194/egusphere-2025-1488, 2025
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This work develops an Neural-Network-based above cloud aerosol (ACA) detection and retrieval scheme for multi-angular polarimetric (MAP) instruments. On one year of PARASOL data, the retrieved aerosol properties (aerosol optical thickness, AOT, Angstrom Exponent, AE, and Single Scattering Albedo, SSA) agree well with adjacent clear-sky RemoTAP-PARASOL aerosol retrievals. The seasonal global pattern of ACA events and above cloud AOT are also within expectation.
Harikrishnan Charuvil Asokan, Jochen Landgraf, Pepijn Veefkind, Stijn Dellaert, and André Butz
EGUsphere, https://doi.org/10.5194/egusphere-2025-1071, https://doi.org/10.5194/egusphere-2025-1071, 2025
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Greenhouse gases like CO2 and CH4 drive climate change. Satellites enable monitoring of these emissions from space. Our simulations show that the upcoming TANGO mission can detect about 500 targets per 4-day cycle under clear skies, but cloud cover reduces detection. Integrating cloud forecasts into TANGO’s maneuvering boosts detections, highlighting its potential for improving global emission monitoring.
Eva-Marie Metz, Sanam Noreen Vardag, Sourish Basu, Martin Jung, and André Butz
Biogeosciences, 22, 555–584, https://doi.org/10.5194/bg-22-555-2025, https://doi.org/10.5194/bg-22-555-2025, 2025
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We estimate CO2 fluxes in semiarid southern Africa from 2009 to 2018 based on satellite CO2 measurements and atmospheric inverse modeling. By selecting process-based vegetation models, which agree with the satellite CO2 fluxes, we find that soil respiration mainly drives the seasonality, whereas photosynthesis substantially influences the interannual variability. Our study emphasizes the need for better representation of the response of semiarid ecosystems to soil rewetting in vegetation models.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, Ivar R. van der Velde, and Ilse Aben
Atmos. Chem. Phys., 25, 555–574, https://doi.org/10.5194/acp-25-555-2025, https://doi.org/10.5194/acp-25-555-2025, 2025
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The production of steel coincides with large emissions of greenhouse gases and air pollutants including carbon monoxide. European facilities are required to report their emissions, which are estimated using a variety of methods. We evaluate these estimates using carbon monoxide concentrations measured via satellite. We find generally good agreement between our values and those reported but also identify some uncertainties, showing that satellites can provide insights into these emissions.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
EGUsphere, https://doi.org/10.5194/egusphere-2024-3692, https://doi.org/10.5194/egusphere-2024-3692, 2025
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The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
Max Bechthold, Wolfram Barfuss, André Butz, Jannes Breier, Sara M. Constantino, Jobst Heitzig, Luana Schwarz, Sanam N. Vardag, and Jonathan F. Donges
EGUsphere, https://doi.org/10.5194/egusphere-2024-2924, https://doi.org/10.5194/egusphere-2024-2924, 2024
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Social norms are a major influence on human behaviour. In natural resource use models, norms are often included in a simplistic way leading to "black or white" sustainability outcomes. We find that a dynamic representation of norms, including social groups, determines more nuanced states of the environment in a stylized model of resource use, while also defining the success of attempts to manage the system, suggesting the importance of well representing both in coupled models.
Karolin Voss, Philip Holzbeck, Klaus Pfeilsticker, Ralph Kleinschek, Gerald Wetzel, Blanca Fuentes Andrade, Michael Höpfner, Jörn Ungermann, Björn-Martin Sinnhuber, and André Butz
Atmos. Meas. Tech., 17, 4507–4528, https://doi.org/10.5194/amt-17-4507-2024, https://doi.org/10.5194/amt-17-4507-2024, 2024
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A novel balloon-borne instrument for direct sun and solar occultation measurements of several UV–Vis absorbing gases (e.g. O3, NO2, BrO, IO, and HONO) is described. Its major design features and performance during two stratospheric deployments are discussed. From the measured overhead BrO concentration and a suitable photochemical correction, total stratospheric bromine is inferred to (17.5 ± 2.2) ppt in air masses which entered the stratosphere around early 2017 ± 1 year.
Brian Nathan, Joannes D. Maasakkers, Stijn Naus, Ritesh Gautam, Mark Omara, Daniel J. Varon, Melissa P. Sulprizio, Lucas A. Estrada, Alba Lorente, Tobias Borsdorff, Robert J. Parker, and Ilse Aben
Atmos. Chem. Phys., 24, 6845–6863, https://doi.org/10.5194/acp-24-6845-2024, https://doi.org/10.5194/acp-24-6845-2024, 2024
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Venezuela's Lake Maracaibo region is notoriously hard to observe from space and features intensive oil exploitation, although production has strongly decreased in recent years. We estimate methane emissions using 2018–2020 TROPOMI satellite observations with national and regional transport models. Despite the production decrease, we find relatively constant emissions from Lake Maracaibo between 2018 and 2020, indicating that there could be large emissions from abandoned infrastructure.
Zihao Yuan, Guangliang Fu, Bastiaan van Diedenhoven, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp
Atmos. Meas. Tech., 17, 2595–2610, https://doi.org/10.5194/amt-17-2595-2024, https://doi.org/10.5194/amt-17-2595-2024, 2024
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Currently, aerosol properties from spaceborne multi-angle polarimeter (MAP) instruments can only be retrieved in cloud-free areas or in areas where an aerosol layer is located above a cloud. Therefore, it is important to be able to identify cloud-free pixels for which an aerosol retrieval algorithm can provide meaningful output. The developed neural network cloud screening demonstrates that cloud masking for MAP aerosol retrieval can be based on the MAP measurements themselves.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Alba Lorente, Zichong Chen, Xiao Lu, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Margaux Winter, Shuang Ma, A. Anthony Bloom, John R. Worden, Robert N. Stavins, and Cynthia A. Randles
Atmos. Chem. Phys., 24, 5069–5091, https://doi.org/10.5194/acp-24-5069-2024, https://doi.org/10.5194/acp-24-5069-2024, 2024
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We quantify 2019 methane emissions in the contiguous US (CONUS) at a ≈ 25 km × 25 km resolution using satellite methane observations. We find a 13 % upward correction to the 2023 US Environmental Protection Agency (EPA) Greenhouse Gas Emissions Inventory (GHGI) for 2019, with large corrections to individual states, urban areas, and landfills. This may present a challenge for US climate policies and goals, many of which target significant reductions in methane emissions.
Marvin Knapp, Ralph Kleinschek, Sanam N. Vardag, Felix Külheim, Helge Haveresch, Moritz Sindram, Tim Siegel, Bruno Burger, and André Butz
Atmos. Meas. Tech., 17, 2257–2275, https://doi.org/10.5194/amt-17-2257-2024, https://doi.org/10.5194/amt-17-2257-2024, 2024
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Imaging carbon dioxide (CO2) plumes of anthropogenic sources from planes and satellites has proven valuable for detecting emitters and monitoring climate mitigation efforts. We present the first images of CO2 plumes taken with a ground-based spectral camera, observing a coal-fired power plant as a validation target. We develop a technique to find the source emission strength with an hourly resolution, which reasonably agrees with the expected emissions under favorable conditions.
Otto Hasekamp, Pavel Litvinov, Guangliang Fu, Cheng Chen, and Oleg Dubovik
Atmos. Meas. Tech., 17, 1497–1525, https://doi.org/10.5194/amt-17-1497-2024, https://doi.org/10.5194/amt-17-1497-2024, 2024
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Aerosols are particles in the atmosphere that cool the climate by reflecting and absorbing sunlight (direct effect) and changing cloud properties (indirect effect). The scale of aerosol cooling is uncertain, hampering accurate climate predictions. We compare two algorithms for the retrieval of aerosol properties from multi-angle polarimetric measurements: Generalized Retrieval of Atmosphere and Surface Properties (GRASP) and Remote sensing of Trace gas and Aerosol Products (RemoTAP).
Astrid Müller, Hiroshi Tanimoto, Takafumi Sugita, Prabir K. Patra, Shin-ichiro Nakaoka, Toshinobu Machida, Isamu Morino, André Butz, and Kei Shiomi
Atmos. Meas. Tech., 17, 1297–1316, https://doi.org/10.5194/amt-17-1297-2024, https://doi.org/10.5194/amt-17-1297-2024, 2024
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Satellite CH4 observations with high accuracy are needed to understand changes in atmospheric CH4 concentrations. But over oceans, reference data are limited. We combine various ship and aircraft observations with the help of atmospheric chemistry models to derive observation-based column-averaged mixing ratios of CH4 (obs. XCH4). We discuss three different approaches and demonstrate the applicability of the new reference dataset for carbon cycle studies and satellite evaluation.
Tobias D. Schmitt, Jonas Kuhn, Ralph Kleinschek, Benedikt A. Löw, Stefan Schmitt, William Cranton, Martina Schmidt, Sanam N. Vardag, Frank Hase, David W. T. Griffith, and André Butz
Atmos. Meas. Tech., 16, 6097–6110, https://doi.org/10.5194/amt-16-6097-2023, https://doi.org/10.5194/amt-16-6097-2023, 2023
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Our new observatory measures greenhouse gas concentrations of carbon dioxide (CO2) and methane (CH4) along a 1.55 km long light path over the city of Heidelberg, Germany. We compared our measurements with measurements that were taken at a single point at one end of our path. The two mostly agreed but show a significant difference for CO2 with certain wind directions. This is important when using greenhouse gas concentration measurements to observe greenhouse gas emissions of cities.
Zihan Zhang, Guangliang Fu, and Otto Hasekamp
Atmos. Meas. Tech., 16, 6051–6063, https://doi.org/10.5194/amt-16-6051-2023, https://doi.org/10.5194/amt-16-6051-2023, 2023
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In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm is extended with a bi-directional reflection distribution function for snow surfaces. The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover > 75 %.
Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew M. Sayer, Xiaoguang Xu, J. Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 5863–5881, https://doi.org/10.5194/amt-16-5863-2023, https://doi.org/10.5194/amt-16-5863-2023, 2023
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This study evaluated the retrievability and uncertainty of aerosol and ocean properties from PACE's HARP2 instrument using enhanced neural network models with the FastMAPOL algorithm. A cascading retrieval method is developed to improve retrieval performance. A global set of simulated HARP2 data is generated and used for uncertainty evaluations. The performance assessment demonstrates that the FastMAPOL algorithm is a viable approach for operational application to HARP2 data after PACE launch.
Benedikt A. Löw, Ralph Kleinschek, Vincent Enders, Stanley P. Sander, Thomas J. Pongetti, Tobias D. Schmitt, Frank Hase, Julian Kostinek, and André Butz
Atmos. Meas. Tech., 16, 5125–5144, https://doi.org/10.5194/amt-16-5125-2023, https://doi.org/10.5194/amt-16-5125-2023, 2023
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We developed a portable spectrometer (EM27/SCA) that remotely measures greenhouse gases in the lower atmosphere above a target region. The measurements can deliver insights into local emission patterns. To evaluate its performance, we set up the EM27/SCA above the Los Angeles Basin side by side with a similar non-portable instrument (CLARS-FTS). The precision is promising and the measurements are consistent with CLARS-FTS. In the future, we need to account for light scattering.
Berend J. Schuit, Joannes D. Maasakkers, Pieter Bijl, Gourav Mahapatra, Anne-Wil van den Berg, Sudhanshu Pandey, Alba Lorente, Tobias Borsdorff, Sander Houweling, Daniel J. Varon, Jason McKeever, Dylan Jervis, Marianne Girard, Itziar Irakulis-Loitxate, Javier Gorroño, Luis Guanter, Daniel H. Cusworth, and Ilse Aben
Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023, https://doi.org/10.5194/acp-23-9071-2023, 2023
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Using two machine learning models, which were trained on TROPOMI methane satellite data, we detect 2974 methane plumes, so-called super-emitters, in 2021. We detect methane emissions globally related to urban areas or landfills, coal mining, and oil and gas production. Using our monitoring system, we identify 94 regions with frequent emissions. For 12 locations, we target high-resolution satellite instruments to enlarge and identify the exact infrastructure responsible for the emissions.
Athanasios Tsikerdekis, Otto P. Hasekamp, Nick A. J. Schutgens, and Qirui Zhong
Atmos. Chem. Phys., 23, 9495–9524, https://doi.org/10.5194/acp-23-9495-2023, https://doi.org/10.5194/acp-23-9495-2023, 2023
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Aerosols are tiny particles of different substances (species) that can be emitted into the atmosphere by natural processes or by anthropogenic activities. However, the actual aerosol emission amount per species is highly uncertain. Thus in this work we correct the aerosol emissions used to drive a global aerosol–climate model using satellite observations through a process called data assimilation. These more accurate aerosol emissions can lead to a more accurate weather and climate prediction.
Manu Goudar, Juliëtte C. S. Anema, Rajesh Kumar, Tobias Borsdorff, and Jochen Landgraf
Geosci. Model Dev., 16, 4835–4852, https://doi.org/10.5194/gmd-16-4835-2023, https://doi.org/10.5194/gmd-16-4835-2023, 2023
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A framework was developed to automatically detect plumes and compute emission estimates with cross-sectional flux method (CFM) for biomass burning events in TROPOMI CO datasets using Visible Infrared Imaging Radiometer Suite active fire data. The emissions were more reliable when changing plume height in downwind direction was used instead of constant injection height. The CFM had uncertainty even when the meteorological conditions were accurate; thus there is a need for better inversion models.
Nicholas Balasus, Daniel J. Jacob, Alba Lorente, Joannes D. Maasakkers, Robert J. Parker, Hartmut Boesch, Zichong Chen, Makoto M. Kelp, Hannah Nesser, and Daniel J. Varon
Atmos. Meas. Tech., 16, 3787–3807, https://doi.org/10.5194/amt-16-3787-2023, https://doi.org/10.5194/amt-16-3787-2023, 2023
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We use machine learning to remove biases in TROPOMI satellite observations of atmospheric methane, with GOSAT observations serving as a reference. We find that the TROPOMI biases relative to GOSAT are related to the presence of aerosols and clouds, the surface brightness, and the specific detector that makes the observation aboard TROPOMI. The resulting blended TROPOMI+GOSAT product is more reliable for quantifying methane emissions.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 23, 8899–8919, https://doi.org/10.5194/acp-23-8899-2023, https://doi.org/10.5194/acp-23-8899-2023, 2023
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We present a fast method to evaluate carbon monoxide emissions from cities in Africa. Carbon monoxide is important for climate change in an indirect way, as it is linked to ozone, methane, and carbon dioxide. Our measurements are made with a satellite that sees the entire globe every single day. This means that we can check from space whether the current knowledge of emission rates is up to date. We make the comparison and show that the emission rates in northern Africa are underestimated.
Ruosi Liang, Yuzhong Zhang, Wei Chen, Peixuan Zhang, Jingran Liu, Cuihong Chen, Huiqin Mao, Guofeng Shen, Zhen Qu, Zichong Chen, Minqiang Zhou, Pucai Wang, Robert J. Parker, Hartmut Boesch, Alba Lorente, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 8039–8057, https://doi.org/10.5194/acp-23-8039-2023, https://doi.org/10.5194/acp-23-8039-2023, 2023
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We compare and evaluate East Asian methane emissions inferred from different satellite observations (GOSAT and TROPOMI). The results show discrepancies over northern India and eastern China. Independent ground-based observations are more consistent with TROPOMI-derived emissions in northern India and GOSAT-derived emissions in eastern China.
Daniel J. Varon, Daniel J. Jacob, Benjamin Hmiel, Ritesh Gautam, David R. Lyon, Mark Omara, Melissa Sulprizio, Lu Shen, Drew Pendergrass, Hannah Nesser, Zhen Qu, Zachary R. Barkley, Natasha L. Miles, Scott J. Richardson, Kenneth J. Davis, Sudhanshu Pandey, Xiao Lu, Alba Lorente, Tobias Borsdorff, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 7503–7520, https://doi.org/10.5194/acp-23-7503-2023, https://doi.org/10.5194/acp-23-7503-2023, 2023
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We use TROPOMI satellite observations to quantify weekly methane emissions from the US Permian oil and gas basin from May 2018 to October 2020. We find that Permian emissions are highly variable, with diverse economic and activity drivers. The most important drivers during our study period were new well development and natural gas price. Permian methane intensity averaged 4.6 % and decreased by 1 % per year.
Tobias Borsdorff, Teresa Campos, Natalie Kille, Kyle J. Zarzana, Rainer Volkamer, and Jochen Landgraf
Atmos. Meas. Tech., 16, 3027–3038, https://doi.org/10.5194/amt-16-3027-2023, https://doi.org/10.5194/amt-16-3027-2023, 2023
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ECMWF plans to assimilate TROPOMI CO with their CAMS-IFS model. This will constrain the total column and the vertical CO distribution of the model. To show this, we combine individual TROPOMI CO column retrievals with different vertical sensitivities and obtain a vertical CO concentration profile. We test the approach on three CO pollution events in comparison with CAMS-IFS simulations that do not assimilate TROPOMI CO data and in situ airborne measurements of the BB-FLUX campaign.
Zichong Chen, Daniel J. Jacob, Ritesh Gautam, Mark Omara, Robert N. Stavins, Robert C. Stowe, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Drew C. Pendergrass, and Sarah Hancock
Atmos. Chem. Phys., 23, 5945–5967, https://doi.org/10.5194/acp-23-5945-2023, https://doi.org/10.5194/acp-23-5945-2023, 2023
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We quantify methane emissions from individual countries in the Middle East and North Africa by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We show that the ability to simply relate oil/gas emissions to activity metrics is compromised by stochastic nature of local infrastructure and management practices. We find that the industry target for oil/gas methane intensity is achievable through associated gas capture, modern infrastructure, and centralized operations.
Edward Gryspeerdt, Adam C. Povey, Roy G. Grainger, Otto Hasekamp, N. Christina Hsu, Jane P. Mulcahy, Andrew M. Sayer, and Armin Sorooshian
Atmos. Chem. Phys., 23, 4115–4122, https://doi.org/10.5194/acp-23-4115-2023, https://doi.org/10.5194/acp-23-4115-2023, 2023
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The impact of aerosols on clouds is one of the largest uncertainties in the human forcing of the climate. Aerosol can increase the concentrations of droplets in clouds, but observational and model studies produce widely varying estimates of this effect. We show that these estimates can be reconciled if only polluted clouds are studied, but this is insufficient to constrain the climate impact of aerosol. The uncertainty in aerosol impact on clouds is currently driven by cases with little aerosol.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
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We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, and Jochen Landgraf
Atmos. Meas. Tech., 16, 1597–1608, https://doi.org/10.5194/amt-16-1597-2023, https://doi.org/10.5194/amt-16-1597-2023, 2023
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In the TROPOMI methane data, there are few false methane anomalies that can be misinterpreted as enhancements caused by strong emission sources. These artefacts are caused by features of the underlying surfaces that are not well characterized in the retrieval algorithm. Here we improve the representation of the surface reflectance dependency with wavelength in the forward model, removing the artificial localized CH4 enhancements found in several locations like Siberia, Australia and Algeria.
Xueying Yu, Dylan B. Millet, Daven K. Henze, Alexander J. Turner, Alba Lorente Delgado, A. Anthony Bloom, and Jianxiong Sheng
Atmos. Chem. Phys., 23, 3325–3346, https://doi.org/10.5194/acp-23-3325-2023, https://doi.org/10.5194/acp-23-3325-2023, 2023
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We combine satellite measurements with a novel downscaling method to map global methane emissions at 0.1°×0.1° resolution. These fine-scale emission estimates reveal unreported emission hotspots and shed light on the roles of agriculture, wetlands, and fossil fuels for regional methane budgets. The satellite-derived emissions point in particular to missing fossil fuel emissions in the Middle East and to a large emission underestimate in South Asia that appears to be tied to monsoon rainfall.
Adriana Bailey, Franziska Aemisegger, Leonie Villiger, Sebastian A. Los, Gilles Reverdin, Estefanía Quiñones Meléndez, Claudia Acquistapace, Dariusz B. Baranowski, Tobias Böck, Sandrine Bony, Tobias Bordsdorff, Derek Coffman, Simon P. de Szoeke, Christopher J. Diekmann, Marina Dütsch, Benjamin Ertl, Joseph Galewsky, Dean Henze, Przemyslaw Makuch, David Noone, Patricia K. Quinn, Michael Rösch, Andreas Schneider, Matthias Schneider, Sabrina Speich, Bjorn Stevens, and Elizabeth J. Thompson
Earth Syst. Sci. Data, 15, 465–495, https://doi.org/10.5194/essd-15-465-2023, https://doi.org/10.5194/essd-15-465-2023, 2023
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One of the novel ways EUREC4A set out to investigate trade wind clouds and their coupling to the large-scale circulation was through an extensive network of isotopic measurements in water vapor, precipitation, and seawater. Samples were taken from the island of Barbados, from aboard two aircraft, and from aboard four ships. This paper describes the full collection of EUREC4A isotopic in situ data and guides readers to complementary remotely sensed water vapor isotope ratios.
Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stamnes, Michael Shook, and Luke Ziemba
Atmos. Meas. Tech., 15, 7411–7434, https://doi.org/10.5194/amt-15-7411-2022, https://doi.org/10.5194/amt-15-7411-2022, 2022
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The strong variability in the chemistry of atmospheric particulate matter affects the amount of water aerosols absorb and their effect on climate. We present a remote sensing method to determine the amount of water in particulate matter. Its application to airborne instruments indicates that the observed aerosols have rather low water contents and low fractions of soluble particles. Future satellites will be able to yield global aerosol water uptake data.
Antje Inness, Ilse Aben, Melanie Ades, Tobias Borsdorff, Johannes Flemming, Luke Jones, Jochen Landgraf, Bavo Langerock, Philippe Nedelec, Mark Parrington, and Roberto Ribas
Atmos. Chem. Phys., 22, 14355–14376, https://doi.org/10.5194/acp-22-14355-2022, https://doi.org/10.5194/acp-22-14355-2022, 2022
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The Copernicus Atmosphere Monitoring Service (CAMS) provides daily global air quality forecasts to users worldwide. One of the species of interest is carbon monoxide (CO), an important trace gas in the atmosphere with anthropogenic and natural sources, produced by incomplete combustion, for example, by wildfires. This paper looks at how well CAMS can model CO in the atmosphere and shows that the fields can be improved when blending CO data from the TROPOMI instrument with the CAMS model.
Zichong Chen, Daniel J. Jacob, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Elise Penn, and Xueying Yu
Atmos. Chem. Phys., 22, 10809–10826, https://doi.org/10.5194/acp-22-10809-2022, https://doi.org/10.5194/acp-22-10809-2022, 2022
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We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current
coal-to-gasenergy transition in China. However, this small loss rate can be misleading given China's high gas imports.
Matthieu Dogniaux, Cyril Crevoisier, Silvère Gousset, Étienne Le Coarer, Yann Ferrec, Laurence Croizé, Lianghai Wu, Otto Hasekamp, Bojan Sic, and Laure Brooker
Atmos. Meas. Tech., 15, 4835–4858, https://doi.org/10.5194/amt-15-4835-2022, https://doi.org/10.5194/amt-15-4835-2022, 2022
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The Space Carbon Observatory (SCARBO) concept proposes a constellation of small satellites that would carry a miniaturized Fabry–Pérot imaging interferometer named NanoCarb and an aerosol instrument named SPEXone. In this work, we assess the performance of this concept for the retrieval of the total weighted columns of CO2 and CH4 and show the interest of adding the SPEXone aerosol instrument to improve the CO2 and CH4 column retrieval.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879, https://doi.org/10.5194/amt-15-4859-2022, https://doi.org/10.5194/amt-15-4859-2022, 2022
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In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
Sara Martínez-Alonso, Merritt N. Deeter, Bianca C. Baier, Kathryn McKain, Helen Worden, Tobias Borsdorff, Colm Sweeney, and Ilse Aben
Atmos. Meas. Tech., 15, 4751–4765, https://doi.org/10.5194/amt-15-4751-2022, https://doi.org/10.5194/amt-15-4751-2022, 2022
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AirCore is a novel balloon sampling system that can measure, among others, vertical profiles of carbon monoxide (CO) from 25–30 km of altitude to near the surface. Our analyses of AirCore and satellite CO data show that AirCore profiles are suited for satellite data validation, the use of shorter aircraft vertical profiles in satellite validation results in small errors (1–3 percent points) mostly at 300 hPa and above, and the error introduced by clouds in TROPOMI land data is small (1–2 %).
Pieternel F. Levelt, Deborah C. Stein Zweers, Ilse Aben, Maite Bauwens, Tobias Borsdorff, Isabelle De Smedt, Henk J. Eskes, Christophe Lerot, Diego G. Loyola, Fabian Romahn, Trissevgeni Stavrakou, Nicolas Theys, Michel Van Roozendael, J. Pepijn Veefkind, and Tijl Verhoelst
Atmos. Chem. Phys., 22, 10319–10351, https://doi.org/10.5194/acp-22-10319-2022, https://doi.org/10.5194/acp-22-10319-2022, 2022
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Using the COVID-19 lockdown periods as an example, we show how Sentinel-5P/TROPOMI trace gas data (NO2, SO2, CO, HCHO and CHOCHO) can be used to understand impacts on air quality for regions and cities around the globe. We also provide information for both experienced and inexperienced users about how we created the data using state-of-the-art algorithms, where to get the data, methods taking meteorological and seasonal variability into consideration, and insights for future studies.
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
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We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Daniel J. Varon, Daniel J. Jacob, Melissa Sulprizio, Lucas A. Estrada, William B. Downs, Lu Shen, Sarah E. Hancock, Hannah Nesser, Zhen Qu, Elise Penn, Zichong Chen, Xiao Lu, Alba Lorente, Ashutosh Tewari, and Cynthia A. Randles
Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022, https://doi.org/10.5194/gmd-15-5787-2022, 2022
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Reducing atmospheric methane emissions is critical to slow near-term climate change. Globally surveying satellite instruments like the TROPOspheric Monitoring Instrument (TROPOMI) have unique capabilities for monitoring atmospheric methane around the world. Here we present a user-friendly cloud-computing tool that enables researchers and stakeholders to quantify methane emissions across user-selected regions of interest using TROPOMI satellite observations.
Jonas Hachmeister, Oliver Schneising, Michael Buchwitz, Alba Lorente, Tobias Borsdorff, John P. Burrows, Justus Notholt, and Matthias Buschmann
Atmos. Meas. Tech., 15, 4063–4074, https://doi.org/10.5194/amt-15-4063-2022, https://doi.org/10.5194/amt-15-4063-2022, 2022
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Sentinel-5P trace gas retrievals rely on elevation data in their calculations. Outdated or inaccurate data can lead to significant errors in e.g. dry-air mole fractions of methane (XCH4). We show that the use of inadequate elevation data leads to strong XCH4 anomalies in Greenland. Similar problems can be expected for other regions with inaccurate elevation data. However, we expect these to be more localized. We show that updating elevation data used in the retrieval solves this issue.
Andreas Luther, Julian Kostinek, Ralph Kleinschek, Sara Defratyka, Mila Stanisavljević, Andreas Forstmaier, Alexandru Dandocsi, Leon Scheidweiler, Darko Dubravica, Norman Wildmann, Frank Hase, Matthias M. Frey, Jia Chen, Florian Dietrich, Jarosław Nȩcki, Justyna Swolkień, Christoph Knote, Sanam N. Vardag, Anke Roiger, and André Butz
Atmos. Chem. Phys., 22, 5859–5876, https://doi.org/10.5194/acp-22-5859-2022, https://doi.org/10.5194/acp-22-5859-2022, 2022
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Coal mining is an extensive source of anthropogenic methane emissions. In order to reduce and mitigate methane emissions, it is important to know how much and where the methane is emitted. We estimated coal mining methane emissions in Poland based on atmospheric methane measurements and particle dispersion modeling. In general, our emission estimates suggest higher emissions than expected by previous annual emission reports.
Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
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Space-borne greenhouse gas missions require ground-based validation networks capable of providing fiducial reference measurements. Here, considerable refinements of the calibration procedures for the COllaborative Carbon Column Observing Network (COCCON) are presented. Laboratory and solar side-by-side procedures for the characterization of the spectrometers have been refined and extended. Revised calibration factors for XCO2, XCO and XCH4 are provided, incorporating 47 new spectrometers.
Athanasios Tsikerdekis, Nick A. J. Schutgens, Guangliang Fu, and Otto P. Hasekamp
Geosci. Model Dev., 15, 3253–3279, https://doi.org/10.5194/gmd-15-3253-2022, https://doi.org/10.5194/gmd-15-3253-2022, 2022
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In our study we quantify the ability of the future satellite sensor SPEXone, part of the NASA PACE mission, to estimate aerosol emissions. The sensor will be able to retrieve accurate information of aerosol light extinction and most importantly light absorption. We simulate SPEXone spatial coverage and combine it with an aerosol model. We found that SPEXone will be able to estimate species-specific (e.g. dust, sea salt, organic or black carbon, sulfates) aerosol emissions very accurately.
Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Alba Lorente, Franziska Aemisegger, David Noone, Dean Henze, Rigel Kivi, and Jochen Landgraf
Atmos. Meas. Tech., 15, 2251–2275, https://doi.org/10.5194/amt-15-2251-2022, https://doi.org/10.5194/amt-15-2251-2022, 2022
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This paper presents an extended H₂O/HDO total column dataset from short-wave infrared measurements by TROPOMI including cloudy and clear-sky scenes. Coverage is tremendously increased compared to previous TROPOMI HDO datasets. The new dataset is validated against recent ground-based FTIR measurements from TCCON and against aircraft measurements over the ocean. The use of the new dataset is demonstrated with a case study of a cold air outbreak in January 2020.
Meloë S. F. Kacenelenbogen, Qian Tan, Sharon P. Burton, Otto P. Hasekamp, Karl D. Froyd, Yohei Shinozuka, Andreas J. Beyersdorf, Luke Ziemba, Kenneth L. Thornhill, Jack E. Dibb, Taylor Shingler, Armin Sorooshian, Reed W. Espinosa, Vanderlei Martins, Jose L. Jimenez, Pedro Campuzano-Jost, Joshua P. Schwarz, Matthew S. Johnson, Jens Redemann, and Gregory L. Schuster
Atmos. Chem. Phys., 22, 3713–3742, https://doi.org/10.5194/acp-22-3713-2022, https://doi.org/10.5194/acp-22-3713-2022, 2022
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The impact of aerosols on Earth's radiation budget and human health is important and strongly depends on their composition. One desire of our scientific community is to derive the composition of the aerosol from satellite sensors. However, satellites observe aerosol optical properties (and not aerosol composition) based on remote sensing instrumentation. This study assesses how much aerosol optical properties can tell us about aerosol composition.
Tobias Küchler, Stefan Noël, Heinrich Bovensmann, John Philip Burrows, Thomas Wagner, Christian Borger, Tobias Borsdorff, and Andreas Schneider
Atmos. Meas. Tech., 15, 297–320, https://doi.org/10.5194/amt-15-297-2022, https://doi.org/10.5194/amt-15-297-2022, 2022
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We applied the air-mass-corrected differential optical absorption spectroscopy (AMC-DOAS) method to derive total column water vapour (TCWV) from Sentinel-5P measurements and compared it to independent data sets. The correlation coefficients of typically more than 0.9 and the small deviations up to 2.5 kg m−2 reveal good agreement between our data product and other TCWV data sets. In particular for the different Sentinel-5P water vapour products, the deviations are around 1 kg m−2.
Qiansi Tu, Frank Hase, Matthias Schneider, Omaira García, Thomas Blumenstock, Tobias Borsdorff, Matthias Frey, Farahnaz Khosrawi, Alba Lorente, Carlos Alberti, Juan J. Bustos, André Butz, Virgilio Carreño, Emilio Cuevas, Roger Curcoll, Christopher J. Diekmann, Darko Dubravica, Benjamin Ertl, Carme Estruch, Sergio Fabián León-Luis, Carlos Marrero, Josep-Anton Morgui, Ramón Ramos, Christian Scharun, Carsten Schneider, Eliezer Sepúlveda, Carlos Toledano, and Carlos Torres
Atmos. Chem. Phys., 22, 295–317, https://doi.org/10.5194/acp-22-295-2022, https://doi.org/10.5194/acp-22-295-2022, 2022
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We use different methane ground- and space-based remote sensing data sets for investigating the emission strength of three waste disposal sites close to Madrid. We present a method that uses wind-assigned anomalies for deriving emission strengths from satellite data and estimate their uncertainty to 9–14 %. The emission strengths estimated from the remote sensing data sets are significantly larger than the values published in the official register.
Tyler Wizenberg, Kimberly Strong, Kaley Walker, Erik Lutsch, Tobias Borsdorff, and Jochen Landgraf
Atmos. Meas. Tech., 14, 7707–7728, https://doi.org/10.5194/amt-14-7707-2021, https://doi.org/10.5194/amt-14-7707-2021, 2021
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CO is an important atmospheric gas that influences both air quality and the climate. Here, we compare CO measurements from TROPOMI with those from ACE-FTS and an Arctic ground-based FTS at Eureka, Nunavut, to further characterize the accuracy of TROPOMI measurements. CO columns from the instruments agree well but show larger differences at high latitudes. Despite this, the results fall within the TROPOMI accuracy target, indicating good data quality at high latitudes.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
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This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
Zhen Qu, Daniel J. Jacob, Lu Shen, Xiao Lu, Yuzhong Zhang, Tia R. Scarpelli, Hannah Nesser, Melissa P. Sulprizio, Joannes D. Maasakkers, A. Anthony Bloom, John R. Worden, Robert J. Parker, and Alba L. Delgado
Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, https://doi.org/10.5194/acp-21-14159-2021, 2021
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The recent launch of TROPOMI offers an unprecedented opportunity to quantify the methane budget from a top-down perspective. We use TROPOMI and the more mature GOSAT methane observations to estimate methane emissions and get consistent global budgets. However, TROPOMI shows biases over regions where surface albedo is small and provides less information for the coarse-resolution inversion due to the larger error correlations and spatial variations in the number of observations.
William G. K. McLean, Guangliang Fu, Sharon P. Burton, and Otto P. Hasekamp
Atmos. Meas. Tech., 14, 4755–4771, https://doi.org/10.5194/amt-14-4755-2021, https://doi.org/10.5194/amt-14-4755-2021, 2021
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In this study, we present results from aerosol retrievals using both synthetic and real lidar datasets, including measurements from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, a combined initiative between NASA and SRON (the Netherlands Institute for Space Research). Aerosol microphysical retrievals were performed using the High Spectral Resolution Lidar-2 (HSRL-2) setup, alongside several others, with the ACEPOL retrievals also compared to polarimeter retrievals.
Julian Kostinek, Anke Roiger, Maximilian Eckl, Alina Fiehn, Andreas Luther, Norman Wildmann, Theresa Klausner, Andreas Fix, Christoph Knote, Andreas Stohl, and André Butz
Atmos. Chem. Phys., 21, 8791–8807, https://doi.org/10.5194/acp-21-8791-2021, https://doi.org/10.5194/acp-21-8791-2021, 2021
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Abundant mining and industrial activities in the Upper Silesian Coal Basin lead to large emissions of the potent greenhouse gas methane. This study quantifies these emissions with continuous, high-precision airborne measurements and dispersion modeling. Our emission estimates are in line with values reported in the European Pollutant Release and Transfer Register (E-PRTR 2017) but significantly lower than values reported in the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2).
Meng Gao, Bryan A. Franz, Kirk Knobelspiesse, Peng-Wang Zhai, Vanderlei Martins, Sharon Burton, Brian Cairns, Richard Ferrare, Joel Gales, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Brent McBride, Anin Puthukkudy, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 14, 4083–4110, https://doi.org/10.5194/amt-14-4083-2021, https://doi.org/10.5194/amt-14-4083-2021, 2021
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Multi-angle polarimetric measurements can retrieve accurate aerosol properties over complex atmosphere and ocean systems; however, most retrieval algorithms require high computational costs. We propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems and then conduct simultaneous aerosol and ocean color retrievals on AirHARP measurements. The computational acceleration is 103 times with CPU or 104 times with GPU.
Nick Schutgens, Oleg Dubovik, Otto Hasekamp, Omar Torres, Hiren Jethva, Peter J. T. Leonard, Pavel Litvinov, Jens Redemann, Yohei Shinozuka, Gerrit de Leeuw, Stefan Kinne, Thomas Popp, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 21, 6895–6917, https://doi.org/10.5194/acp-21-6895-2021, https://doi.org/10.5194/acp-21-6895-2021, 2021
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Absorptive aerosol has a potentially large impact on climate change. We evaluate and intercompare four global satellite datasets of absorptive aerosol optical depth (AAOD) and single-scattering albedo (SSA). We show that these datasets show reasonable correlations with the AErosol RObotic NETwork (AERONET) reference, although significant biases remain. In a follow-up paper we show that these observations nevertheless can be used for model evaluation.
Jérôme Barré, Ilse Aben, Anna Agustí-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Peter Dueben, Richard Engelen, Antje Inness, Alba Lorente, Joe McNorton, Vincent-Henri Peuch, Gabor Radnoti, and Roberto Ribas
Atmos. Chem. Phys., 21, 5117–5136, https://doi.org/10.5194/acp-21-5117-2021, https://doi.org/10.5194/acp-21-5117-2021, 2021
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This study presents a new approach to the systematic global detection of anomalous local CH4 concentration anomalies caused by rapid changes in anthropogenic emission levels. The approach utilises both satellite measurements and model simulations, and applies novel data analysis techniques (such as filtering and classification) to automatically detect anomalous emissions from point sources and small areas, such as oil and gas drilling sites, pipelines and facility leaks.
Michael Buchwitz, Maximilian Reuter, Stefan Noël, Klaus Bramstedt, Oliver Schneising, Michael Hilker, Blanca Fuentes Andrade, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Hartmut Boesch, Lianghai Wu, Jochen Landgraf, Ilse Aben, Christian Retscher, Christopher W. O'Dell, and David Crisp
Atmos. Meas. Tech., 14, 2141–2166, https://doi.org/10.5194/amt-14-2141-2021, https://doi.org/10.5194/amt-14-2141-2021, 2021
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The COVID-19 pandemic resulted in reduced anthropogenic carbon dioxide (CO2) emissions during 2020 in large parts of the world. We have used a small ensemble of satellite retrievals of column-averaged CO2 (XCO2) to find out if a regional-scale reduction of atmospheric CO2 can be detected from space. We focus on East China and show that it is challenging to reliably detect and to accurately quantify the emission reduction, which only results in regional XCO2 reductions of about 0.1–0.2 ppm.
Hiroshi Suto, Fumie Kataoka, Nobuhiro Kikuchi, Robert O. Knuteson, Andre Butz, Markus Haun, Henry Buijs, Kei Shiomi, Hiroko Imai, and Akihiko Kuze
Atmos. Meas. Tech., 14, 2013–2039, https://doi.org/10.5194/amt-14-2013-2021, https://doi.org/10.5194/amt-14-2013-2021, 2021
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The Japanese Greenhouse gases Observing SATellite-2 (GOSAT-2), in orbit since October 2018, is the follow-up mission of GOSAT, which has been operating since January 2009. Both satellites are dedicated to the monitoring of global carbon dioxide and methane to further knowledge of the global carbon cycle. This paper has reported on the function and performance of the TANSO-FTS-2 instrument, level-1 data processing, and calibrations for the first year of GOSAT-2 observation.
Qiansi Tu, Frank Hase, Thomas Blumenstock, Matthias Schneider, Andreas Schneider, Rigel Kivi, Pauli Heikkinen, Benjamin Ertl, Christopher Diekmann, Farahnaz Khosrawi, Michael Sommer, Tobias Borsdorff, and Uwe Raffalski
Atmos. Meas. Tech., 14, 1993–2011, https://doi.org/10.5194/amt-14-1993-2021, https://doi.org/10.5194/amt-14-1993-2021, 2021
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We compare column-averaged dry-air mole fractions of water vapor (XH2O) retrievals from the COllaborative Carbon Column Observing Network (COCCON) with two co-located ground-based spectrometers as references at two boreal sites. Our study supports the assumption that COCCON also delivers a well-characterized XH2O data product. This is the first published study applying COCCON for MUSICA IASI and TROPOMI validation.
Athanasios Tsikerdekis, Nick A. J. Schutgens, and Otto P. Hasekamp
Atmos. Chem. Phys., 21, 2637–2674, https://doi.org/10.5194/acp-21-2637-2021, https://doi.org/10.5194/acp-21-2637-2021, 2021
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Accurate representation of aerosols in the atmosphere is hard to achieve due to their complex microphysical and optical properties and uncertain emissions. In our work, we employ a data assimilation method which integrates model simulations with satellite observation related to the amount, size and the light absorption of aerosol. The use of these observations in an experiment improves aerosol representation and it is recommended for utilization in future data assimilation practices.
Stephanie P. Rusli, Otto Hasekamp, Joost aan de Brugh, Guangliang Fu, Yasjka Meijer, and Jochen Landgraf
Atmos. Meas. Tech., 14, 1167–1190, https://doi.org/10.5194/amt-14-1167-2021, https://doi.org/10.5194/amt-14-1167-2021, 2021
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This study investigates the added value of multi-angle polarimeter (MAP) measurements for XCO2 retrievals, particularly in the context of the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission. In this paper, we derive the required MAP instrument specification, and we demonstrate that MAP observations significantly improve the retrieval performance and are needed to meet the XCO2 precision and accuracy requirements of the CO2M mission.
Marvin Knapp, Ralph Kleinschek, Frank Hase, Anna Agustí-Panareda, Antje Inness, Jérôme Barré, Jochen Landgraf, Tobias Borsdorff, Stefan Kinne, and André Butz
Earth Syst. Sci. Data, 13, 199–211, https://doi.org/10.5194/essd-13-199-2021, https://doi.org/10.5194/essd-13-199-2021, 2021
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We developed a shipborne variant of a remote sensing spectrometer for direct sunlight measurements of column-averaged atmospheric mixing ratios of carbon dioxide, methane, and carbon monoxide. The instrument was deployed on the research vessel Sonne during a longitudinal transect over the Pacific during June 2019. The campaign yielded more than 32 000 observations which compare excellently to atmospheric composition data from a state-of-the-art model (CAMS) and satellite observations (TROPOMI).
Alba Lorente, Tobias Borsdorff, Andre Butz, Otto Hasekamp, Joost aan de Brugh, Andreas Schneider, Lianghai Wu, Frank Hase, Rigel Kivi, Debra Wunch, David F. Pollard, Kei Shiomi, Nicholas M. Deutscher, Voltaire A. Velazco, Coleen M. Roehl, Paul O. Wennberg, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, https://doi.org/10.5194/amt-14-665-2021, 2021
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TROPOMI aboard Sentinel-5P satellite provides methane (CH4) measurements with exceptional temporal and spatial resolution. The study describes a series of improvements developed to retrieve CH4 from TROPOMI. The updated CH4 product features (among others) a more accurate a posteriori correction derived independently of any reference data. The validation of the improved data product shows good agreement with ground-based and satellite measurements, which highlights the quality of the TROPOMI CH4.
Sudhanshu Pandey, Sander Houweling, Alba Lorente, Tobias Borsdorff, Maria Tsivlidou, A. Anthony Bloom, Benjamin Poulter, Zhen Zhang, and Ilse Aben
Biogeosciences, 18, 557–572, https://doi.org/10.5194/bg-18-557-2021, https://doi.org/10.5194/bg-18-557-2021, 2021
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We use atmospheric methane observations from the novel TROPOspheric Monitoring Instrument (TROPOMI; Sentinel-5p) to estimate methane emissions from South Sudan's wetlands. Our emission estimates are an order of magnitude larger than the estimate of process-based wetland models. We find that this underestimation by the models is likely due to their misrepresentation of the wetlands' inundation extent and temperature dependences.
Ivar R. van der Velde, Guido R. van der Werf, Sander Houweling, Henk J. Eskes, J. Pepijn Veefkind, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 21, 597–616, https://doi.org/10.5194/acp-21-597-2021, https://doi.org/10.5194/acp-21-597-2021, 2021
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This paper compares the relative atmospheric enhancements of CO and NO2 measured by the space-based instrument TROPOMI over different fire-prone ecosystems around the world. We find distinct spatial and temporal patterns in the ΔNO2 / ΔCO ratio that correspond to regional differences in combustion efficiency. This joint analysis provides a better understanding of regional-scale combustion characteristics and can help the fire modeling community to improve existing global emission inventories.
Tobias Borsdorff, Agustín García Reynoso, Gilberto Maldonado, Bertha Mar-Morales, Wolfgang Stremme, Michel Grutter, and Jochen Landgraf
Atmos. Chem. Phys., 20, 15761–15774, https://doi.org/10.5194/acp-20-15761-2020, https://doi.org/10.5194/acp-20-15761-2020, 2020
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
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Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Sara Martínez-Alonso, Merritt Deeter, Helen Worden, Tobias Borsdorff, Ilse Aben, Róisin Commane, Bruce Daube, Gene Francis, Maya George, Jochen Landgraf, Debbie Mao, Kathryn McKain, and Steven Wofsy
Atmos. Meas. Tech., 13, 4841–4864, https://doi.org/10.5194/amt-13-4841-2020, https://doi.org/10.5194/amt-13-4841-2020, 2020
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CO is of great importance in climate and air quality studies. To understand newly available TROPOMI data in the frame of the global CO record, we compared those to satellite (MOPITT) and airborne (ATom) CO datasets. The MOPITT dataset is the longest to date (2000–present) and is well-characterized. We used ATom to validate cloudy TROPOMI data over oceans and investigate TROPOMI's vertical sensitivity to CO. Our results show that TROPOMI CO data are in excellent agreement with the other datasets.
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
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The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign is a resource for the next generation of spaceborne multi-angle polarimeter (MAP) and lidar missions. Conducted in the fall of 2017 from the Armstrong Flight Research Center in Palmdale, California, four MAP instruments and two lidars were flown on the high-altitude ER-2 aircraft over a variety of scene types and ground assets. Data are freely available to the public and useful for algorithm development and testing.
Qiansi Tu, Frank Hase, Thomas Blumenstock, Rigel Kivi, Pauli Heikkinen, Mahesh Kumar Sha, Uwe Raffalski, Jochen Landgraf, Alba Lorente, Tobias Borsdorff, Huilin Chen, Florian Dietrich, and Jia Chen
Atmos. Meas. Tech., 13, 4751–4771, https://doi.org/10.5194/amt-13-4751-2020, https://doi.org/10.5194/amt-13-4751-2020, 2020
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Two COCCON instruments are used to observe multiyear greenhouse gases in boreal areas and are compared with the CAMS analysis and S5P satellite data. These three datasets predict greenhouse gas gradients with reasonable agreement. The results indicate that the COCCON instrument has the capability of measuring gradients on regional scales, and observations performed with the portable spectrometers can contribute to inferring sources and sinks and to validating spaceborne greenhouse gases.
Srijana Lama, Sander Houweling, K. Folkert Boersma, Henk Eskes, Ilse Aben, Hugo A. C. Denier van der Gon, Maarten C. Krol, Han Dolman, Tobias Borsdorff, and Alba Lorente
Atmos. Chem. Phys., 20, 10295–10310, https://doi.org/10.5194/acp-20-10295-2020, https://doi.org/10.5194/acp-20-10295-2020, 2020
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Rapid urbanization has increased the consumption of fossil fuel, contributing the degradation of urban air quality. Burning efficiency is a major factor determining the impact of fuel burning on the environment. We quantify the burning efficiency of fossil fuel use over six megacities using satellite remote sensing data. City governance can use these results to understand air pollution scenarios and to formulate effective air pollution control strategies.
Thomas von Clarmann, Douglas A. Degenstein, Nathaniel J. Livesey, Stefan Bender, Amy Braverman, André Butz, Steven Compernolle, Robert Damadeo, Seth Dueck, Patrick Eriksson, Bernd Funke, Margaret C. Johnson, Yasuko Kasai, Arno Keppens, Anne Kleinert, Natalya A. Kramarova, Alexandra Laeng, Bavo Langerock, Vivienne H. Payne, Alexei Rozanov, Tomohiro O. Sato, Matthias Schneider, Patrick Sheese, Viktoria Sofieva, Gabriele P. Stiller, Christian von Savigny, and Daniel Zawada
Atmos. Meas. Tech., 13, 4393–4436, https://doi.org/10.5194/amt-13-4393-2020, https://doi.org/10.5194/amt-13-4393-2020, 2020
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Remote sensing of atmospheric state variables typically relies on the inverse solution of the radiative transfer equation. An adequately characterized retrieval provides information on the uncertainties of the estimated state variables as well as on how any constraint or a priori assumption affects the estimate. This paper summarizes related techniques and provides recommendations for unified error reporting.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Kirk Knobelspiesse, Amir Ibrahim, Brian Cairns, Susanne E. Craig, Guangliang Fu, Otto Hasekamp, Yongxiang Hu, and P. Jeremy Werdell
Atmos. Meas. Tech., 13, 3939–3956, https://doi.org/10.5194/amt-13-3939-2020, https://doi.org/10.5194/amt-13-3939-2020, 2020
Steven Compernolle, Tijl Verhoelst, Gaia Pinardi, José Granville, Daan Hubert, Arno Keppens, Sander Niemeijer, Bruno Rino, Alkis Bais, Steffen Beirle, Folkert Boersma, John P. Burrows, Isabelle De Smedt, Henk Eskes, Florence Goutail, François Hendrick, Alba Lorente, Andrea Pazmino, Ankie Piters, Enno Peters, Jean-Pierre Pommereau, Julia Remmers, Andreas Richter, Jos van Geffen, Michel Van Roozendael, Thomas Wagner, and Jean-Christopher Lambert
Atmos. Chem. Phys., 20, 8017–8045, https://doi.org/10.5194/acp-20-8017-2020, https://doi.org/10.5194/acp-20-8017-2020, 2020
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Tropospheric and stratospheric NO2 columns from the OMI QA4ECV NO2 satellite product are validated by comparison with ground-based measurements at 11 sites. The OMI stratospheric column has a small negative bias, and the OMI tropospheric column has a stronger negative bias relative to the ground-based data. Discrepancies are attributed to comparison errors (e.g. difference in horizontal smoothing) and measurement errors (e.g. clouds, aerosols, vertical smoothing and a priori profile assumptions).
Johan Strandgren, David Krutz, Jonas Wilzewski, Carsten Paproth, Ilse Sebastian, Kevin R. Gurney, Jianming Liang, Anke Roiger, and André Butz
Atmos. Meas. Tech., 13, 2887–2904, https://doi.org/10.5194/amt-13-2887-2020, https://doi.org/10.5194/amt-13-2887-2020, 2020
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This paper presents the concept of a spaceborne imaging spectrometer targeting the routine monitoring of CO2 emissions from localized point sources down to an emission strength of about 1 Mt CO2 yr-1. Using high-resolution CO2 emission and albedo data, it is shown that CO2 plumes from point sources with an emission strength down to the order of 0.3 Mt CO2 yr-1 can be resolved in an urban environment (when limited by instrument noise only), hence leaving significant margin for additional errors.
Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Stefan Noël, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Antonio Di Noia, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Lianghai Wu, Otto P. Hasekamp, Ilse Aben, Akihiko Kuze, Hiroshi Suto, Kei Shiomi, Yukio Yoshida, Isamu Morino, David Crisp, Christopher W. O'Dell, Justus Notholt, Christof Petri, Thorsten Warneke, Voltaire A. Velazco, Nicholas M. Deutscher, David W. T. Griffith, Rigel Kivi, David F. Pollard, Frank Hase, Ralf Sussmann, Yao V. Té, Kimberly Strong, Sébastien Roche, Mahesh K. Sha, Martine De Mazière, Dietrich G. Feist, Laura T. Iraci, Coleen M. Roehl, Christian Retscher, and Dinand Schepers
Atmos. Meas. Tech., 13, 789–819, https://doi.org/10.5194/amt-13-789-2020, https://doi.org/10.5194/amt-13-789-2020, 2020
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We present new satellite-derived data sets of atmospheric carbon dioxide (CO2) and methane (CH4). The data products are column-averaged dry-air mole fractions of CO2 and CH4, denoted XCO2 and XCH4. The products cover the years 2003–2018 and are merged Level 2 (satellite footprints) and merged Level 3 (gridded at monthly time and 5° x 5° spatial resolution) products obtained from combining several individual sensor products. We present the merging algorithms and product validation results.
Jonas Simon Wilzewski, Anke Roiger, Johan Strandgren, Jochen Landgraf, Dietrich G. Feist, Voltaire A. Velazco, Nicholas M. Deutscher, Isamu Morino, Hirofumi Ohyama, Yao Té, Rigel Kivi, Thorsten Warneke, Justus Notholt, Manvendra Dubey, Ralf Sussmann, Markus Rettinger, Frank Hase, Kei Shiomi, and André Butz
Atmos. Meas. Tech., 13, 731–745, https://doi.org/10.5194/amt-13-731-2020, https://doi.org/10.5194/amt-13-731-2020, 2020
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Through spectral degradation of GOSAT measurements in the 1.6 and 2.0 μm spectral bands, we mimic a single-band, passive satellite sensor for monitoring of CO2 emissions at fine spatial scales. We compare retrievals of XCO2 from these bands to TCCON and native GOSAT retrievals. At spectral resolutions near 1.3 nm, XCO2 retrievals from both bands show promising performance, but the 2.0 μm band is favorable due to better noise performance and the potential to retrieve some aerosol information.
Lianghai Wu, Joost aan de Brugh, Yasjka Meijer, Bernd Sierk, Otto Hasekamp, Andre Butz, and Jochen Landgraf
Atmos. Meas. Tech., 13, 713–729, https://doi.org/10.5194/amt-13-713-2020, https://doi.org/10.5194/amt-13-713-2020, 2020
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The future European CO2 monitoring constellation is targeting a moderate spectral resolution of 0.1, 0.3, and 0.3–0.55 nm in the spectral bands of 0.76, 1.61, and 2.06 μm. To assess this choice, we perform XCO2 retrievals using both satellite (OCO-2 and GOSAT) and synthetic observations, which we spectrally degrade to the target spectral resolution. We see that moderate spectral resolution mainly reduces XCO2 precision and has little effect on the the systematic error.
Guangliang Fu, Otto Hasekamp, Jeroen Rietjens, Martijn Smit, Antonio Di Noia, Brian Cairns, Andrzej Wasilewski, David Diner, Felix Seidel, Feng Xu, Kirk Knobelspiesse, Meng Gao, Arlindo da Silva, Sharon Burton, Chris Hostetler, John Hair, and Richard Ferrare
Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, https://doi.org/10.5194/amt-13-553-2020, 2020
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In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON (the Netherlands Institute for Space Research). We perform aerosol retrievals from different multi-angle polarimeters employed during the ACEPOL campaign and evaluate them against ground-based AERONET measurements and High Spectral Resolution Lidar-2 (HSRL-2) measurements.
Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Franziska Aemisegger, Dietrich G. Feist, Rigel Kivi, Frank Hase, Matthias Schneider, and Jochen Landgraf
Atmos. Meas. Tech., 13, 85–100, https://doi.org/10.5194/amt-13-85-2020, https://doi.org/10.5194/amt-13-85-2020, 2020
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This paper presents a new H2O/HDO data set from TROPOMI short-wave infrared measurements. It is validated against recent ground-based FTIR measurements from the TCCON network. A bias in TCCON HDO (which is not verified) is corrected by fitting a correction factor for the HDO column to match MUSICA δD for common observations. The use of the new TROPOMI data set is demonstrated using a case study of a blocking anticyclone over Europe in July 2018.
Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, John P. Burrows, Tobias Borsdorff, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Christian Hermans, Laura T. Iraci, Rigel Kivi, Jochen Landgraf, Isamu Morino, Justus Notholt, Christof Petri, David F. Pollard, Sébastien Roche, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Voltaire A. Velazco, Thorsten Warneke, and Debra Wunch
Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, https://doi.org/10.5194/amt-12-6771-2019, 2019
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We introduce an algorithm that is used to simultaneously derive the abundances of the important atmospheric constituents carbon monoxide and methane from the TROPOMI instrument onboard the Sentinel-5 Precursor satellite, which enables the determination of both gases with an unprecedented level of detail on a global scale. The quality of the resulting data sets is assessed and the first results are presented.
Edward Malina, Haili Hu, Jochen Landgraf, and Ben Veihelmann
Atmos. Meas. Tech., 12, 6273–6301, https://doi.org/10.5194/amt-12-6273-2019, https://doi.org/10.5194/amt-12-6273-2019, 2019
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We present a feasibility study on retrieving 12CH4 and 13CH4 using the recently launched TROPOMI on the Copernicus Sentinel 5P satellite and the future UVNS instrument on Sentinel 5. The ratio of 12CH4 and 13CH4 can be used to calculate the δ13C value, which has been shown to be able to distinguish between biological and non-biological sources of methane. We show that Sentinel 5/UVNS may be used to distinguish between methane source types, while Sentinel 5P/TROPOMI is subject to large biases.
Lianghai Wu, Otto Hasekamp, Haili Hu, Joost aan de Brugh, Jochen Landgraf, Andre Butz, and Ilse Aben
Atmos. Meas. Tech., 12, 6049–6058, https://doi.org/10.5194/amt-12-6049-2019, https://doi.org/10.5194/amt-12-6049-2019, 2019
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We propose a one–band XCO2 retrieval technique which uses only the 2.06 µm band measurements from the Orbiting Carbon Observatory–2 (OCO–2) satellite. Compared to the current state–of–the–art three–band retrievals, XCO2 retrievals using only the 2.06 µm band have similar retrieval accuracy, precision, and data yield. For future missions it may be better to replace the O2 A band with measurements that have larger information content on aerosols, like a multi–angle polarimeter (MAP).
Tobias Borsdorff, Joost aan de Brugh, Andreas Schneider, Alba Lorente, Manfred Birk, Georg Wagner, Rigel Kivi, Frank Hase, Dietrich G. Feist, Ralf Sussmann, Markus Rettinger, Debra Wunch, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 12, 5443–5455, https://doi.org/10.5194/amt-12-5443-2019, https://doi.org/10.5194/amt-12-5443-2019, 2019
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The study presents possible improvements of the TROPOMI CO dataset, which is a primary product of ESA's Sentinel-5P mission. We discuss the use of different molecular spectroscopic databases in the CO retrieval, the induced biases between TROPOMI CO and TCCON validation measurements, and the latitudinally dependent bias between TROPOMI CO and the CAMS-IFS model. Additionally, two methods for the stripe correction of single TROPOMI CO orbits are presented.
Andreas Luther, Ralph Kleinschek, Leon Scheidweiler, Sara Defratyka, Mila Stanisavljevic, Andreas Forstmaier, Alexandru Dandocsi, Sebastian Wolff, Darko Dubravica, Norman Wildmann, Julian Kostinek, Patrick Jöckel, Anna-Leah Nickl, Theresa Klausner, Frank Hase, Matthias Frey, Jia Chen, Florian Dietrich, Jarosław Nȩcki, Justyna Swolkień, Andreas Fix, Anke Roiger, and André Butz
Atmos. Meas. Tech., 12, 5217–5230, https://doi.org/10.5194/amt-12-5217-2019, https://doi.org/10.5194/amt-12-5217-2019, 2019
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Methane ventilated from hard coal mines in the Upper Silesian
Coal Basin in Poland is measured with a mobile Fourier transform spectrometer EM27/SUN. The instrument was mounted on a truck driving in stop-and-go patterns downwind of the methane sources. The emissions are estimated with the cross-sectional flux method. Calculated emissions are in broad agreement with the E-PRTR database. Wind-related errors on the methane estimates dominate the error budget and typically amount to 20 %.
Tobias Borsdorff, Joost aan de Brugh, Sudhanshu Pandey, Otto Hasekamp, Ilse Aben, Sander Houweling, and Jochen Landgraf
Atmos. Chem. Phys., 19, 3579–3588, https://doi.org/10.5194/acp-19-3579-2019, https://doi.org/10.5194/acp-19-3579-2019, 2019
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The Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite provides carbon monoxide (CO) total column concentrations based on measurements in the 2.3 μm spectral range with a spatial resolution of 7 km x 7 km and daily global coverage. In this study, we analyzed local CO enhancements in an area around Iran from 1 November to 20 December 2017 using the WRF model and evaluated CO emissions from the cities of Tehran, Yerevan, Urmia, and Tabriz.
Julian Kostinek, Anke Roiger, Kenneth J. Davis, Colm Sweeney, Joshua P. DiGangi, Yonghoon Choi, Bianca Baier, Frank Hase, Jochen Groß, Maximilian Eckl, Theresa Klausner, and André Butz
Atmos. Meas. Tech., 12, 1767–1783, https://doi.org/10.5194/amt-12-1767-2019, https://doi.org/10.5194/amt-12-1767-2019, 2019
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We demonstrate the successful adaption of a laser-based spectrometer for airborne in situ trace gas measurements. The modified instrument allows for precise and simultaneous airborne observation of five climatologically relevant gases. We further report on instrument performance during a first field deployment over the eastern and central USA.
Iris N. Dekker, Sander Houweling, Sudhanshu Pandey, Maarten Krol, Thomas Röckmann, Tobias Borsdorff, Jochen Landgraf, and Ilse Aben
Atmos. Chem. Phys., 19, 3433–3445, https://doi.org/10.5194/acp-19-3433-2019, https://doi.org/10.5194/acp-19-3433-2019, 2019
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During November 2017, very high pollution levels were measured in the northern part of India. In this study, satellite (TROPOMI) data and model (WRF) data on carbon monoxide (CO) are studied to investigate the main sources of the CO pollution over the Indo-Gangetic Plain. We found that residential and commercial combustion was a much more important source of CO than the post-monsoon crop burning during this period. Meteorology was found important in the accumulation and ventilation of CO.
Antonio Di Noia, Otto P. Hasekamp, Bastiaan van Diedenhoven, and Zhibo Zhang
Atmos. Meas. Tech., 12, 1697–1716, https://doi.org/10.5194/amt-12-1697-2019, https://doi.org/10.5194/amt-12-1697-2019, 2019
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We present a neural network algorithm for the retrieval of cloud physical properties from multi-angle polarimetric measurements. We have trained the algorithm on a large dataset of synthetic measurements and applied it to a year of POLDER-3 data. A comparison against MODIS cloud products reveals that our algorithm is capable of performing cloud property retrievals on a global scale and possibly improves the estimates of cloud effective radius over land with respect to existing POLDER-3 products.
Matthias Frey, Mahesh K. Sha, Frank Hase, Matthäus Kiel, Thomas Blumenstock, Roland Harig, Gregor Surawicz, Nicholas M. Deutscher, Kei Shiomi, Jonathan E. Franklin, Hartmut Bösch, Jia Chen, Michel Grutter, Hirofumi Ohyama, Youwen Sun, André Butz, Gizaw Mengistu Tsidu, Dragos Ene, Debra Wunch, Zhensong Cao, Omaira Garcia, Michel Ramonet, Felix Vogel, and Johannes Orphal
Atmos. Meas. Tech., 12, 1513–1530, https://doi.org/10.5194/amt-12-1513-2019, https://doi.org/10.5194/amt-12-1513-2019, 2019
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In a 3.5-year long study, the long-term performance of a mobile EM27/SUN spectrometer, used for greenhouse gas observations, is checked with respect to a co-located reference spectrometer. We find that the EM27/SUN is stable on timescales of several years, qualifying it for permanent carbon cycle studies.
The performance of an ensemble of 30 EM27/SUN spectrometers was also tested in the framework of the COllaborative Carbon Column Observing Network (COCCON) and found to be very uniform.
K. Folkert Boersma, Henk J. Eskes, Andreas Richter, Isabelle De Smedt, Alba Lorente, Steffen Beirle, Jos H. G. M. van Geffen, Marina Zara, Enno Peters, Michel Van Roozendael, Thomas Wagner, Joannes D. Maasakkers, Ronald J. van der A, Joanne Nightingale, Anne De Rudder, Hitoshi Irie, Gaia Pinardi, Jean-Christopher Lambert, and Steven C. Compernolle
Atmos. Meas. Tech., 11, 6651–6678, https://doi.org/10.5194/amt-11-6651-2018, https://doi.org/10.5194/amt-11-6651-2018, 2018
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This paper describes a new, improved data record of 22+ years of coherent nitrogen dioxide (NO2) pollution measurements from different satellite instruments. Our work helps to ensure that climate data are of sufficient quality to draw reliable conclusions and shape decisions. It shows how dedicated intercomparisons of retrieval sub-steps have led to improved NO2 measurements from the GOME, SCIAMACHY, GOME-2(A), and OMI sensors, and how quality assurance of the new data product is achieved.
Guangliang Fu and Otto Hasekamp
Atmos. Meas. Tech., 11, 6627–6650, https://doi.org/10.5194/amt-11-6627-2018, https://doi.org/10.5194/amt-11-6627-2018, 2018
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We implement a multimode approach in which each mode has fixed effective radius and effective variance. In this way the algorithm obtains more flexibility in describing the aerosol size distribution and avoids the high nonlinear dependence of the forward model on the aerosol size parameters. The synthetic and real data experiments show that multimode retrievals are good alternatives to the parametric two-mode approach.
Michael Buchwitz, Maximilian Reuter, Oliver Schneising, Stefan Noël, Bettina Gier, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Rob G. Detmers, Otto P. Hasekamp, Ilse Aben, André Butz, Akihiko Kuze, Hiroshi Suto, Yukio Yoshida, David Crisp, and Christopher O'Dell
Atmos. Chem. Phys., 18, 17355–17370, https://doi.org/10.5194/acp-18-17355-2018, https://doi.org/10.5194/acp-18-17355-2018, 2018
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We present a new satellite data set of column-averaged mixing ratios of carbon dioxide (CO2), which covers the time period 2003 to 2016. We used this data set to compute annual mean atmospheric CO2 growth rates. We show that the growth rate is highest during 2015 and 2016 despite nearly constant CO2 emissions from fossil fuel burning in recent years. The high growth rates are attributed to year 2015-2016 El Nino episodes. We present correlations with fossil fuel emissions and ENSO indices.
Tobias Borsdorff, Joost aan de Brugh, Haili Hu, Otto Hasekamp, Ralf Sussmann, Markus Rettinger, Frank Hase, Jochen Gross, Matthias Schneider, Omaira Garcia, Wolfgang Stremme, Michel Grutter, Dietrich G. Feist, Sabrina G. Arnold, Martine De Mazière, Mahesh Kumar Sha, David F. Pollard, Matthäus Kiel, Coleen Roehl, Paul O. Wennberg, Geoffrey C. Toon, and Jochen Landgraf
Atmos. Meas. Tech., 11, 5507–5518, https://doi.org/10.5194/amt-11-5507-2018, https://doi.org/10.5194/amt-11-5507-2018, 2018
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On 13 October 2017, the S5-P satellite was launched with TROPOMI as its only payload. One of the primary products is atmospheric CO observed with daily global coverage and spatial resolution of 7 × 7 km2. The new dataset allows the sensing of CO enhancements above cities and industrial areas and can track pollution transport from biomass burning regions. Through validation with ground-based TCCON measurements we show that the CO data product is already well within the mission requirement.
Alba Lorente, K. Folkert Boersma, Piet Stammes, L. Gijsbert Tilstra, Andreas Richter, Huan Yu, Said Kharbouche, and Jan-Peter Muller
Atmos. Meas. Tech., 11, 4509–4529, https://doi.org/10.5194/amt-11-4509-2018, https://doi.org/10.5194/amt-11-4509-2018, 2018
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Light reflected by Earth’s surface is different in each direction: it appears brighter or darker in certain viewing directions. Currently this effect is not accounted for in satellite retrievals; thus surface reflectance climatologies and cloud fractions show an east-west bias across orbits (GOME2,OMI). The effect for NO2 measurements in partly cloudy scenes is substantial. We recommend that this effect in UV/Vis sensors coherently accounted for, and will be especially beneficial for TROPOMI.
Arno de Lange and Jochen Landgraf
Atmos. Meas. Tech., 11, 3815–3828, https://doi.org/10.5194/amt-11-3815-2018, https://doi.org/10.5194/amt-11-3815-2018, 2018
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Atmospheric methane abundances as function of altitude derived from the thermal infrared band of the Japanese GOSAT satellite show a systematic bias. It has been shown that simple correction schemes can lead to undesired consequences. This paper discusses a more elaborate approach, resulting in methane profiles that fall within 2 % of independent reference measurements and models. This is true for different scenes around the globe and over the full altitude range.
Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Haili Hu, and Jochen Landgraf
Atmos. Meas. Tech., 11, 3339–3350, https://doi.org/10.5194/amt-11-3339-2018, https://doi.org/10.5194/amt-11-3339-2018, 2018
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A new data set of vertical column densities of the water vapour isotopologues H2O and HDO retrieved from short-wave infrared measurements (2339 nm to 2383 nm) by the SCIAMACHY satellite instrument for the whole of the mission period from 2003 to 2012 is presented. The data are validated against ground-based Fourier transform infrared measurements. High-altitude stations observe different air columns; thus in this case collocated scenes with clouds around station height are needed for agreement.
Lianghai Wu, Otto Hasekamp, Haili Hu, Jochen Landgraf, Andre Butz, Joost aan de Brugh, Ilse Aben, Dave F. Pollard, David W. T. Griffith, Dietrich G. Feist, Dmitry Koshelev, Frank Hase, Geoffrey C. Toon, Hirofumi Ohyama, Isamu Morino, Justus Notholt, Kei Shiomi, Laura Iraci, Matthias Schneider, Martine de Mazière, Ralf Sussmann, Rigel Kivi, Thorsten Warneke, Tae-Young Goo, and Yao Té
Atmos. Meas. Tech., 11, 3111–3130, https://doi.org/10.5194/amt-11-3111-2018, https://doi.org/10.5194/amt-11-3111-2018, 2018
Tobias Borsdorff, Josip Andrasec, Joost aan de Brugh, Haili Hu, Ilse Aben, and Jochen Landgraf
Atmos. Meas. Tech., 11, 2553–2565, https://doi.org/10.5194/amt-11-2553-2018, https://doi.org/10.5194/amt-11-2553-2018, 2018
Antonio Di Noia, Otto P. Hasekamp, Lianghai Wu, Bastiaan van Diedenhoven, Brian Cairns, and John E. Yorks
Atmos. Meas. Tech., 10, 4235–4252, https://doi.org/10.5194/amt-10-4235-2017, https://doi.org/10.5194/amt-10-4235-2017, 2017
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In this paper an algorithm for the retrieval of aerosol properties from NASA Research Scanning Polarimeter (RSP) data is presented. An artificial neural network is used to produce a first estimate of the aerosol properties, which is then improved using an iterative retrieval scheme based on Phillips–Tikhonov regularization. Using the neural network retrievals as a first guess for the Phillips–Tikhonov improved the retrieval convergence, confirming results previously found on ground-based data.
Tobias Borsdorff, Joost aan de Brugh, Haili Hu, Philippe Nédélec, Ilse Aben, and Jochen Landgraf
Atmos. Meas. Tech., 10, 1769–1782, https://doi.org/10.5194/amt-10-1769-2017, https://doi.org/10.5194/amt-10-1769-2017, 2017
Michael Buchwitz, Oliver Schneising, Maximilian Reuter, Jens Heymann, Sven Krautwurst, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Robert J. Parker, Peter Somkuti, Rob G. Detmers, Otto P. Hasekamp, Ilse Aben, André Butz, Christian Frankenberg, and Alexander J. Turner
Atmos. Chem. Phys., 17, 5751–5774, https://doi.org/10.5194/acp-17-5751-2017, https://doi.org/10.5194/acp-17-5751-2017, 2017
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Methane is an important greenhouse gas and increasing atmospheric concentrations result in global warming. We present a simple method to derive annual methane emission estimates of methane hotspot areas from satellite data. We present results for four source areas. We found that our estimates are in good agreement with other studies/data sets for the Four Corners region in the USA and for Azerbaijan but we also found higher emissions for parts of California and Turkmenistan.
Alba Lorente, K. Folkert Boersma, Huan Yu, Steffen Dörner, Andreas Hilboll, Andreas Richter, Mengyao Liu, Lok N. Lamsal, Michael Barkley, Isabelle De Smedt, Michel Van Roozendael, Yang Wang, Thomas Wagner, Steffen Beirle, Jin-Tai Lin, Nickolay Krotkov, Piet Stammes, Ping Wang, Henk J. Eskes, and Maarten Krol
Atmos. Meas. Tech., 10, 759–782, https://doi.org/10.5194/amt-10-759-2017, https://doi.org/10.5194/amt-10-759-2017, 2017
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Choices and assumptions made to represent the state of the atmosphere introduce an uncertainty of 42 % in the air mass factor calculation in trace gas satellite retrievals in polluted regions. The AMF strongly depends on the choice of a priori trace gas profile, surface albedo data set and the correction method to account for clouds and aerosols. We call for well-designed validation exercises focusing on situations when AMF structural uncertainty has the highest impact on satellite retrievals.
Anna Agusti-Panareda, Michail Diamantakis, Victor Bayona, Friedrich Klappenbach, and Andre Butz
Geosci. Model Dev., 10, 1–18, https://doi.org/10.5194/gmd-10-1-2017, https://doi.org/10.5194/gmd-10-1-2017, 2017
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This paper demonstrates how important mass fixers can be in the simulation of long-lived greenhouse gases using transport models based on the highly efficient semi-Lagrangian advection scheme. Mass fixers can have a large impact on the representation of the inter-hemispheric gradient of CO2 and CH4, a crucial feature of their distribution. This work is relevant for models simulating atmospheric composition that use semi-Lagrangian advection schemes both for climate and air quality applications.
André Butz, Anna Solvejg Dinger, Nicole Bobrowski, Julian Kostinek, Lukas Fieber, Constanze Fischerkeller, Giovanni Bruno Giuffrida, Frank Hase, Friedrich Klappenbach, Jonas Kuhn, Peter Lübcke, Lukas Tirpitz, and Qiansi Tu
Atmos. Meas. Tech., 10, 1–14, https://doi.org/10.5194/amt-10-1-2017, https://doi.org/10.5194/amt-10-1-2017, 2017
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Remote sensing of the gaseous composition of non-eruptive, passively degassing volcanic plumes can be a tool for volcano monitoring. Here, we report on a field study that demonstrates the feasibility of remotely measuring the volcanic enhancements of carbon dioxide, hydrogen fluoride, hydrogen chloride, sulfur dioxide, and bromine monoxide in the plume of Mt. Etna using portable spectroscopic instrumentation sampling the plume several kilometers downwind of the source.
Haili Hu, Otto Hasekamp, André Butz, André Galli, Jochen Landgraf, Joost Aan de Brugh, Tobias Borsdorff, Remco Scheepmaker, and Ilse Aben
Atmos. Meas. Tech., 9, 5423–5440, https://doi.org/10.5194/amt-9-5423-2016, https://doi.org/10.5194/amt-9-5423-2016, 2016
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In 2017, the TROPOMI spectrometer will be launched on board the Sentinel 5 Precursor satellite. It will deliver, among other things, daily global measurements of methane as part of the Copernicus atmospheric services.
In this paper, we present the algorithm that is used for operational data processing of the methane product from TROPOMI measurements of the shortwave and near-infrared spectral range, and we discuss its performance using realistic simulated measurements.
Jochen Landgraf, Joost aan de Brugh, Remco Scheepmaker, Tobias Borsdorff, Haili Hu, Sander Houweling, Andre Butz, Ilse Aben, and Otto Hasekamp
Atmos. Meas. Tech., 9, 4955–4975, https://doi.org/10.5194/amt-9-4955-2016, https://doi.org/10.5194/amt-9-4955-2016, 2016
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In 2016, the Sentinel 5 Precursor mission will be launched, with the TROPOMI instrument as its single payload. It will deliver daily global measurements of carbon monoxide for air quality monitoring as part of the Copernicus atmospheric services. In this paper, we focus on the operational data processing of the CO product from TROPOMI measurements of the shortwave infrared spectral range, and we discuss the algorithm's maturity.
Remco A. Scheepmaker, Joost aan de Brugh, Haili Hu, Tobias Borsdorff, Christian Frankenberg, Camille Risi, Otto Hasekamp, Ilse Aben, and Jochen Landgraf
Atmos. Meas. Tech., 9, 3921–3937, https://doi.org/10.5194/amt-9-3921-2016, https://doi.org/10.5194/amt-9-3921-2016, 2016
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We have developed an algorithm to measure HDO (heavy water) in the atmosphere using the TROPOMI satellite instrument, scheduled for launch in 2016. Giving an insight in the history of water vapour, these measurements will help to better understand the water cycle and its role in climate change. We use realistic measurement simulations to describe the performance of the algorithm, and show that TROPOMI will greatly improve and extend the HDO datasets from the previous SCIAMACHY and GOSAT missions.
Dejian Fu, Kevin W. Bowman, Helen M. Worden, Vijay Natraj, John R. Worden, Shanshan Yu, Pepijn Veefkind, Ilse Aben, Jochen Landgraf, Larrabee Strow, and Yong Han
Atmos. Meas. Tech., 9, 2567–2579, https://doi.org/10.5194/amt-9-2567-2016, https://doi.org/10.5194/amt-9-2567-2016, 2016
T. Borsdorff, P. Tol, J. E. Williams, J. de Laat, J. aan de Brugh, P. Nédélec, I. Aben, and J. Landgraf
Atmos. Meas. Tech., 9, 227–248, https://doi.org/10.5194/amt-9-227-2016, https://doi.org/10.5194/amt-9-227-2016, 2016
F. Klappenbach, M. Bertleff, J. Kostinek, F. Hase, T. Blumenstock, A. Agusti-Panareda, M. Razinger, and A. Butz
Atmos. Meas. Tech., 8, 5023–5038, https://doi.org/10.5194/amt-8-5023-2015, https://doi.org/10.5194/amt-8-5023-2015, 2015
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Measurements of atmospheric carbon dioxide and methane total vertical column abundance from onboard the research vessel "RV Polarstern" in March / April 2014. Along the journey on the Atlantic from Cape Town (South Africa) to Bremerhaven (Germany) we could reproduce the interhemispheric gradient of the target gases, and we compared the measurements with satellite and model data. Future campaigns could use the new mobility to characterize sources and sinks of carbon-dioxide and methane.
A. Butz, J. Orphal, R. Checa-Garcia, F. Friedl-Vallon, T. von Clarmann, H. Bovensmann, O. Hasekamp, J. Landgraf, T. Knigge, D. Weise, O. Sqalli-Houssini, and D. Kemper
Atmos. Meas. Tech., 8, 4719–4734, https://doi.org/10.5194/amt-8-4719-2015, https://doi.org/10.5194/amt-8-4719-2015, 2015
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The Geostationary Emission Explorer for Europe (G3E) is a mission concept for a greenhouse gas sounder in geostationary orbit. It is designed to provide column-average concentrations of carbon dioxide, methane, and carbon monoxide with high spatial and 2-hour temporal resolution throughout the central European continent. The prospective data density, precision and accuracy suggest G3E as a key component of a future carbon emission monitoring system.
A. Wassmann, T. Borsdorff, J. M. J. aan de Brugh, O. P. Hasekamp, I. Aben, and J. Landgraf
Atmos. Meas. Tech., 8, 4429–4451, https://doi.org/10.5194/amt-8-4429-2015, https://doi.org/10.5194/amt-8-4429-2015, 2015
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We present an extensive sensitivity study of retrieved total ozone columns from clear sky Global Ozone Monitoring Experiment 2 (GOME-2) measurements between 325 and 335nm which are corrected for instrument degradation. We address the choice of the scaling ozone profile, the choice of the radiative transfer solver, and the approximation of Earth's sphericity. Finally, we study the effect of instrument degradation on the retrieved total ozone columns for the first 4 years of the mission.
R. Checa-Garcia, J. Landgraf, A. Galli, F. Hase, V. A. Velazco, H. Tran, V. Boudon, F. Alkemade, and A. Butz
Atmos. Meas. Tech., 8, 3617–3629, https://doi.org/10.5194/amt-8-3617-2015, https://doi.org/10.5194/amt-8-3617-2015, 2015
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The future satellite missions Sentinel-5 and its precursor will monitor methane column average dry air mole fractions. The ambitious accuracy required on regional scales demands a characterization of the systematic error sources in which spectroscopic uncertainties are crucial. This study investigates how methane and water vapour spectroscopic errors propagate into retrieval errors, showing that spectroscopy-induced errors exceed 0.6% in large parts of the
world and are regionally correlated.
A. Babenhauserheide, S. Basu, S. Houweling, W. Peters, and A. Butz
Atmos. Chem. Phys., 15, 9747–9763, https://doi.org/10.5194/acp-15-9747-2015, https://doi.org/10.5194/acp-15-9747-2015, 2015
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We compare two different data assimilation systems for estimating sources and sinks of CO_2 from concentration measurements. The systems are CarbonTracker and TM5-4DVar, which have both been used in a number of scientific studies. We analyze the differences between both models as well as the sensitivity of the estimated sources and sinks to the observation coverage. The results provide a lower limit for the uncertainty of surface carbon fluxes with the current measurement network.
L. Wu, O. Hasekamp, B. van Diedenhoven, and B. Cairns
Atmos. Meas. Tech., 8, 2625–2638, https://doi.org/10.5194/amt-8-2625-2015, https://doi.org/10.5194/amt-8-2625-2015, 2015
R. A. Scheepmaker, C. Frankenberg, N. M. Deutscher, M. Schneider, S. Barthlott, T. Blumenstock, O. E. Garcia, F. Hase, N. Jones, E. Mahieu, J. Notholt, V. Velazco, J. Landgraf, and I. Aben
Atmos. Meas. Tech., 8, 1799–1818, https://doi.org/10.5194/amt-8-1799-2015, https://doi.org/10.5194/amt-8-1799-2015, 2015
L. Guanter, I. Aben, P. Tol, J. M. Krijger, A. Hollstein, P. Köhler, A. Damm, J. Joiner, C. Frankenberg, and J. Landgraf
Atmos. Meas. Tech., 8, 1337–1352, https://doi.org/10.5194/amt-8-1337-2015, https://doi.org/10.5194/amt-8-1337-2015, 2015
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This paper investigates the potential of the upcoming TROPOspheric Monitoring Instrument (TROPOMI) instrument for the retrieval of the chlorophyll fluorescence signal emitted in the 650–850nm spectral range by the photosynthetic machinery of green plants. We find that TROPOMI will allow substantial improvements in the space monitoring of fluorescence with respect to current spaceborne instruments such as GOME-2 and SCIAMACHY.
F. A. Stap, O. P. Hasekamp, and T. Röckmann
Atmos. Meas. Tech., 8, 1287–1301, https://doi.org/10.5194/amt-8-1287-2015, https://doi.org/10.5194/amt-8-1287-2015, 2015
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We present the capability of an aerosol retrieval algorithm, intended for multi-angle, multi-wavelength photopolarimetric measurements, to intrinsically screen for sub-pixel liquid water cloud contamination.
The screening is based on goodness-of-fit criteria. The algorithm has been applied to a synthetic data set of partially clouded scenes and (non-cloud-screened) POLDER3/PARASOL observations.
M. Reuter, M. Buchwitz, M. Hilker, J. Heymann, O. Schneising, D. Pillai, H. Bovensmann, J. P. Burrows, H. Bösch, R. Parker, A. Butz, O. Hasekamp, C. W. O'Dell, Y. Yoshida, C. Gerbig, T. Nehrkorn, N. M. Deutscher, T. Warneke, J. Notholt, F. Hase, R. Kivi, R. Sussmann, T. Machida, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 13739–13753, https://doi.org/10.5194/acp-14-13739-2014, https://doi.org/10.5194/acp-14-13739-2014, 2014
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Current knowledge about the European terrestrial biospheric carbon sink relies upon bottom-up and global surface flux inverse model estimates using in situ measurements. Our analysis of five satellite data sets comprises a regional inversion designed to be insensitive to potential retrieval biases and transport errors. We show that the satellite-derived sink is larger (1.0±0.3GtC/a) than previous estimates (0.4±0.4GtC/a).
R. Sander, P. Jöckel, O. Kirner, A. T. Kunert, J. Landgraf, and A. Pozzer
Geosci. Model Dev., 7, 2653–2662, https://doi.org/10.5194/gmd-7-2653-2014, https://doi.org/10.5194/gmd-7-2653-2014, 2014
B. Dils, M. Buchwitz, M. Reuter, O. Schneising, H. Boesch, R. Parker, S. Guerlet, I. Aben, T. Blumenstock, J. P. Burrows, A. Butz, N. M. Deutscher, C. Frankenberg, F. Hase, O. P. Hasekamp, J. Heymann, M. De Mazière, J. Notholt, R. Sussmann, T. Warneke, D. Griffith, V. Sherlock, and D. Wunch
Atmos. Meas. Tech., 7, 1723–1744, https://doi.org/10.5194/amt-7-1723-2014, https://doi.org/10.5194/amt-7-1723-2014, 2014
A. Galli, S. Guerlet, A. Butz, I. Aben, H. Suto, A. Kuze, N. M. Deutscher, J. Notholt, D. Wunch, P. O. Wennberg, D. W. T. Griffith, O. Hasekamp, and J. Landgraf
Atmos. Meas. Tech., 7, 1105–1119, https://doi.org/10.5194/amt-7-1105-2014, https://doi.org/10.5194/amt-7-1105-2014, 2014
T. Borsdorff, O. P. Hasekamp, A. Wassmann, and J. Landgraf
Atmos. Meas. Tech., 7, 523–535, https://doi.org/10.5194/amt-7-523-2014, https://doi.org/10.5194/amt-7-523-2014, 2014
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.
Cited articles
Aben, I., Hasekamp, O., and Hartmann, W.: Uncertainties in the space-based measurements of CO2 columns due to scattering in the Earth's atmosphere, J. Quant. Spectrosc. Ra., 104, 450–459, https://doi.org/10.1016/j.jqsrt.2006.09.013, 2007. a, b, c, d
Birk, M., Wagner, G., Loos, J., Wilzewski, J., Mondelain, D., Campargue, A., Hase, F., Orphal, J., Perrin, A., Tran, H., Daumont, L., Rotger-Languereau, M., Bigazzi, A., and Zehner, C.: Methane and water spectroscopic database for TROPOMI Sentinel 5 Precursor in the 2.3 µm region, EGU General Assembly, Vienna, Austria, 23–28 April 2017, EGU2017-14652, 2017. a
Blumenstock, T., Hase, F., Schneider, M., García, O. E., and Sepúlveda, E.: TCCON data from Izana (ES), Release GGG2014.R0, CaltechDATA [data set], https://doi.org/10.14291/TCCON.GGG2014.IZANA01.R0/1149295, 2014. a
Buchwitz, M., Reuter, M., Schneising, O., Hewson, W., Detmers, R. G., Boesch, H., Hasekamp, O., Aben, I., Bovensmann, H., Burrows, J., Butz, A., Chevallier, F., Dils, B., Frankenberg, C., Heymann, J., Lichtenberg, G., De Mazière, M., Notholt, J., Parker, R., Warneke, T., Zehner, C., Griffith, D. W. T., Deutscher, N., Kuze, A., Suto, H., and Wunch, D.: Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set, Remote Sens. Environ., 203, 276–295, https://doi.org/10.1016/j.rse.2016.12.027, 2017. a
Buchwitz, M., Aben, I., Armante, R., Boesch, H., Crevoisier, C., Di Noia, A., Hasekamp, O. P., Reuter, M., Schneising-Weigel, O., and Wu, L.: Algorithm Theoretical Basis Document (ATBD) – Main document for Greenhouse Gas (GHG: CO2 and CH4) data set CDR 3 (2003–2018), C3S project, Copernicus Climate Change Service, Project number: C3S_D312b_Lot2.1.3.2-v1.0_ATBD-GHG_MAIN_v3.1, 43 pp., https://www.iup.uni-bremen.de/carbon_ghg/docs/C3S/CDR3_2003-2018/ATBD/C3S_D312b_Lot2.1.3.2-v1.0_ATBD-GHG_MAIN_v3.1.pdf (last access: 8 November 2022), 2019. a, b
Butz, A., Hasekamp, O. P., Frankenberg, C., Vidot, J., and Aben, I.: CH4 retrievals from space-based solar backscatter measurements: Performance evaluation against simulated aerosol and cirrus loaded scenes, J. Geophys. Res., 115, D24302, https://doi.org/10.1029/2010JD014514, 2010. a
Butz, A., Guerlet, S., Hasekamp, O., Schepers, D., Galli, A., Aben, I., Frankenberg, C., Hartmann, J.-M., Tran, H., Kuze, A., Keppel-Aleks, G., Toon, G., Wunch, D., Wennberg, P., Deutscher, N., Griffith, D., Macatangay, R., Messerschmidt, J., Notholt, J., and Warneke, T.: Toward accurate CO2 and CH4 observations from GOSAT, Geophys. Res. Lett., 38, L14812, https://doi.org/10.1029/2011GL047888, 2011. a, b, c, d, e
Butz, A., Guerlet, S., Hasekamp, O. P., Kuze, A., and Suto, H.: Using ocean-glint scattered sunlight as a diagnostic tool for satellite remote sensing of greenhouse gases, Atmos. Meas. Tech., 6, 2509–2520, https://doi.org/10.5194/amt-6-2509-2013, 2013. a, b, c, d
Cogan, A. J., Boesch, H., Parker, R. J., Feng, L., Palmer, P. I., Blavier, J.-F. L., Deutscher, N. M., Macatangay, R., Notholt, J., Roehl, C., Warneke, T., and Wunch, D.: Atmospheric carbon dioxide retrieved from the Greenhouse gases Observing SATellite (GOSAT): Comparison with ground-based TCCON observations and GEOS-Chem model calculations, J. Geophys. Res., 117, D21301, https://doi.org/10.1029/2012JD018087, 2012. a
Cox, C. and Munk, W.: Measurement of the Roughness of the Sea Surface from Photographs of the Sun's Glitter, J. Opt. Soc. Am., 44, 838–850, https://doi.org/10.1364/JOSA.44.000838, 1954. a
Crisp, D., Fisher, B. M., O'Dell, C., Frankenberg, C., Basilio, R., Bösch, H., Brown, L. R., Castano, R., Connor, B., Deutscher, N. M., Eldering, A., Griffith, D., Gunson, M., Kuze, A., Mandrake, L., McDuffie, J., Messerschmidt, J., Miller, C. E., Morino, I., Natraj, V., Notholt, J., O'Brien, D. M., Oyafuso, F., Polonsky, I., Robinson, J., Salawitch, R., Sherlock, V., Smyth, M., Suto, H., Taylor, T. E., Thompson, D. R., Wennberg, P. O., Wunch, D., and Yung, Y. L.: The ACOS CO2 retrieval algorithm – Part II: Global X
de Graaf, M., de Haan, J. F., and Sanders, A.: Algorithm Theoretical Baseline Document of the Aerosol Layer Height, KNMI, De Bilt, The Netherlands, Report Number: S5P-KNMI-L2-0006-RP,
version 2.4.0, https://sentinel.esa.int/documents/247904/2476257/Sentinel-5P-TROPOMI-ATBD-Aerosol-Height (last access: 8 November 2022), 2021. a
De Mazière, M., Sha, M. K., Desmet, F., Hermans, C., Scolas, F., Kumps, N., Metzger, J.-M., Duflot, V., and Cammas, J.-P.: TCCON data from Réunion Island (RE), Release GGG2014.R0, CaltechDATA [data set], https://doi.org/10.14291/tccon.ggg2014.reunion01.R0/1149288, 2014. a
Griffith, D. W. T., Deutscher, N. M., Velazco, V. A., Wennberg, P. O., Yavin, Y., Keppel-Aleks, G., Washenfelder, R. A., Toon, G. C., Blavier, J.-F., Paton-Walsh, C., Jones, N. B., Kettlewell, G. C., Connor, B. J., Macatangay, R. C., Roehl, C., Ryczek, M., Glowacki, J., Culgan, T., and Bryant, G. W.:
TCCON data from Darwin (AU), Release GGG2014.R0, CaltechDATA [data set], https://doi.org/10.14291/tccon.ggg2014.darwin01.r0/1149290, 2017a. a, b
Griffith, D. W. T., Velazco, V. A., Deutscher, N. M., Paton-Walsh, C., Jones, N. B., Wilson, S. R., Macatangay, R. C., Kettlewell, G. C., Buchholz, R. R., and Riggenbach, M.: TCCON data from Wollongong (AU), Release GGG2014.R0, CaltechDATA [data set], https://doi.org/10.14291/tccon.ggg2014.wollongong01.r0/1149291, 2017b. a, b
Guerlet, S., Butz, A., Schepers, D., Basu, S., Hasekamp, O. P., Kuze, A., Yokota, T., Blavier, J., Deutscher, N. M., Griffith, D. W., Hase, F., Kyro, E., Morino, I., Sherlock, V., Sussmann, R., Galli, A., and Aben, I.: Impact of aerosol and thin cirrus on retrieving and validating XCO2 from GOSAT shortwave infrared measurements, J. Geophys. Res.-Atmos., 118, 4887–4905, https://doi.org/10.1002/jgrd.50332, 2013. a
Hase, F., Blumenstock, T., Dohe, S., Groß, J., and Kiel, M.: TCCON data from Karlsruhe (DE), Release GGG2014.R0, CaltechDATA [data set], https://doi.org/10.14291/tccon.ggg2014.karlsruhe01.r0/1149270, 2017. a
Hasekamp, O., Lorente, A., Hu, H., Butz, A., aan de Brugh, J., and Landgraf, J.: Algorithm Theoretical Baseline Document for Sentinel-5 Precursor methane retrieval, KNMI, De Bilt, The Netherlands, Document number: SRON-S5P-LEV2-RP-001, version 2.4.0, https://sentinels.copernicus.eu/documents/247904/2476257/Sentinel-5P-TROPOMI-ATBD-Methane-retrieval.pdf (last access: 8 November 2022), 2021. a
Houweling, S., Hartmann, W., Aben, I., Schrijver, H., Skidmore, J., Roelofs, G.-J., and Breon, F.-M.: Evidence of systematic errors in SCIAMACHY-observed CO2 due to aerosols, Atmos. Chem. Phys., 5, 3003–3013, https://doi.org/10.5194/acp-5-3003-2005, 2005. a
Iraci, L. T., Podolske, J. R., Hillyard, P. W., Roehl, C., Wennberg, P. O., Blavier, J.-F., Landeros, J., Allen, N., Wunch, D., Zavaleta, J., Quigley, E., Osterman, G. B., Albertson, R., Dunwoody, K., and Boyden, H.: TCCON data from Edwards (US), Release GGG2014.R1, CaltechDATA [data set], https://doi.org/10.14291/TCCON.GGG2014.EDWARDS01.R1/1255068, 2016. a, b
Irakulis-Loitxate, I., Guanter, L., Maasakkers, J. D., Zavala-Araiza, D., and Aben, I.: Satellites Detect Abatable Super-Emissions in One of the World's Largest Methane Hotspot Regions, Environ. Sci. Technol., 56, 2143–2152, 2022. a
Kawakami, S., Ohyama, H., Arai, K., Okumura, H., Taura, C., Fukamachi, T., and Sakashita, M.: TCCON data from Saga (JP), Release GGG2014.R0, CaltechDATA [data set], https://doi.org/10.14291/tccon.ggg2014.saga01.r0/1149283, 2017. a, b
Kivi, R. and Heikkinen, P.: Fourier transform spectrometer measurements of column CO2 at Sodankylä, Finland, Geosci. Instrum. Method. Data Syst., 5, 271–279, https://doi.org/10.5194/gi-5-271-2016, 2016. a
Kivi, R., Heikkinen, P., and Kyrö, E.: TCCON data from Sodankylä (FI), Release GGG2014.R0, CaltechDATA [data set], https://doi.org/10.14291/tccon.ggg2014.sodankyla01.r0/1149280, 2017. a
Landgraf, J., Hasekamp, O. P., Box, M. A., and Trautmann, T.: A linearized radiative transfer model for ozone profile retrieval using the analytical forward-adjoint perturbation theory approach, J. Geophys. Res., 106, 27291–27305, https://doi.org/10.1029/2001JD000636, 2001. a
Lorente, A., Borsdorff, T., Butz, A., Hasekamp, O., aan de Brugh, J., Schneider, A., Wu, L., Hase, F., Kivi, R., Wunch, D., Pollard, D. F., Shiomi, K., Deutscher, N. M., Velazco, V. A., Roehl, C. M., Wennberg, P. O., Warneke, T., and Landgraf, J.: Methane retrieved from TROPOMI: improvement of the data product and validation of the first 2 years of measurements, Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, 2021. a, b, c, d, e, f, g, h, i, j
Lorente, A., Borsdorff, T., Martinez Velarte, M. C., and Landgraf, J.: SRON S5P – RemoTeC scientific TROPOMI XCH4 dataset v18_17, Zenodo [data set], https://doi.org/10.5281/zenodo.7303388, 2022 (data also available at: https://ftp.sron.nl/open-access-data-2/TROPOMI/tropomi/ch4/18_17/, last access: 8 November 2022). a
Morino, I., Matsuzaki, T., and Horikawa, M.: TCCON data from Tsukuba (JP), 125HR, Release GGG2014.R1, CaltechDATA [data set], https://doi.org/10.14291/TCCON.GGG2014.TSUKUBA02.R1/1241486, 2016a. a
Morino, I., Yokozeki, N., Matsuzaki, T., and Horikawa, M.: TCCON data from Rikubetsu (JP), Release GGG2014.R1, CaltechDATA [data set], https://doi.org/10.14291/TCCON.GGG2014.RIKUBETSU01.R1/1242265, 2016b. a
O'Dell, C. W., Eldering, A., Wennberg, P. O., Crisp, D., Gunson, M. R., Fisher, B., Frankenberg, C., Kiel, M., Lindqvist, H., Mandrake, L., Merrelli, A., Natraj, V., Nelson, R. R., Osterman, G. B., Payne, V. H., Taylor, T. E., Wunch, D., Drouin, B. J., Oyafuso, F., Chang, A., McDuffie, J., Smyth, M., Baker, D. F., Basu, S., Chevallier, F., Crowell, S. M. R., Feng, L., Palmer, P. I., Dubey, M., García, O. E., Griffith, D. W. T., Hase, F., Iraci, L. T., Kivi, R., Morino, I., Notholt, J., Ohyama, H., Petri, C., Roehl, C. M., Sha, M. K., Strong, K., Sussmann, R., Te, Y., Uchino, O., and Velazco, V. A.: Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm, Atmos. Meas. Tech., 11, 6539–6576, https://doi.org/10.5194/amt-11-6539-2018, 2018. a
Pollard, D. F., Robinson, J., and Shiona, H.: TCCON data from Lauder (NZ), Release GGG2014.R0, CaltechDATA [data set], https://doi.org/10.14291/TCCON.GGG2014.LAUDER03.R0, 2019. a
Qu, Z., Jacob, D. J., Shen, L., Lu, X., Zhang, Y., Scarpelli, T. R., Nesser, H., Sulprizio, M. P., Maasakkers, J. D., Bloom, A. A., Worden, J. R., Parker, R. J., and Delgado, A. L.: Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments, Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, 2021. a
Schepers, D., aan de Brugh, J., Hahne, P., Butz, A., Hasekamp, O., and Landgraf, J.: LINTRAN v2.0: A linearised vector radiative transfer model for efficient simulation of satellite-born nadir-viewing reflection measurements of cloudy atmospheres, J. Quant. Spectrosc. Ra., 149, 347–359, https://doi.org/10.1016/j.jqsrt.2014.08.019, 2014. a
Sha, M. K., Langerock, B., Blavier, J.-F. L., Blumenstock, T., Borsdorff, T., Buschmann, M., Dehn, A., De Mazière, M., Deutscher, N. M., Feist, D. G., García, O. E., Griffith, D. W. T., Grutter, M., Hannigan, J. W., Hase, F., Heikkinen, P., Hermans, C., Iraci, L. T., Jeseck, P., Jones, N., Kivi, R., Kumps, N., Landgraf, J., Lorente, A., Mahieu, E., Makarova, M. V., Mellqvist, J., Metzger, J.-M., Morino, I., Nagahama, T., Notholt, J., Ohyama, H., Ortega, I., Palm, M., Petri, C., Pollard, D. F., Rettinger, M., Robinson, J., Roche, S., Roehl, C. M., Röhling, A. N., Rousogenous, C., Schneider, M., Shiomi, K., Smale, D., Stremme, W., Strong, K., Sussmann, R., Té, Y., Uchino, O., Velazco, V. A., Vigouroux, C., Vrekoussis, M., Wang, P., Warneke, T., Wizenberg, T., Wunch, D., Yamanouchi, S., Yang, Y., and Zhou, M.: Validation of methane and carbon monoxide from Sentinel-5 Precursor using TCCON and NDACC-IRWG stations, Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, 2021. a
Sherlock, V., Connor, B., Robinson, J., Shiona, H., Smale, D., and Pollard, D. F.: TCCON data from Lauder (NZ), 125HR, Release GGG2014.R0, CaltechDATA [data set], https://doi.org/10.14291/tccon.ggg2014.lauder02.r0/1149298, 2017. a
Siddans, R.: Algorithm Theoretical Baseline Document for S5P-NPP Cloud Processor, RAL Space, Document number: S5P-NPPC-RAL-ATBD-0001, https://sentinel.esa.int/documents/247904/2476257/Sentinel-5P-NPP-ATBD-NPP-Clouds (last access: 8 November 2022), 2016. a
Stein Zweers, D. C.: Algorithm Theoretical Baseline Document if the UV Aerosol Index, KNMI, De Bilt, The Netherlands, Document number: S5P-KNMI-L2-0008-RP,
https://sentinel.esa.int/documents/247904/2476257/Sentinel-5P-TROPOMI-ATBD-UV-Aerosol-Index.pdf (last access: 8 November 2022), 2021. a
Varon, D. J., McKeever, J., Jervis, D., Maasakkers, J. D., Pandey, S., Houweling, S., Aben, I., Scarpelli, T., and Jacob, D. J.: Satellite Discovery of Anomalously Large Methane Point Sources From Oil/Gas Production, Geophys. Res. Lett., 46, 13507–13516, https://doi.org/10.1029/2019GL083798, 2019. a
Varon, D. J., Jacob, D. J., Sulprizio, M., Estrada, L. A., Downs, W. B., Shen, L., Hancock, S. E., Nesser, H., Qu, Z., Penn, E., Chen, Z., Lu, X., Lorente, A., Tewari, A., and Randles, C. A.: Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations, Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022, 2022. a
Velazco, V. A., Morino, I., Uchino, O., Hori, A., Kiel, M., Bukosa, B., Deutscher, N. M., Sakai, T., Nagai, T., Bagtasa, G., Izumi, T., Yoshida, Y., and Griffith, D. W. T.: TCCON Philippines: First Measurement Results, Satellite Data and Model Comparisons in Southeast Asia, Remote Sens., 9, 1228, https://doi.org/10.3390/rs9121228, 2017. a
Warneke, T., Messerschmidt, J., Notholt, J., Weinzierl, C., Deutscher, N. M., Petri, C., and Grupe, P.: TCCON data from Orléans (FR), Release GGG2014.R0, CaltechDATA [data set], https://doi.org/10.14291/tccon.ggg2014.orleans01.r0/1149276, 2017. a
Wennberg, P. O., Roehl, C. M., Wunch, D., Toon, G. C., Blavier, J.-F., Washenfelder, R., Keppel-Aleks, G., Allen, N. T., and Ayers, J.: TCCON data from Park Falls (US), Release GGG2014.R1, CaltechDATA [data set], https://doi.org/10.14291/tccon.ggg2014.parkfalls01.r1, 2017a. a
Wennberg, P. O., Wunch, D., Roehl, C. M., Blavier, J.-F., Toon, G. C., and Allen, N. T.: TCCON data from Lamont (US), Release GGG2014.R1, CaltechDATA [data set], https://doi.org/10.14291/tccon.ggg2014.lamont01.r1/1255070, 2017c. a
Wu, L., Hasekamp, O., Hu, H., Landgraf, J., Butz, A., aan de Brugh, J., Aben, I., Pollard, D. F., Griffith, D. W. T., Feist, D. G., Koshelev, D., Hase, F., Toon, G. C., Ohyama, H., Morino, I., Notholt, J., Shiomi, K., Iraci, L., Schneider, M., de Mazière, M., Sussmann, R., Kivi, R., Warneke, T., Goo, T.-Y., and Té, Y.: Carbon dioxide retrieval from OCO-2 satellite observations using the RemoTeC algorithm and validation with TCCON measurements, Atmos. Meas. Tech., 11, 3111–3130, https://doi.org/10.5194/amt-11-3111-2018, 2018. a
Wu, L., aan de Brugh, J., Meijer, Y., Sierk, B., Hasekamp, O., Butz, A., and Landgraf, J.: XCO2 observations using satellite measurements with moderate spectral resolution: investigation using GOSAT and OCO-2 measurements, Atmos. Meas. Tech., 13, 713–729, https://doi.org/10.5194/amt-13-713-2020, 2020.
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Yoshida, Y., Kikuchi, N., Morino, I., Uchino, O., Oshchepkov, S., Bril, A., Saeki, T., Schutgens, N., Toon, G. C., Wunch, D., Roehl, C. M., Wennberg, P. O., Griffith, D. W. T., Deutscher, N. M., Warneke, T., Notholt, J., Robinson, J., Sherlock, V., Connor, B., Rettinger, M., Sussmann, R., Ahonen, P., Heikkinen, P., Kyrö, E., Mendonca, J., Strong, K., Hase, F., Dohe, S., and Yokota, T.: Improvement of the retrieval algorithm for GOSAT SWIR XCO2 and XCH4 and their validation using TCCON data, Atmos. Meas. Tech., 6, 1533–1547, https://doi.org/10.5194/amt-6-1533-2013, 2013. a, b, c, d
Zhou, M., Dils, B., Wang, P., Detmers, R., Yoshida, Y., O'Dell, C. W., Feist, D. G., Velazco, V. A., Schneider, M., and De Mazière, M.: Validation of TANSO-FTS/GOSAT XCO2 and XCH4 glint mode retrievals using TCCON data from near-ocean sites, Atmos. Meas. Tech., 9, 1415–1430, https://doi.org/10.5194/amt-9-1415-2016, 2016. a
Short summary
The TROPOspheric Monitoring Instrument (TROPOMI) performs observations over ocean in every orbit, enhancing the monitoring capabilities of methane from space. In the sun glint geometry the mirror-like reflection at the water surface provides a signal that is high enough to retrieve methane with high accuracy and precision. We present 4 years of methane concentrations over the ocean, and we assess its quality. We also show the importance of ocean observations to quantify total CH4 emissions.
The TROPOspheric Monitoring Instrument (TROPOMI) performs observations over ocean in every...
