Articles | Volume 10, issue 10
https://doi.org/10.5194/gmd-10-3695-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-3695-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Methods for assessment of models
| 
10 Oct 2017
Methods for assessment of models |
| 10 Oct 2017
Atmospheric inverse modeling via sparse reconstruction
Center for Industrial Mathematics, University of Bremen, Bremen, Germany
Scot M. Miller
Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA
Peter Maaß
Center for Industrial Mathematics, University of Bremen, Bremen, Germany
Justus Notholt
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Mathias Palm
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Thorsten Warneke
Institute of Environmental Physics, University of Bremen, Bremen, Germany
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Zhiting Wang, Nils Hase, Wenshou Tian, and Mengchu Tao
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-1096, https://doi.org/10.5194/acp-2021-1096, 2022
Publication in ACP not foreseen
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The distribution of trace gases in the stratosphere impacts the thermal and dynamical structures of the atmosphere. The spatial structure of the trace gases is determined by the residual circulation and stirring and mixing processes. Currently the stirring is purely constrained due to lack of observation. Here we develop a diagnosis for stirring mainly based on the trace gas contour. The method is applied for estimating stirring and mixing effects on methane concentration in a polar vortex.
Hanyu Liu, Felix R. Vogel, Misa Ishizawa, Zhen Zhang, Benjamin Poulter, Doug E. J. Worthy, Leyang Feng, Anna L. Gagné-Landmann, Ao Chen, Ziting Huang, Dylan C. Gaeta, Joe R. Melton, Douglas Chan, Vineet Yadav, Deborah Huntzinger, and Scot M. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2025-2150, https://doi.org/10.5194/egusphere-2025-2150, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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We find that the state-of-the-art process-based methane flux models have both lower flux magnitude and reduced inter-model uncertainty compared to a previous model inter-comparison from over a decade ago. Despite these improvements, methane flux estimates from process-based models are still likely too high compared to atmospheric observations. We also find that models with simpler parameterizations often result in better agreement with atmospheric observations in high-latitude North America.
Denghui Ji, Christoph Ritter, Xiaoyu Sun, Manuel Moser, Christiane Voigt, Mathias Palm, and Justus Notholt
EGUsphere, https://doi.org/10.5194/egusphere-2025-1932, https://doi.org/10.5194/egusphere-2025-1932, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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We discovered a process where large aerosols help small water droplets in Arctic clouds grow, even when conditions normally favor ice. Unlike the traditional view, this process may explain how liquid and ice can coexist in cold clouds. Based on theory and aircraft data, our findings provide new insight into the microphysics of mixed-phase clouds, which could improve understanding of how Arctic clouds affect climate.
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.
Denghui Ji, Mathias Palm, Matthias Buschmann, Kerstin Ebell, Marion Maturilli, Xiaoyu Sun, and Justus Notholt
Atmos. Chem. Phys., 25, 3889–3904, https://doi.org/10.5194/acp-25-3889-2025, https://doi.org/10.5194/acp-25-3889-2025, 2025
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Our study explores how certain aerosols, like sea salt, affect infrared heat radiation in the Arctic, potentially speeding up warming. We used advanced technology to measure aerosol composition and found that these particles grow with humidity, significantly increasing their heat-trapping effect in the infrared region, especially in winter. Our findings suggest these aerosols could be a key factor in Arctic warming, emphasizing the importance of understanding aerosols for climate prediction.
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.
Jonas Hachmeister, Debra Wunch, Erin McGee, Kimberly Strong, Rigel Kivi, Justus Notholt, Thorsten Warneke, and Matthias Buschmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-4055, https://doi.org/10.5194/egusphere-2024-4055, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Methane measurements from the Total Carbon Column Observing Network (TCCON) are important for climate research, especially in the Arctic where few measurements are available. We show that during early spring systematic errors are present in these data that are correlated to the presence of the polar vortex. These errors occur due to the usage of wrong methane prior shapes in the retrieval and can be alleviated by modifying the prior shape accordingly.
Jamal Makkor, Mathias Palm, Matthias Buschmann, Emmanuel Mahieu, Martyn P. Chipperfield, and Justus Notholt
Atmos. Meas. Tech., 18, 1105–1114, https://doi.org/10.5194/amt-18-1105-2025, https://doi.org/10.5194/amt-18-1105-2025, 2025
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During the years 1950 and 1951, Marcel Migeotte took regular solar measurements in the form of paper rolls at the Jungfraujoch site. These historical spectra proved to be valuable for atmospheric research and needed to be saved for posterity. Therefore, a digitization method which used image-processing techniques was developed to extract them from the historical paper rolls. This allowed them to be saved in a machine-readable format that is easily accessible to the scientific community.
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.
Aki Tsuruta, Akihiko Kuze, Kei Shiomi, Fumie Kataoka, Nobuhiro Kikuchi, Tuula Aalto, Leif Backman, Ella Kivimäki, Maria K. Tenkanen, Kathryn McKain, Omaira E. García, Frank Hase, Rigel Kivi, Isamu Morino, Hirofumi Ohyama, David F. Pollard, Mahesh K. Sha, Kimberly Strong, Ralf Sussmann, Yao Te, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, Minqiang Zhou, and Hiroshi Suto
EGUsphere, https://doi.org/10.5194/egusphere-2025-159, https://doi.org/10.5194/egusphere-2025-159, 2025
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Satellite data bring invaluable information about greenhouse gas emissions globally. We found that a new type of data from the Greenhouse Gas Observing Satellite (GOSAT), which contains information about methane in the lowest layer of Earth's atmosphere, could provide reliable estimates of recent methane emissions when combined with atmospheric modelling. Therefore, the use of such data is encouraged to improve emission quantification methods and advance our understanding of methane cycles.
Xiaoyu Sun, Katrin Müller, Mathias Palm, Christoph Ritter, Denghui Ji, Tim Balthasar Röpke, and Justus Notholt
EGUsphere, https://doi.org/10.5194/egusphere-2024-3981, https://doi.org/10.5194/egusphere-2024-3981, 2025
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We studied how air moves from the lower atmosphere to the stratosphere over the Tropical Western Pacific, a region with very cold temperatures high up. By using ground-based observations and tracking air movement, we found that during winter, the formation of thin cloud allow air to rise, while in summer, most of the air sinks down. This process changes the water vapor amount in the stratosphere, which influences the greenhouse effect and plays an important role in climate change.
Roeland Van Malderen, Anne M. Thompson, Debra E. Kollonige, Ryan M. Stauffer, Herman G. J. Smit, Eliane Maillard Barras, Corinne Vigouroux, Irina Petropavlovskikh, Thierry Leblanc, Valérie Thouret, Pawel Wolff, Peter Effertz, David W. Tarasick, Deniz Poyraz, Gérard Ancellet, Marie-Renée De Backer, Stéphanie Evan, Victoria Flood, Matthias M. Frey, James W. Hannigan, José L. Hernandez, Marco Iarlori, Bryan J. Johnson, Nicholas Jones, Rigel Kivi, Emmanuel Mahieu, Glen McConville, Katrin Müller, Tomoo Nagahama, Justus Notholt, Ankie Piters, Natalia Prats, Richard Querel, Dan Smale, Wolfgang Steinbrecht, Kimberly Strong, and Ralf Sussmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-3736, https://doi.org/10.5194/egusphere-2024-3736, 2025
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Tropospheric ozone is an important greenhouse gas and is an air pollutant. The time variability of tropospheric ozone is mainly driven by anthropogenic emissions. In this paper, we study the distribution and time variability of ozone from harmonized ground-based observations from five different measurement techniques. Our findings will provide clear standard references for atmospheric models and evolving tropospheric ozone satellite data for the 2000–2022 period.
Roeland Van Malderen, Zhou Zang, Kai-Lan Chang, Robin Björklund, Owen R. Cooper, Jane Liu, Eliane Maillard Barras, Corinne Vigouroux, Irina Petropavlovskikh, Thierry Leblanc, Valérie Thouret, Pawel Wolff, Peter Effertz, Audrey Gaudel, David W. Tarasick, Herman G. J. Smit, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Deniz Poyraz, Gérard Ancellet, Marie-Renée De Backer, Matthias M. Frey, James W. Hannigan, José L. Hernandez, Bryan J. Johnson, Nicholas Jones, Rigel Kivi, Emmanuel Mahieu, Isamu Morino, Glen McConville, Katrin Müller, Isao Murata, Justus Notholt, Ankie Piters, Maxime Prignon, Richard Querel, Vincenzo Rizi, Dan Smale, Wolfgang Steinbrecht, Kimberly Strong, and Ralf Sussmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-3745, https://doi.org/10.5194/egusphere-2024-3745, 2025
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Tropospheric ozone is an important greenhouse gas and an air pollutant, whose distribution and time variability is mainly governed by anthropogenic emissions and dynamics. In this paper, we assess regional trends of tropospheric ozone column amounts, based on two different approaches of merging or synthesizing ground-based observations and their trends within specific regions. Our findings clearly demonstrate regional trend differences, but also consistently higher pre- than post-COVID trends.
Malena Sabaté Landman, Julianne Chung, Jiahua Jiang, Scot M. Miller, and Arvind K. Saibaba
Geosci. Model Dev., 17, 8853–8872, https://doi.org/10.5194/gmd-17-8853-2024, https://doi.org/10.5194/gmd-17-8853-2024, 2024
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Making an informed decision about what prior information to incorporate or discard in an inverse model is important yet very challenging, as it is often not straightforward to distinguish between informative and non-informative variables. In this study, we develop a new approach for incorporating prior information in an inverse model using predictor variables, while simultaneously selecting the relevant predictor variables for the estimation of the unknown quantity of interest.
Henk Eskes, Athanasios Tsikerdekis, Melanie Ades, Mihai Alexe, Anna Carlin Benedictow, Yasmine Bennouna, Lewis Blake, Idir Bouarar, Simon Chabrillat, Richard Engelen, Quentin Errera, Johannes Flemming, Sebastien Garrigues, Jan Griesfeller, Vincent Huijnen, Luka Ilić, Antje Inness, John Kapsomenakis, Zak Kipling, Bavo Langerock, Augustin Mortier, Mark Parrington, Isabelle Pison, Mikko Pitkänen, Samuel Remy, Andreas Richter, Anja Schoenhardt, Michael Schulz, Valerie Thouret, Thorsten Warneke, Christos Zerefos, and Vincent-Henri Peuch
Atmos. Chem. Phys., 24, 9475–9514, https://doi.org/10.5194/acp-24-9475-2024, https://doi.org/10.5194/acp-24-9475-2024, 2024
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The Copernicus Atmosphere Monitoring Service (CAMS) provides global analyses and forecasts of aerosols and trace gases in the atmosphere. On 27 June 2023 a major upgrade, Cy48R1, became operational. Comparisons with in situ, surface remote sensing, aircraft, and balloon and satellite observations show that the new CAMS system is a significant improvement. The results quantify the skill of CAMS to forecast impactful events, such as wildfires, dust storms and air pollution peaks.
Hella van Asperen, Thorsten Warneke, Alessandro Carioca de Araújo, Bruce Forsberg, Sávio José Filgueiras Ferreira, Thomas Röckmann, Carina van der Veen, Sipko Bulthuis, Leonardo Ramos de Oliveira, Thiago de Lima Xavier, Jailson da Mata, Marta de Oliveira Sá, Paulo Ricardo Teixeira, Julie Andrews de França e Silva, Susan Trumbore, and Justus Notholt
Biogeosciences, 21, 3183–3199, https://doi.org/10.5194/bg-21-3183-2024, https://doi.org/10.5194/bg-21-3183-2024, 2024
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Carbon monoxide (CO) is regarded as an important indirect greenhouse gas. Soils can emit and take up CO, but, until now, uncertainty remains as to which process dominates in tropical rainforests. We present the first soil CO flux measurements from a tropical rainforest. Based on our observations, we report that tropical rainforest soils are a net source of CO. In addition, we show that valley streams and inundated areas are likely additional hot spots of CO in the ecosystem.
Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin Lan, Erin McGee, Kathryn McKain, John Miller, Isamu Morino, Justus Notholt, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Haris Riris, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Steven C. Wofsy, Minqiang Zhou, and Paul O. Wennberg
Earth Syst. Sci. Data, 16, 2197–2260, https://doi.org/10.5194/essd-16-2197-2024, https://doi.org/10.5194/essd-16-2197-2024, 2024
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This paper describes a new version, called GGG2020, of a data set containing column-integrated observations of greenhouse and related gases (including CO2, CH4, CO, and N2O) made by ground stations located around the world. Compared to the previous version (GGG2014), improvements have been made toward site-to-site consistency. This data set plays a key role in validating space-based greenhouse gas observations and in understanding the carbon cycle.
Alexandra Klemme, Thorsten Warneke, Heinrich Bovensmann, Matthias Weigelt, Jürgen Müller, Tim Rixen, Justus Notholt, and Claus Lämmerzahl
Hydrol. Earth Syst. Sci., 28, 1527–1538, https://doi.org/10.5194/hess-28-1527-2024, https://doi.org/10.5194/hess-28-1527-2024, 2024
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Satellite data help estimate groundwater depletion, but earlier assessments missed mass loss from river sediment. In the Ganges–Brahmaputra–Meghna (GBM) river system, sediment accounts for 4 % of the depletion. Correcting for sediment in the GBM mountains reduces estimated depletion by 14 %. It's important to note that the Himalayas' uplift may offset some sediment-induced mass loss. This understanding is vital for accurate water storage trend assessments and sustainable groundwater management.
Jean-François Müller, Trissevgeni Stavrakou, Glenn-Michael Oomen, Beata Opacka, Isabelle De Smedt, Alex Guenther, Corinne Vigouroux, Bavo Langerock, Carlos Augusto Bauer Aquino, Michel Grutter, James Hannigan, Frank Hase, Rigel Kivi, Erik Lutsch, Emmanuel Mahieu, Maria Makarova, Jean-Marc Metzger, Isamu Morino, Isao Murata, Tomoo Nagahama, Justus Notholt, Ivan Ortega, Mathias Palm, Amelie Röhling, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, and Alan Fried
Atmos. Chem. Phys., 24, 2207–2237, https://doi.org/10.5194/acp-24-2207-2024, https://doi.org/10.5194/acp-24-2207-2024, 2024
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Formaldehyde observations from satellites can be used to constrain the emissions of volatile organic compounds, but those observations have biases. Using an atmospheric model, aircraft and ground-based remote sensing data, we quantify these biases, propose a correction to the data, and assess the consequence of this correction for the evaluation of emissions.
Katrin Müller, Jordis S. Tradowsky, Peter von der Gathen, Christoph Ritter, Sharon Patris, Justus Notholt, and Markus Rex
Atmos. Chem. Phys., 24, 2169–2193, https://doi.org/10.5194/acp-24-2169-2024, https://doi.org/10.5194/acp-24-2169-2024, 2024
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The Palau Atmospheric Observatory is introduced as an ideal site to detect changes in atmospheric composition and dynamics above the remote tropical western Pacific. We focus on the ozone sounding program from 2016–2021, including El Niño 2016. The year-round high convective activity is reflected in dominant low tropospheric ozone and high relative humidity. Their seasonal distributions are unique compared to other tropical sites and are modulated by the Intertropical Convergence Zone.
Victoria A. Flood, Kimberly Strong, Cynthia H. Whaley, Kaley A. Walker, Thomas Blumenstock, James W. Hannigan, Johan Mellqvist, Justus Notholt, Mathias Palm, Amelie N. Röhling, Stephen Arnold, Stephen Beagley, Rong-You Chien, Jesper Christensen, Makoto Deushi, Srdjan Dobricic, Xinyi Dong, Joshua S. Fu, Michael Gauss, Wanmin Gong, Joakim Langner, Kathy S. Law, Louis Marelle, Tatsuo Onishi, Naga Oshima, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Manu A. Thomas, Svetlana Tsyro, and Steven Turnock
Atmos. Chem. Phys., 24, 1079–1118, https://doi.org/10.5194/acp-24-1079-2024, https://doi.org/10.5194/acp-24-1079-2024, 2024
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It is important to understand the composition of the Arctic atmosphere and how it is changing. Atmospheric models provide simulations that can inform policy. This study examines simulations of CH4, CO, and O3 by 11 models. Model performance is assessed by comparing results matched in space and time to measurements from five high-latitude ground-based infrared spectrometers. This work finds that models generally underpredict the concentrations of these gases in the Arctic troposphere.
Jonas Hachmeister, Oliver Schneising, Michael Buchwitz, John P. Burrows, Justus Notholt, and Matthias Buschmann
Atmos. Chem. Phys., 24, 577–595, https://doi.org/10.5194/acp-24-577-2024, https://doi.org/10.5194/acp-24-577-2024, 2024
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We quantified changes in atmospheric methane concentrations using satellite data and a dynamic linear model approach. We calculated global annual methane increases for the years 2019–2022, which are in good agreement with other sources. For zonal methane growth rates, we identified strong inter-hemispheric differences in 2019 and 2022. For 2022, we could attribute decreases in the global growth rate to the Northern Hemisphere, possibly related to a reduction in anthropogenic emissions.
Minqiang Zhou, Bavo Langerock, Mahesh Kumar Sha, Christian Hermans, Nicolas Kumps, Rigel Kivi, Pauli Heikkinen, Christof Petri, Justus Notholt, Huilin Chen, and Martine De Mazière
Atmos. Meas. Tech., 16, 5593–5608, https://doi.org/10.5194/amt-16-5593-2023, https://doi.org/10.5194/amt-16-5593-2023, 2023
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Atmospheric N2O and CH4 columns are successfully retrieved from low-resolution FTIR spectra recorded by a Bruker VERTEX 70. The 1-year measurements at Sodankylä show that the N2O total columns retrieved from 125HR and VERTEX 70 spectra are −0.3 ± 0.7 % with an R value of 0.93. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX spectra are 0.0 ± 0.8 % with an R value of 0.87. Such a technique can help to fill the gap in NDACC N2O and CH4 measurements.
Rafaella Chiarella, Matthias Buschmann, Joshua Laughner, Isamu Morino, Justus Notholt, Christof Petri, Geoffrey Toon, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 16, 3987–4007, https://doi.org/10.5194/amt-16-3987-2023, https://doi.org/10.5194/amt-16-3987-2023, 2023
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The goal is to establish a window and strategy for xCO2 retrieval from ground-based Fourier transform spectrometers for NDACC. In the study we describe the spectroscopy of the region, the locations and instruments used, and the methods of calculating the retrieved xCO2. We performed tests to assess the sensitivity to diverse factors and sources of errors while comparing the retrieval to a well-established xCO2 retrieval from TCCON.
Xiaoyu Sun, Mathias Palm, Katrin Müller, Jonas Hachmeister, and Justus Notholt
Atmos. Chem. Phys., 23, 7075–7090, https://doi.org/10.5194/acp-23-7075-2023, https://doi.org/10.5194/acp-23-7075-2023, 2023
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The tropical western Pacific (TWP) is an active interhemispheric transport region contributing significantly to the global climate. A method to determine the chemical equator was developed by model simulations of a virtual passive tracer to analyze transport in the tropics, with a focus on the TWP region. We compare the chemical equator with tropical rain belts and wind fields and obtain a vertical pattern of interhemispheric transport processes which shows tilt structure in certain seasons.
Yifan Guan, Gretchen Keppel-Aleks, Scott C. Doney, Christof Petri, Dave Pollard, Debra Wunch, Frank Hase, Hirofumi Ohyama, Isamu Morino, Justus Notholt, Kei Shiomi, Kim Strong, Rigel Kivi, Matthias Buschmann, Nicholas Deutscher, Paul Wennberg, Ralf Sussmann, Voltaire A. Velazco, and Yao Té
Atmos. Chem. Phys., 23, 5355–5372, https://doi.org/10.5194/acp-23-5355-2023, https://doi.org/10.5194/acp-23-5355-2023, 2023
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We characterize spatial–temporal patterns of interannual variability (IAV) in atmospheric CO2 based on NASA’s Orbiting Carbon Observatory-2 (OCO-2). CO2 variation is strongly impacted by climate events, with higher anomalies during El Nino years. We show high correlation in IAV between space-based and ground-based CO2 from long-term sites. Because OCO-2 has near-global coverage, our paper provides a roadmap to study IAV where in situ observation is sparse, such as open oceans and remote lands.
Antonio G. Bruno, Jeremy J. Harrison, Martyn P. Chipperfield, David P. Moore, Richard J. Pope, Christopher Wilson, Emmanuel Mahieu, and Justus Notholt
Atmos. Chem. Phys., 23, 4849–4861, https://doi.org/10.5194/acp-23-4849-2023, https://doi.org/10.5194/acp-23-4849-2023, 2023
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A 3-D chemical transport model, TOMCAT; satellite data; and ground-based observations have been used to investigate hydrogen cyanide (HCN) variability. We found that the oxidation by O(1D) drives the HCN loss in the middle stratosphere and the currently JPL-recommended OH reaction rate overestimates HCN atmospheric loss. We also evaluated two different ocean uptake schemes. We found them to be unrealistic, and we need to scale these schemes to obtain good agreement with HCN observations.
Denghui Ji, Mathias Palm, Christoph Ritter, Philipp Richter, Xiaoyu Sun, Matthias Buschmann, and Justus Notholt
Atmos. Meas. Tech., 16, 1865–1879, https://doi.org/10.5194/amt-16-1865-2023, https://doi.org/10.5194/amt-16-1865-2023, 2023
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To measuring aerosol components, a Fourier transform infrared spectrometer (FTIS) and a lidar are operated in Ny-Ålesund, Spitsbergen (78° N, 11° E). Using the FTIS, a retrieval algorithm is developed for dust, sea salt, black carbon, and sulfate. The distribution of aerosols or clouds is provided by lidar and used as an indicator for aerosol or cloud retrieval with the FTS. Thus, a two-instrument joint-observation scheme is designed and is used on the data measured from 2019 to the present.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Hao Yin, Youwen Sun, Justus Notholt, Mathias Palm, Chunxiang Ye, and Cheng Liu
Atmos. Chem. Phys., 22, 14401–14419, https://doi.org/10.5194/acp-22-14401-2022, https://doi.org/10.5194/acp-22-14401-2022, 2022
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Improved knowledge of the chemistry and drivers of surface ozone over the Qinghai-Tibet Plateau (QTP) is significant for regulatory and control purposes in this high-altitude region in the Himalayas. Our study investigates the processes and drivers of surface ozone anomalies by using machine-learning model-based meteorological normalization methods between 2015 and 2020 in urban areas over the QTP. This study can provide valuable implication for ozone mitigation over the QTP.
Youwen Sun, Hao Yin, Wei Wang, Changgong Shan, Justus Notholt, Mathias Palm, Ke Liu, Zhenyi Chen, and Cheng Liu
Atmos. Meas. Tech., 15, 4819–4834, https://doi.org/10.5194/amt-15-4819-2022, https://doi.org/10.5194/amt-15-4819-2022, 2022
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This study summarizes an overview of the status and perspective of GHG monitoring in China. This study not only improves our understanding with respect to the status, advances, and challenges of GHG monitoring in China but also presents an outlook for further improving GHG monitoring capacity in China.
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.
Taewon Cho, Julianne Chung, Scot M. Miller, and Arvind K. Saibaba
Geosci. Model Dev., 15, 5547–5565, https://doi.org/10.5194/gmd-15-5547-2022, https://doi.org/10.5194/gmd-15-5547-2022, 2022
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Atmospheric inverse modeling describes the process of estimating greenhouse gas fluxes or air pollution emissions at the Earth's surface using observations of these gases collected in the atmosphere. The launch of new satellites, the expansion of surface observation networks, and a desire for more detailed maps of surface fluxes have yielded numerous computational and statistical challenges. This article describes computationally efficient methods for large-scale atmospheric inverse modeling.
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.
Philipp Richter, Mathias Palm, Christine Weinzierl, Hannes Griesche, Penny M. Rowe, and Justus Notholt
Earth Syst. Sci. Data, 14, 2767–2784, https://doi.org/10.5194/essd-14-2767-2022, https://doi.org/10.5194/essd-14-2767-2022, 2022
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We present a dataset of cloud optical depths, effective radii and water paths from optically thin clouds observed in the Arctic around Svalbard. The data have been retrieved from infrared spectral radiance measured using a Fourier-transform infrared (FTIR) spectrometer. Besides a description of the measurements and retrieval technique, the data are put into context with results of corresponding measurements from microwave radiometer, lidar and cloud radar.
Alexandra Klemme, Tim Rixen, Denise Müller-Dum, Moritz Müller, Justus Notholt, and Thorsten Warneke
Biogeosciences, 19, 2855–2880, https://doi.org/10.5194/bg-19-2855-2022, https://doi.org/10.5194/bg-19-2855-2022, 2022
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Tropical peat-draining rivers contain high amounts of carbon. Surprisingly, measured carbon dioxide (CO2) emissions from those rivers are comparatively moderate. We compiled data from 10 Southeast Asian rivers and found that CO2 production within these rivers is hampered by low water pH, providing a natural threshold for CO2 emissions. Furthermore, we find that enhanced carbonate input, e.g. caused by human activities, suspends this natural threshold and causes increased CO2 emissions.
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Oliver Schneising, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Robert J. Parker, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Markus Rettinger, Coleen Roehl, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, and Thorsten Warneke
Atmos. Meas. Tech., 15, 3401–3437, https://doi.org/10.5194/amt-15-3401-2022, https://doi.org/10.5194/amt-15-3401-2022, 2022
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We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products.
In addition to an increased number of XCO2 data, v3 also includes products for XCH4 (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN2O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.
Carlos Alberti, Qiansi Tu, Frank Hase, Maria V. Makarova, Konstantin Gribanov, Stefani C. Foka, Vyacheslav Zakharov, Thomas Blumenstock, Michael Buchwitz, Christopher Diekmann, Benjamin Ertl, Matthias M. Frey, Hamud Kh. Imhasin, Dmitry V. Ionov, Farahnaz Khosrawi, Sergey I. Osipov, Maximilian Reuter, Matthias Schneider, and Thorsten Warneke
Atmos. Meas. Tech., 15, 2199–2229, https://doi.org/10.5194/amt-15-2199-2022, https://doi.org/10.5194/amt-15-2199-2022, 2022
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Satellite and ground-based observations at high latitudes are much sparser than at low or mid latitudes, which makes direct coincident comparisons between remote-sensing observations more difficult. Therefore, a method of scaling continuous CAMS model data to the ground-based observations is developed and used for creating virtual COCCON observations. These adjusted CAMS data are then used for satellite inter-comparison, showing good agreement in both Peterhof and Yekaterinburg cities.
Hao Yin, Youwen Sun, Justus Notholt, Mathias Palm, and Cheng Liu
Atmos. Chem. Phys., 22, 4167–4185, https://doi.org/10.5194/acp-22-4167-2022, https://doi.org/10.5194/acp-22-4167-2022, 2022
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In this study, we quantity the long-term variabilities and the underlying drivers of NO2 from 2005 to 2020 over the Yangtze River Delta (YRD), one of the most densely populated and highly industrialized city clusters in China. We reveal the significant effect of the Action Plan on the Prevention and Control of Air Pollution since 2013 adopted by the Chinese government to reduce NOx pollution. Our study can improve the understanding of pollution control measures on a regional scale.
Zhiting Wang, Nils Hase, Wenshou Tian, and Mengchu Tao
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-1096, https://doi.org/10.5194/acp-2021-1096, 2022
Publication in ACP not foreseen
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The distribution of trace gases in the stratosphere impacts the thermal and dynamical structures of the atmosphere. The spatial structure of the trace gases is determined by the residual circulation and stirring and mixing processes. Currently the stirring is purely constrained due to lack of observation. Here we develop a diagnosis for stirring mainly based on the trace gas contour. The method is applied for estimating stirring and mixing effects on methane concentration in a polar vortex.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
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We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
Youwen Sun, Hao Yin, Xiao Lu, Justus Notholt, Mathias Palm, Cheng Liu, Yuan Tian, and Bo Zheng
Atmos. Chem. Phys., 21, 18589–18608, https://doi.org/10.5194/acp-21-18589-2021, https://doi.org/10.5194/acp-21-18589-2021, 2021
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This study uses high-resolution nested-grid GEOS-Chem simulation, the eXtreme Gradient Boosting (XGBoost) machine learning method, and the exposure–response relationship to determine the drivers and evaluate the health risks of the unexpected surface O3 enhancements over the Sichuan Basin in 2020. These unexpected O3 enhancements were induced by meteorological anomalies and caused dramatically high health risks.
Joseph Mendonca, Ray Nassar, Christopher W. O'Dell, Rigel Kivi, Isamu Morino, Justus Notholt, Christof Petri, Kimberly Strong, and Debra Wunch
Atmos. Meas. Tech., 14, 7511–7524, https://doi.org/10.5194/amt-14-7511-2021, https://doi.org/10.5194/amt-14-7511-2021, 2021
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Machine learning has become an important tool for pattern recognition in many applications. In this study, we used a neural network to improve the data quality of OCO-2 measurements made at northern high latitudes. The neural network was trained and used as a binary classifier to filter out bad OCO-2 measurements in order to increase the accuracy and precision of OCO-2 XCO2 measurements in the Boreal and Arctic regions.
Nicole Jacobs, William R. Simpson, Kelly A. Graham, Christopher Holmes, Frank Hase, Thomas Blumenstock, Qiansi Tu, Matthias Frey, Manvendra K. Dubey, Harrison A. Parker, Debra Wunch, Rigel Kivi, Pauli Heikkinen, Justus Notholt, Christof Petri, and Thorsten Warneke
Atmos. Chem. Phys., 21, 16661–16687, https://doi.org/10.5194/acp-21-16661-2021, https://doi.org/10.5194/acp-21-16661-2021, 2021
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Spatial patterns of carbon dioxide seasonal cycle amplitude and summer drawdown timing derived from the OCO-2 satellite over northern high latitudes agree well with corresponding estimates from two models. The Asian boreal forest is anomalous with the largest amplitude and earliest seasonal drawdown. Modeled land contact tracers suggest that accumulated CO2 exchanges during atmospheric transport play a major role in shaping carbon dioxide seasonality in northern high-latitude regions.
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.
Youwen Sun, Hao Yin, Cheng Liu, Emmanuel Mahieu, Justus Notholt, Yao Té, Xiao Lu, Mathias Palm, Wei Wang, Changgong Shan, Qihou Hu, Min Qin, Yuan Tian, and Bo Zheng
Atmos. Chem. Phys., 21, 11759–11779, https://doi.org/10.5194/acp-21-11759-2021, https://doi.org/10.5194/acp-21-11759-2021, 2021
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The variability, sources, and transport of ethane (C2H6) over eastern China from 2015 to 2020 were studied using ground-based Fourier transform infrared (FTIR) spectroscopy and GEOS-Chem simulations. C2H6 variability is driven by both meteorological and emission factors. The reduction in C2H6 in recent years over eastern China points to air quality improvement in China.
Xiaoling Liu, August L. Weinbren, He Chang, Jovan M. Tadić, Marikate E. Mountain, Michael E. Trudeau, Arlyn E. Andrews, Zichong Chen, and Scot M. Miller
Geosci. Model Dev., 14, 4683–4696, https://doi.org/10.5194/gmd-14-4683-2021, https://doi.org/10.5194/gmd-14-4683-2021, 2021
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Observations of greenhouse gases have become far more numerous in recent years due to new satellite observations. The sheer size of these datasets makes it challenging to incorporate these data into statistical models and use these data to estimate greenhouse gas sources and sinks. In this paper, we develop an approach to reduce the size of these datasets while preserving the most information possible. We subsequently test this approach using satellite observations of carbon dioxide.
Dmitry V. Ionov, Maria V. Makarova, Frank Hase, Stefani C. Foka, Vladimir S. Kostsov, Carlos Alberti, Thomas Blumenstock, Thorsten Warneke, and Yana A. Virolainen
Atmos. Chem. Phys., 21, 10939–10963, https://doi.org/10.5194/acp-21-10939-2021, https://doi.org/10.5194/acp-21-10939-2021, 2021
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Megacities are a significant source of emissions of various substances in the atmosphere, including carbon dioxide, which is the most important anthropogenic greenhouse gas. In 2019–2020, the Emission Monitoring Mobile Experiment was carried out in St Petersburg, which is the second-largest industrial city in Russia. The results of this experiment, coupled with numerical modelling, helped to estimate the amount of CO2 emitted by the city. This value was twice as high as predicted.
Ilya Stanevich, Dylan B. A. Jones, Kimberly Strong, Martin Keller, Daven K. Henze, Robert J. Parker, Hartmut Boesch, Debra Wunch, Justus Notholt, Christof Petri, Thorsten Warneke, Ralf Sussmann, Matthias Schneider, Frank Hase, Rigel Kivi, Nicholas M. Deutscher, Voltaire A. Velazco, Kaley A. Walker, and Feng Deng
Atmos. Chem. Phys., 21, 9545–9572, https://doi.org/10.5194/acp-21-9545-2021, https://doi.org/10.5194/acp-21-9545-2021, 2021
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We explore the utility of a weak-constraint (WC) four-dimensional variational (4D-Var) data assimilation scheme for mitigating systematic errors in methane simulation in the GEOS-Chem model. We use data from the Greenhouse Gases Observing Satellite (GOSAT) and show that, compared to the traditional 4D-Var approach, the WC scheme improves the agreement between the model and independent observations. We find that the WC corrections to the model provide insight into the source of the errors.
Matthieu Dogniaux, Cyril Crevoisier, Raymond Armante, Virginie Capelle, Thibault Delahaye, Vincent Cassé, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. Garcia, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, David F. Pollard, Coleen M. Roehl, Kei Shiomi, Kimberly Strong, Yao Té, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 14, 4689–4706, https://doi.org/10.5194/amt-14-4689-2021, https://doi.org/10.5194/amt-14-4689-2021, 2021
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We present the Adaptable 4A Inversion (5AI), an implementation of the optimal estimation (OE) algorithm, relying on the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer model, that enables the retrieval of greenhouse gas atmospheric weighted columns from infrared measurements. It is tested on a sample of Orbiting Carbon Observatory-2 observations, and its results satisfactorily compare to several reference products, thus showing the reliability of 5AI OE implementation.
Youwen Sun, Hao Yin, Yuan Cheng, Qianggong Zhang, Bo Zheng, Justus Notholt, Xiao Lu, Cheng Liu, Yuan Tian, and Jianguo Liu
Atmos. Chem. Phys., 21, 9201–9222, https://doi.org/10.5194/acp-21-9201-2021, https://doi.org/10.5194/acp-21-9201-2021, 2021
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We quantified the variability, source, and transport of urban CO over the Himalayas and Tibetan Plateau (HTP) by using measurement, model simulation, and the analysis of meteorological fields. Urban CO over the HTP is dominated by anthropogenic and biomass burning emissions from local, South Asia and East Asia, and oxidation sources. The decreasing trends in surface CO since 2015 in most cities over the HTP are attributed to the reduction in local and transported CO emissions in recent years.
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Isamu Morino, Justus Notholt, Hirofumi Ohyama, Christof Petri, James R. Podolske, David F. Pollard, Mahesh Kumar Sha, Kei Shiomi, Ralf Sussmann, Yao Té, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 14, 3837–3869, https://doi.org/10.5194/amt-14-3837-2021, https://doi.org/10.5194/amt-14-3837-2021, 2021
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We present the first GOSAT and GOSAT-2 XCO2 data derived with the FOCAL retrieval algorithm. Comparisons of the GOSAT-FOCAL product with other data reveal long-term agreement within about 1 ppm over 1 decade, differences in seasonal variations of about 0.5 ppm, and a mean regional bias to ground-based TCCON data of 0.56 ppm with a mean scatter of 1.89 ppm. GOSAT-2-FOCAL data are preliminary only, but first comparisons show that they compare well with the GOSAT-FOCAL results and TCCON.
Holger Winkler, Takayoshi Yamada, Yasuko Kasai, Uwe Berger, and Justus Notholt
Atmos. Chem. Phys., 21, 7579–7596, https://doi.org/10.5194/acp-21-7579-2021, https://doi.org/10.5194/acp-21-7579-2021, 2021
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Sprites are electrical discharges above thunderstorms. We performed model simulations of the chemical processes in sprites to compare them with measurements of chemical perturbations above sprite-producing thunderstorms.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Youwen Sun, Hao Yin, Cheng Liu, Lin Zhang, Yuan Cheng, Mathias Palm, Justus Notholt, Xiao Lu, Corinne Vigouroux, Bo Zheng, Wei Wang, Nicholas Jones, Changong Shan, Min Qin, Yuan Tian, Qihou Hu, Fanhao Meng, and Jianguo Liu
Atmos. Chem. Phys., 21, 6365–6387, https://doi.org/10.5194/acp-21-6365-2021, https://doi.org/10.5194/acp-21-6365-2021, 2021
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This study mapped the drivers of HCHO variability from 2015 to 2019 over eastern China. Hydroxyl (OH) radical production rates from HCHO photolysis were evaluated. The relative contributions of emitted and photochemical sources to the observed HCHO abundance were analyzed. Contributions of various emission sources and geographical regions to the observed HCHO summertime enhancements were determined.
Hella van Asperen, João Rafael Alves-Oliveira, Thorsten Warneke, Bruce Forsberg, Alessandro Carioca de Araújo, and Justus Notholt
Biogeosciences, 18, 2609–2625, https://doi.org/10.5194/bg-18-2609-2021, https://doi.org/10.5194/bg-18-2609-2021, 2021
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Termites are insects that are highly abundant in tropical ecosystems. It is known that termites emit CH4, an important greenhouse gas, but their absolute emission remains uncertain. In the Amazon rainforest, we measured CH4 emissions from termite nests and groups of termites. In addition, we tested a fast and non-destructive field method to estimate termite nest colony size. We found that termites play a significant role in an ecosystem's CH4 budget and probably emit more than currently assumed.
Thomas Blumenstock, Frank Hase, Axel Keens, Denis Czurlok, Orfeo Colebatch, Omaira Garcia, David W. T. Griffith, Michel Grutter, James W. Hannigan, Pauli Heikkinen, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Erik Lutsch, Maria Makarova, Hamud K. Imhasin, Johan Mellqvist, Isamu Morino, Tomoo Nagahama, Justus Notholt, Ivan Ortega, Mathias Palm, Uwe Raffalski, Markus Rettinger, John Robinson, Matthias Schneider, Christian Servais, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, and Voltaire A. Velazco
Atmos. Meas. Tech., 14, 1239–1252, https://doi.org/10.5194/amt-14-1239-2021, https://doi.org/10.5194/amt-14-1239-2021, 2021
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This study investigates the level of channeling (optical resonances) of each FTIR spectrometer within the Network for the Detection of Atmospheric Composition Change (NDACC). Since the air gap of the beam splitter is a significant source of channeling, we propose new beam splitters with an increased wedge of the air gap. This study shows the potential for reducing channeling in the FTIR spectrometers operated by the NDACC, thereby increasing the quality of recorded spectra across the network.
Maria V. Makarova, Carlos Alberti, Dmitry V. Ionov, Frank Hase, Stefani C. Foka, Thomas Blumenstock, Thorsten Warneke, Yana A. Virolainen, Vladimir S. Kostsov, Matthias Frey, Anatoly V. Poberovskii, Yuri M. Timofeyev, Nina N. Paramonova, Kristina A. Volkova, Nikita A. Zaitsev, Egor Y. Biryukov, Sergey I. Osipov, Boris K. Makarov, Alexander V. Polyakov, Viktor M. Ivakhov, Hamud Kh. Imhasin, and Eugene F. Mikhailov
Atmos. Meas. Tech., 14, 1047–1073, https://doi.org/10.5194/amt-14-1047-2021, https://doi.org/10.5194/amt-14-1047-2021, 2021
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Fundamental understanding of the major processes driving climate change is a key problem which is to be solved, not only on a global but also on a regional scale. The Emission Monitoring Mobile Experiment (EMME) carried out in 2019 with two portable Bruker EM27/SUN spectrometers as core instruments provided new information on the emissions of greenhouse (CO2, CH4) and reactive (CO, NOx) gases from St. Petersburg (Russia), which is the largest northern megacity with a population of 5 million.
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.
Robert J. Parker, Alex Webb, Hartmut Boesch, Peter Somkuti, Rocio Barrio Guillo, Antonio Di Noia, Nikoleta Kalaitzi, Jasdeep S. Anand, Peter Bergamaschi, Frederic Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Coleen Roehl, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Thorsten Warneke, Paul O. Wennberg, and Debra Wunch
Earth Syst. Sci. Data, 12, 3383–3412, https://doi.org/10.5194/essd-12-3383-2020, https://doi.org/10.5194/essd-12-3383-2020, 2020
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This work presents the latest release of the University of Leicester GOSAT methane data and acts as the definitive description of this dataset. We detail the processing, validation and evaluation involved in producing these data and highlight its many applications. With now over a decade of global atmospheric methane observations, this dataset has helped, and will continue to help, us better understand the global methane budget and investigate how it may respond to a future changing climate.
Erik Lutsch, Kimberly Strong, Dylan B. A. Jones, Thomas Blumenstock, Stephanie Conway, Jenny A. Fisher, James W. Hannigan, Frank Hase, Yasuko Kasai, Emmanuel Mahieu, Maria Makarova, Isamu Morino, Tomoo Nagahama, Justus Notholt, Ivan Ortega, Mathias Palm, Anatoly V. Poberovskii, Ralf Sussmann, and Thorsten Warneke
Atmos. Chem. Phys., 20, 12813–12851, https://doi.org/10.5194/acp-20-12813-2020, https://doi.org/10.5194/acp-20-12813-2020, 2020
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This paper describes the use of a network of 10 Arctic and midlatitude ground-based FTIR measurement sites to detect enhancements of the wildfire tracers carbon monoxide, hydrogen cyanide, and ethane from 2003 to 2018. A tagged CO GEOS-Chem simulation is used for source attribution and to evaluate the relative contribution of CO sources to the FTIR measurements. The use of FTIR measurements allowed for the emission ratios of hydrogen cyanide and ethane to be quantified.
Mahesh Kumar Sha, Martine De Mazière, Justus Notholt, Thomas Blumenstock, Huilin Chen, Angelika Dehn, David W. T. Griffith, Frank Hase, Pauli Heikkinen, Christian Hermans, Alex Hoffmann, Marko Huebner, Nicholas Jones, Rigel Kivi, Bavo Langerock, Christof Petri, Francis Scolas, Qiansi Tu, and Damien Weidmann
Atmos. Meas. Tech., 13, 4791–4839, https://doi.org/10.5194/amt-13-4791-2020, https://doi.org/10.5194/amt-13-4791-2020, 2020
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We present the results of the 2017 FRM4GHG campaign at the Sodankylä TCCON site aimed at characterising the assessment of several low-cost portable instruments for precise solar absorption measurements of column-averaged dry-air mole fractions of CO2, CH4, and CO. The test instruments provided stable and precise measurements of these gases with quantified small biases. This qualifies the instruments to complement TCCON and expand the global coverage of ground-based measurements of these gases.
Ilya Stanevich, Dylan B. A. Jones, Kimberly Strong, Robert J. Parker, Hartmut Boesch, Debra Wunch, Justus Notholt, Christof Petri, Thorsten Warneke, Ralf Sussmann, Matthias Schneider, Frank Hase, Rigel Kivi, Nicholas M. Deutscher, Voltaire A. Velazco, Kaley A. Walker, and Feng Deng
Geosci. Model Dev., 13, 3839–3862, https://doi.org/10.5194/gmd-13-3839-2020, https://doi.org/10.5194/gmd-13-3839-2020, 2020
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Systematic errors in atmospheric models pose a challenge for inverse modeling studies of methane (CH4) emissions. We evaluated the CH4 simulation in the GEOS-Chem model at the horizontal resolutions of 4° × 5° and 2° × 2.5°. Our analysis identified resolution-dependent biases in the model, which we attributed to discrepancies between the two model resolutions in vertical transport in the troposphere and in stratosphere–troposphere exchange.
Philipp Richter, Mathias Palm, Christine Weinzierl, Hannes Griesche, Penny M. Rowe, and Justus Notholt
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-266, https://doi.org/10.5194/amt-2020-266, 2020
Preprint withdrawn
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Optically thin clouds containing low amounts of water are difficult to observe, but due to their frequent presence they have a non-neglectible impact on Earth's radiative budget. Here we present a retrieval for mixed-phase clouds from thermal-infared spectra, measured using a FTIR spectrometer. Even in situations where the atmospheric windows in the far-infrared are not applicable, cloud optical depths, effective droplet radii and water paths of mixed-phase clouds can be retrieved.
Corinne Vigouroux, Bavo Langerock, Carlos Augusto Bauer Aquino, Thomas Blumenstock, Zhibin Cheng, Martine De Mazière, Isabelle De Smedt, Michel Grutter, James W. Hannigan, Nicholas Jones, Rigel Kivi, Diego Loyola, Erik Lutsch, Emmanuel Mahieu, Maria Makarova, Jean-Marc Metzger, Isamu Morino, Isao Murata, Tomoo Nagahama, Justus Notholt, Ivan Ortega, Mathias Palm, Gaia Pinardi, Amelie Röhling, Dan Smale, Wolfgang Stremme, Kim Strong, Ralf Sussmann, Yao Té, Michel van Roozendael, Pucai Wang, and Holger Winkler
Atmos. Meas. Tech., 13, 3751–3767, https://doi.org/10.5194/amt-13-3751-2020, https://doi.org/10.5194/amt-13-3751-2020, 2020
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We validate the TROPOMI HCHO product with ground-based FTIR (Fourier-transform infrared) measurements from 25 stations. We find that TROPOMI overestimates HCHO under clean conditions, while it underestimates it at high HCHO levels. Both TROPOMI precision and accuracy reach the pre-launch requirements, and its precision can even be 2 times better. The observed TROPOMI seasonal variability is in agreement with the FTIR data. The TROPOMI random uncertainty and data filtering should be refined.
Youwen Sun, Cheng Liu, Lin Zhang, Mathias Palm, Justus Notholt, Hao Yin, Corinne Vigouroux, Erik Lutsch, Wei Wang, Changong Shan, Thomas Blumenstock, Tomoo Nagahama, Isamu Morino, Emmanuel Mahieu, Kimberly Strong, Bavo Langerock, Martine De Mazière, Qihou Hu, Huifang Zhang, Christof Petri, and Jianguo Liu
Atmos. Chem. Phys., 20, 5437–5456, https://doi.org/10.5194/acp-20-5437-2020, https://doi.org/10.5194/acp-20-5437-2020, 2020
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We present multiyear time series of ground-based Fourier-transform infrared spectroscopy measurements of HCN in densely populated eastern China. The seasonality and interannual variability of tropospheric HCN columns were investigated. The potential sources that drive the observed HCN seasonality and interannual variability were determined using a GEOS-Chem tagged CO simulation, global fire maps, and potential source contribution function values calculated using HYSPLIT back trajectories.
Scot M. Miller, Arvind K. Saibaba, Michael E. Trudeau, Marikate E. Mountain, and Arlyn E. Andrews
Geosci. Model Dev., 13, 1771–1785, https://doi.org/10.5194/gmd-13-1771-2020, https://doi.org/10.5194/gmd-13-1771-2020, 2020
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New observations of greenhouse gases from satellites and aircraft provide an unprecedented window into global carbon sources and sinks. However, these new datasets also present enormous computational challenges due to the sheer number of observations. In this article, we discuss the challenges of estimating greenhouse gas source and sinks using very large atmospheric datasets and evaluate several strategies for overcoming these challenges.
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.
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 20, 323–331, https://doi.org/10.5194/acp-20-323-2020, https://doi.org/10.5194/acp-20-323-2020, 2020
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes CO2 in the atmosphere. The satellite measures radiation, and these measurements are then converted to an estimate of atmospheric CO2. This conversion or retrieval algorithm has improved markedly since the satellite launch. We find that these improvements in the CO2 retrieval are having a potentially transformative effect on satellite-based estimates of the global biospheric carbon balance.
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.
Minqiang Zhou, Bavo Langerock, Mahesh Kumar Sha, Nicolas Kumps, Christian Hermans, Christof Petri, Thorsten Warneke, Huilin Chen, Jean-Marc Metzger, Rigel Kivi, Pauli Heikkinen, Michel Ramonet, and Martine De Mazière
Atmos. Meas. Tech., 12, 6125–6141, https://doi.org/10.5194/amt-12-6125-2019, https://doi.org/10.5194/amt-12-6125-2019, 2019
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In this study, CH4 vertical profile is retrieved by SFIT4 code from FTIR NIR spectra based on six sites during 2016–2017. The degree of freedom for signal of the SFIT4NIR retrieval is about 2.4, with two distinct species of information in the troposphere and in the stratosphere. By comparison against other measurements, e.g. TCCON standard products, satellite observations and AirCore measurements, the uncertainties of the SFIT4NIR total column and partial columns are estimated and discussed.
Minqiang Zhou, Bavo Langerock, Corinne Vigouroux, Mahesh Kumar Sha, Christian Hermans, Jean-Marc Metzger, Huilin Chen, Michel Ramonet, Rigel Kivi, Pauli Heikkinen, Dan Smale, David F. Pollard, Nicholas Jones, Voltaire A. Velazco, Omaira E. García, Matthias Schneider, Mathias Palm, Thorsten Warneke, and Martine De Mazière
Atmos. Meas. Tech., 12, 5979–5995, https://doi.org/10.5194/amt-12-5979-2019, https://doi.org/10.5194/amt-12-5979-2019, 2019
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The differences between the TCCON and NDACC XCO measurements are investigated and discussed based on six NDACC–TCCON sites (Ny-Ålesund, Bremen, Izaña, Saint-Denis, Wollongong and Lauder) using data over the period 2007–2017. The smoothing errors from both TCCON and NDACC measurements are estimated. In addition, the scaling factor of the TCCON XCO data is reassessed by comparing with the AirCore measurements at Sodankylä and Orléans.
Susan S. Kulawik, Sean Crowell, David Baker, Junjie Liu, Kathryn McKain, Colm Sweeney, Sebastien C. Biraud, Steve Wofsy, Christopher W. O'Dell, Paul O. Wennberg, Debra Wunch, Coleen M. Roehl, Nicholas M. Deutscher, Matthäus Kiel, David W. T. Griffith, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Mazière, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, Dave F. Pollard, Isamu Morino, Osamu Uchino, Frank Hase, Dietrich G. Feist, Sébastien Roche, Kimberly Strong, Rigel Kivi, Laura Iraci, Kei Shiomi, Manvendra K. Dubey, Eliezer Sepulveda, Omaira Elena Garcia Rodriguez, Yao Té, Pascal Jeseck, Pauli Heikkinen, Edward J. Dlugokencky, Michael R. Gunson, Annmarie Eldering, David Crisp, Brendan Fisher, and Gregory B. Osterman
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-257, https://doi.org/10.5194/amt-2019-257, 2019
Publication in AMT not foreseen
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This paper provides a benchmark of OCO-2 v8 and ACOS-GOSAT v7.3 XCO2 and lowermost tropospheric (LMT) errors. The paper focuses on the systematic errors and subtracts out validation, co-location, and random errors, looks at the correlation scale-length (spatially and temporally) of systematic errors, finding that the scale lengths are similar to bias correction scale-lengths. The assimilates of the bias correction term is used to place an error on fluxes estimates.
Jacob K. Hedelius, Tai-Long He, Dylan B. A. Jones, Bianca C. Baier, Rebecca R. Buchholz, Martine De Mazière, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Laura T. Iraci, Pascal Jeseck, Matthäus Kiel, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Sébastien Roche, Coleen M. Roehl, Matthias Schneider, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Colm Sweeney, Yao Té, Osamu Uchino, Voltaire A. Velazco, Wei Wang, Thorsten Warneke, Paul O. Wennberg, Helen M. Worden, and Debra Wunch
Atmos. Meas. Tech., 12, 5547–5572, https://doi.org/10.5194/amt-12-5547-2019, https://doi.org/10.5194/amt-12-5547-2019, 2019
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We seek ways to improve the accuracy of column measurements of carbon monoxide (CO) – an important tracer of pollution – made from the MOPITT satellite instrument. We devise a filtering scheme which reduces the scatter and also eliminates bias among the MOPITT detectors. Compared to ground-based observations, MOPITT measurements are about 6 %–8 % higher. When MOPITT data are implemented in a global assimilation model, they tend to reduce the model mismatch with aircraft measurements.
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.
Franziska Schranz, Brigitte Tschanz, Rolf Rüfenacht, Klemens Hocke, Mathias Palm, and Niklaus Kämpfer
Atmos. Chem. Phys., 19, 9927–9947, https://doi.org/10.5194/acp-19-9927-2019, https://doi.org/10.5194/acp-19-9927-2019, 2019
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The dynamics of the Arctic middle atmosphere above Ny-Ålesund, Svalbard (79° N, 12° E) is investigated using 3 years of H2O and O3 measurements from ground-based microwave radiometers. We found the signals of atmospheric phenomena like sudden stratospheric warmings, polar vortex shifts, effective descent rates of water vapour and periodicities in our data. Additionally, a comprehensive intercomparison is performed with models and measurements from ground-based, in situ and satellite instruments.
Niall J. Ryan, Mathias Palm, Christoph G. Hoffmann, Jens Goliasch, and Justus Notholt
Atmos. Meas. Tech., 12, 4077–4089, https://doi.org/10.5194/amt-12-4077-2019, https://doi.org/10.5194/amt-12-4077-2019, 2019
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We present a new ground-based instrument (CORAM) that measures atmospheric carbon monoxide (CO) concentrations within approximately 47–87 km in altitude with a 1 h time resolution. The measurements are made at Ny-Ålesund (79° N), Svalbard, and add much-needed coverage to the high Arctic. The first measured CO profiles from winter 2017/2018 are compared to co-located measurements from the Aura MLS satellite instrument and show agreement on daily and monthly timescales.
Temesgen Yirdaw Berhe, Gizaw Mengistu Tsidu, Thomas Blumenstock, Frank Hase, Thomas von Clarmann, Justus Notholt, and Emmanuel Mahieu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-209, https://doi.org/10.5194/amt-2019-209, 2019
Revised manuscript not accepted
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This study aims to assess the latitudinal variation of MIPAS version
V5R_CH4_220 and V5R_CH4_224 uncertainty. Furthermore, we analyze the relationship between these uncertainties and the variability of water vapor. Mainly, the high uncertainty found in tropics for MIPAS CH4 220 is highly associated with variability of water vapour. However, this effect has been reduced in the new updated MIPAS CH4 224 datasets due to jointly fitted water profile with methane.
Anna Agustí-Panareda, Michail Diamantakis, Sébastien Massart, Frédéric Chevallier, Joaquín Muñoz-Sabater, Jérôme Barré, Roger Curcoll, Richard Engelen, Bavo Langerock, Rachel M. Law, Zoë Loh, Josep Anton Morguí, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Coleen Roehl, Alex T. Vermeulen, Thorsten Warneke, and Debra Wunch
Atmos. Chem. Phys., 19, 7347–7376, https://doi.org/10.5194/acp-19-7347-2019, https://doi.org/10.5194/acp-19-7347-2019, 2019
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This paper demonstrates the benefits of using global models with high horizontal resolution to represent atmospheric CO2 patterns associated with evolving weather. The modelling of CO2 weather is crucial to interpret the variability from ground-based and satellite CO2 observations, which can then be used to infer CO2 fluxes in atmospheric inversions. The benefits of high resolution come from an improved representation of the topography, winds, tracer transport and CO2 flux distribution.
Debra Wunch, Dylan B. A. Jones, Geoffrey C. Toon, Nicholas M. Deutscher, Frank Hase, Justus Notholt, Ralf Sussmann, Thorsten Warneke, Jeroen Kuenen, Hugo Denier van der Gon, Jenny A. Fisher, and Joannes D. Maasakkers
Atmos. Chem. Phys., 19, 3963–3980, https://doi.org/10.5194/acp-19-3963-2019, https://doi.org/10.5194/acp-19-3963-2019, 2019
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We used five atmospheric observatories in Europe measuring total column dry-air mole fractions of methane and carbon monoxide to infer methane emissions in the area between the observatories. We find that the methane emissions are overestimated by the state-of-the-art inventories, and that this is likely due, at least in part, to the inventory disaggregation. We find that there is significant uncertainty in the carbon monoxide inventories that requires further investigation.
Minqiang Zhou, Bavo Langerock, Kelley C. Wells, Dylan B. Millet, Corinne Vigouroux, Mahesh Kumar Sha, Christian Hermans, Jean-Marc Metzger, Rigel Kivi, Pauli Heikkinen, Dan Smale, David F. Pollard, Nicholas Jones, Nicholas M. Deutscher, Thomas Blumenstock, Matthias Schneider, Mathias Palm, Justus Notholt, James W. Hannigan, and Martine De Mazière
Atmos. Meas. Tech., 12, 1393–1408, https://doi.org/10.5194/amt-12-1393-2019, https://doi.org/10.5194/amt-12-1393-2019, 2019
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N2O is an important atmospheric gas which is observed by two ground-based FTIR networks (TCCON and NDACC). The difference between NDACC and TCCON XN2O measurements is discussed. It is found that the bias between the two networks is within their combined uncertainties. However, TCCON measurements are affected by a priori profiles. In addition, the TCCON and NDACC N2O measurements are compared with the GEOS-Chem model simulations.
Denise Müller-Dum, Thorsten Warneke, Tim Rixen, Moritz Müller, Antje Baum, Aliki Christodoulou, Joanne Oakes, Bradley D. Eyre, and Justus Notholt
Biogeosciences, 16, 17–32, https://doi.org/10.5194/bg-16-17-2019, https://doi.org/10.5194/bg-16-17-2019, 2019
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Southeast Asian peat-draining rivers are potentially strong sources of carbon to the atmosphere due to the large amounts of organic carbon stored in those ecosystems. We present the first assessment of CO2 emissions from the Rajang River, the largest peat-draining river in Malaysia. The peatlands’ influence on the CO2 emissions from the Rajang River was smaller than expected, probably due to their proximity to the coast. Therefore, the Rajang was only a moderate source of CO2 to the atmosphere.
Christopher W. O'Dell, Annmarie Eldering, Paul O. Wennberg, David Crisp, Michael R. Gunson, Brendan Fisher, Christian Frankenberg, Matthäus Kiel, Hannakaisa Lindqvist, Lukas Mandrake, Aronne Merrelli, Vijay Natraj, Robert R. Nelson, Gregory B. Osterman, Vivienne H. Payne, Thomas E. Taylor, Debra Wunch, Brian J. Drouin, Fabiano Oyafuso, Albert Chang, James McDuffie, Michael Smyth, David F. Baker, Sourish Basu, Frédéric Chevallier, Sean M. R. Crowell, Liang Feng, Paul I. Palmer, Mavendra Dubey, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, Hirofumi Ohyama, Christof Petri, Coleen M. Roehl, Mahesh K. Sha, Kimberly Strong, Ralf Sussmann, Yao Te, Osamu Uchino, and Voltaire A. Velazco
Atmos. Meas. Tech., 11, 6539–6576, https://doi.org/10.5194/amt-11-6539-2018, https://doi.org/10.5194/amt-11-6539-2018, 2018
Youwen Sun, Cheng Liu, Mathias Palm, Corinne Vigouroux, Justus Notholt, Qihou Hu, Nicholas Jones, Wei Wang, Wenjing Su, Wenqiang Zhang, Changong Shan, Yuan Tian, Xingwei Xu, Martine De Mazière, Minqiang Zhou, and Jianguo Liu
Atmos. Chem. Phys., 18, 14569–14583, https://doi.org/10.5194/acp-18-14569-2018, https://doi.org/10.5194/acp-18-14569-2018, 2018
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The seasonal evolution of O3 and its photochemical production regime in a polluted region of eastern China between 2014 and 2017 was investigated using FTS observations. We observed a broad summer O3 maximum in Hefei, China, and the ozone production is mainly NOx limited in spring and summer and is mainly VOC or mixed VOC–NOx limited in autumn and winter.
Minqiang Zhou, Bavo Langerock, Corinne Vigouroux, Mahesh Kumar Sha, Michel Ramonet, Marc Delmotte, Emmanuel Mahieu, Whitney Bader, Christian Hermans, Nicolas Kumps, Jean-Marc Metzger, Valentin Duflot, Zhiting Wang, Mathias Palm, and Martine De Mazière
Atmos. Chem. Phys., 18, 13881–13901, https://doi.org/10.5194/acp-18-13881-2018, https://doi.org/10.5194/acp-18-13881-2018, 2018
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This study focuses on atmospheric CO and CH4 time series and seasonal variations on Reunion Island based on in situ and FTIR measurements from two sites, Saint Denis and Maido. Ground-based in situ and FTIR (NDACC and TCCON) measurements are used to show their complementarity with regards to obtaining the CO and CH4 concentrations at the surface and in the troposphere and stratosphere. FLEXPART and GEOS-Chem models are applied to understand the seasonal variations of CO and CH4 at this site.
Corinne Vigouroux, Carlos Augusto Bauer Aquino, Maite Bauwens, Cornelis Becker, Thomas Blumenstock, Martine De Mazière, Omaira García, Michel Grutter, César Guarin, James Hannigan, Frank Hase, Nicholas Jones, Rigel Kivi, Dmitry Koshelev, Bavo Langerock, Erik Lutsch, Maria Makarova, Jean-Marc Metzger, Jean-François Müller, Justus Notholt, Ivan Ortega, Mathias Palm, Clare Paton-Walsh, Anatoly Poberovskii, Markus Rettinger, John Robinson, Dan Smale, Trissevgeni Stavrakou, Wolfgang Stremme, Kim Strong, Ralf Sussmann, Yao Té, and Geoffrey Toon
Atmos. Meas. Tech., 11, 5049–5073, https://doi.org/10.5194/amt-11-5049-2018, https://doi.org/10.5194/amt-11-5049-2018, 2018
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A few ground-based stations have provided time series of HCHO columns until now, which was not optimal for providing good diagnostics for satellite or model validation. In this work, HCHO time series have been determined in a harmonized way at 21 stations ensuring, in addition to a better spatial and level of abundances coverage, that internal biases within the network have been minimized. This data set shows consistent good agreement with model data and is ready for future satellite validation.
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
Youwen Sun, Mathias Palm, Cheng Liu, Frank Hase, David Griffith, Christine Weinzierl, Christof Petri, Wei Wang, and Justus Notholt
Atmos. Meas. Tech., 11, 2879–2896, https://doi.org/10.5194/amt-11-2879-2018, https://doi.org/10.5194/amt-11-2879-2018, 2018
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We simulated instrumental line shape (ILS) degradations with respect to typical types of misalignment, and compared their influence on each NDACC gas. The requirements to suppress the ILS-degradation-related biases within a specified accuracy for all NDACC gases were deduced.
Scot M. Miller, Anna M. Michalak, Vineet Yadav, and Jovan M. Tadić
Atmos. Chem. Phys., 18, 6785–6799, https://doi.org/10.5194/acp-18-6785-2018, https://doi.org/10.5194/acp-18-6785-2018, 2018
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes CO2 in the atmosphere globally. We evaluate the extent to which current OCO-2 observations can inform scientific understanding of the biospheric carbon balance. We find that current observations are best-equipped to constrain the biospheric carbon balance across continental or hemispheric regions and provide limited information on smaller regions.
Franziska Schranz, Susana Fernandez, Niklaus Kämpfer, and Mathias Palm
Atmos. Chem. Phys., 18, 4113–4130, https://doi.org/10.5194/acp-18-4113-2018, https://doi.org/10.5194/acp-18-4113-2018, 2018
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We present 1 year of ozone measurements form two ground-based microwave radiometers located at Ny-Ålesund, Svalbard. The ozone measurements cover an altitude range of 25–70 km altitude and have a high time resolution of 1–2 h. With these datasets and model data a comprehensive analysis of the ozone diurnal cycle in the Arctic is performed for the different insolation conditions throughout the year. In the stratosphere we find a diurnal cycle which persists over the whole polar day.
Niall J. Ryan, Douglas E. Kinnison, Rolando R. Garcia, Christoph G. Hoffmann, Mathias Palm, Uwe Raffalski, and Justus Notholt
Atmos. Chem. Phys., 18, 1457–1474, https://doi.org/10.5194/acp-18-1457-2018, https://doi.org/10.5194/acp-18-1457-2018, 2018
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We used model output and instrument data to assess how well polar atmospheric descent rates can be derived using concentration measurements of long-lived gases in the atmosphere. The results indicate that the method incurs errors as large as the descent rates, and often leads to a misinterpretation of the direction of air motion. The rates derived using this method do not appear to represent the mean vertical wind in the middle atmosphere, and we suggest an alternate definition.
Zhiting Wang, Thorsten Warneke, Nicholas M. Deutscher, Justus Notholt, Ute Karstens, Marielle Saunois, Matthias Schneider, Ralf Sussmann, Harjinder Sembhi, David W. T. Griffith, Dave F. Pollard, Rigel Kivi, Christof Petri, Voltaire A. Velazco, Michel Ramonet, and Huilin Chen
Atmos. Chem. Phys., 17, 13283–13295, https://doi.org/10.5194/acp-17-13283-2017, https://doi.org/10.5194/acp-17-13283-2017, 2017
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In this paper we separate the biases of atmospheric methane models into stratospheric and tropospheric parts. It is observed in other studies that simulated total columns of atmospheric methane present a latitudinal bias compared to measurements. The latitudinal gradients are considered to be from the stratosphere. However, our results show that the latitudinal biases could come from the troposphere in two of three models evaluated in this study.
Kevin S. Olsen, Kimberly Strong, Kaley A. Walker, Chris D. Boone, Piera Raspollini, Johannes Plieninger, Whitney Bader, Stephanie Conway, Michel Grutter, James W. Hannigan, Frank Hase, Nicholas Jones, Martine de Mazière, Justus Notholt, Matthias Schneider, Dan Smale, Ralf Sussmann, and Naoko Saitoh
Atmos. Meas. Tech., 10, 3697–3718, https://doi.org/10.5194/amt-10-3697-2017, https://doi.org/10.5194/amt-10-3697-2017, 2017
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The primary instrument on the Greenhouse gases Observing SATellite (GOSAT) is the Thermal And Near infrared Sensor for carbon Observations (TANSO) Fourier transform spectrometer (FTS). TANSO-FTS has a thermal infrared channel to retrieve vertical profiles of CO2 and CH4 volume mixing ratios in the troposphere. We compare the retrieved vertical profiles of CH4 from TANSO-FTS with those from two other spaceborne FTSs and with ground-based FTS observatories to assess their quality.
Wei Wang, Yuan Tian, Cheng Liu, Youwen Sun, Wenqing Liu, Pinhua Xie, Jianguo Liu, Jin Xu, Isamu Morino, Voltaire A. Velazco, David W. T. Griffith, Justus Notholt, and Thorsten Warneke
Atmos. Meas. Tech., 10, 2627–2643, https://doi.org/10.5194/amt-10-2627-2017, https://doi.org/10.5194/amt-10-2627-2017, 2017
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A ground-based high-resolution Fourier transform spectrometer (FTS) station has been established in Hefei, China to remotely measure CO2, CO and other greenhouse gases. Our research aim is to provide information for constraining regional sources and sinks, and validate satellite data, such as GOSAT, OCO-2 and TANSAT. We investigate the potential of FTS to determine the temporal variability of atmospheric CO2 and CO, and assess the ability of our observations to validate satellite data.
Enrico Dammers, Mark W. Shephard, Mathias Palm, Karen Cady-Pereira, Shannon Capps, Erik Lutsch, Kim Strong, James W. Hannigan, Ivan Ortega, Geoffrey C. Toon, Wolfgang Stremme, Michel Grutter, Nicholas Jones, Dan Smale, Jacob Siemons, Kevin Hrpcek, Denis Tremblay, Martijn Schaap, Justus Notholt, and Jan Willem Erisman
Atmos. Meas. Tech., 10, 2645–2667, https://doi.org/10.5194/amt-10-2645-2017, https://doi.org/10.5194/amt-10-2645-2017, 2017
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Presented here is the validation of the CrIS fast physical retrieval (CFPR) NH3 column and profile measurements using ground-based Fourier transform infrared (FTIR) observations. The overall FTIR and CrIS total columns have a positive correlation of r = 0.77 (N = 218) with very little bias (a slope of 1.02). Furthermore, we find that CrIS and FTIR profile comparison differences are mostly within the range of the estimated retrieval uncertainties, with differences in the range of ~ 20 to 40 %.
Matthias Buschmann, Nicholas M. Deutscher, Mathias Palm, Thorsten Warneke, Christine Weinzierl, and Justus Notholt
Atmos. Meas. Tech., 10, 2397–2411, https://doi.org/10.5194/amt-10-2397-2017, https://doi.org/10.5194/amt-10-2397-2017, 2017
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The column averaged dry-air mole fractions of CO2 and CH4 (xCO2 and xCH4) of the Total Carbon Column Observing Network (TCCON) are retrieved from solar absorption Fourier transform infrared (FTIR) spectrometry. At the Ny-Ålesund site in the high arctic, however, during the polar night no solar measurements are possible. Here, we present a new method to measure xCO2 and xCH4 using the moon as a light source in the near-infrared and present the complete seasonal cycles of xCO2 and xCH4.
Debra Wunch, Paul O. Wennberg, Gregory Osterman, Brendan Fisher, Bret Naylor, Coleen M. Roehl, Christopher O'Dell, Lukas Mandrake, Camille Viatte, Matthäus Kiel, David W. T. Griffith, Nicholas M. Deutscher, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Maziere, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, David Pollard, John Robinson, Isamu Morino, Osamu Uchino, Frank Hase, Thomas Blumenstock, Dietrich G. Feist, Sabrina G. Arnold, Kimberly Strong, Joseph Mendonca, Rigel Kivi, Pauli Heikkinen, Laura Iraci, James Podolske, Patrick W. Hillyard, Shuji Kawakami, Manvendra K. Dubey, Harrison A. Parker, Eliezer Sepulveda, Omaira E. García, Yao Te, Pascal Jeseck, Michael R. Gunson, David Crisp, and Annmarie Eldering
Atmos. Meas. Tech., 10, 2209–2238, https://doi.org/10.5194/amt-10-2209-2017, https://doi.org/10.5194/amt-10-2209-2017, 2017
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This paper describes the comparisons between NASA's Orbiting Carbon Observatory (OCO-2) column-averaged dry-air mole fractions of CO2 with its primary ground-based validation network, the Total Carbon Column Observing Network (TCCON). The paper shows that while the standard bias correction reduces much of the spurious variability in the satellite measurements, residual biases remain.
Zhiting Wang, Thorsten Warneke, Bart Dils, Justus Notholt, and Marielle Saunois
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-435, https://doi.org/10.5194/acp-2017-435, 2017
Revised manuscript not accepted
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It is important to know to what extent the chemistry transport model represents tracer transport in the atmosphere correctly. In this study we evaluate performances of three models in the stratosphere in describing mixing processes there. The results reveal that deficiencies exist in representing mixing processes in mid-latitudes of southern stratosphere. Another related problem of the models is in representing tracer gradients across transport barrier.
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 17, 3963–3985, https://doi.org/10.5194/acp-17-3963-2017, https://doi.org/10.5194/acp-17-3963-2017, 2017
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We reviewed recent efforts to estimate state- and national-scale carbon dioxide and methane emissions from individual anthropogenic source sectors in the United States. State and federal greenhouse gas regulations almost always target reductions from specific source sectors, and reliable emission estimates are important to support and evaluate these policies. We also describe a number of forward-looking opportunities that would improve sector-specific estimates.
Youwen Sun, Mathias Palm, Christine Weinzierl, Christof Petri, Justus Notholt, Yuting Wang, and Cheng Liu
Atmos. Meas. Tech., 10, 989–997, https://doi.org/10.5194/amt-10-989-2017, https://doi.org/10.5194/amt-10-989-2017, 2017
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We first design experiments to investigate the sensitivity of ILS (instrumental line shape) monitoring for a high-resolution FTIR spectrometer within the TCCON and NDACC networks with respect to different optical attenuators. The ILS characteristics derived from lamp and sun spectra are in good agreement. A potential strategy to adapt incident intensity of a detector was deduced.
Jovan M. Tadić, Xuemei Qiu, Scot Miller, and Anna M. Michalak
Geosci. Model Dev., 10, 709–720, https://doi.org/10.5194/gmd-10-709-2017, https://doi.org/10.5194/gmd-10-709-2017, 2017
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We developed a new method to create contiguous maps from sparse and/or noisy satellite observations. This approach could be used to produce retroactive or real-time estimates of environmental data observed by satellites which exhibit spatio-temporal autocorrelations. The method could be applied in a standalone mode or as part of a broader satellite data processing package. Maps produced in this way could then be incorporated into physical and biogeochemical models of the Earth system.
Niall J. Ryan, Mathias Palm, Uwe Raffalski, Richard Larsson, Gloria Manney, Luis Millán, and Justus Notholt
Earth Syst. Sci. Data, 9, 77–89, https://doi.org/10.5194/essd-9-77-2017, https://doi.org/10.5194/essd-9-77-2017, 2017
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We present a self-consistent data set of carbon monoxide (CO) in the Arctic middle atmosphere above Kiruna, Sweden, between 2008 and 2015. The data are retrieved from measurements made by the ground-based radiometer, KIMRA, and are compared to coincident CO data measured by the satellite instrument MLS. KIMRA shows agreement with MLS over the altitude range in which KIMRA is sensitive (48–84 km) and the data show the signatures of dynamic processes such as sudden stratospheric warmings.
Sabine Barthlott, Matthias Schneider, Frank Hase, Thomas Blumenstock, Matthäus Kiel, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Gizaw Mengistu Tsidu, Samuel Takele Kenea, Michel Grutter, Eddy F. Plaza-Medina, Wolfgang Stremme, Kim Strong, Dan Weaver, Mathias Palm, Thorsten Warneke, Justus Notholt, Emmanuel Mahieu, Christian Servais, Nicholas Jones, David W. T. Griffith, Dan Smale, and John Robinson
Earth Syst. Sci. Data, 9, 15–29, https://doi.org/10.5194/essd-9-15-2017, https://doi.org/10.5194/essd-9-15-2017, 2017
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Tropospheric water vapour isotopologue distributions have been consistently generated and quality-filtered for 12 globally distributed ground-based FTIR sites. The products are provided as two data types. The first type is best-suited for tropospheric water vapour distribution studies. The second type is needed for analysing moisture pathways by means of {H2O,δD}-pair distributions. This paper describes the data types and gives recommendations for their correct usage.
Dmitry A. Belikov, Shamil Maksyutov, Alexander Ganshin, Ruslan Zhuravlev, Nicholas M. Deutscher, Debra Wunch, Dietrich G. Feist, Isamu Morino, Robert J. Parker, Kimberly Strong, Yukio Yoshida, Andrey Bril, Sergey Oshchepkov, Hartmut Boesch, Manvendra K. Dubey, David Griffith, Will Hewson, Rigel Kivi, Joseph Mendonca, Justus Notholt, Matthias Schneider, Ralf Sussmann, Voltaire A. Velazco, and Shuji Aoki
Atmos. Chem. Phys., 17, 143–157, https://doi.org/10.5194/acp-17-143-2017, https://doi.org/10.5194/acp-17-143-2017, 2017
Katherine M. Saad, Debra Wunch, Nicholas M. Deutscher, David W. T. Griffith, Frank Hase, Martine De Mazière, Justus Notholt, David F. Pollard, Coleen M. Roehl, Matthias Schneider, Ralf Sussmann, Thorsten Warneke, and Paul O. Wennberg
Atmos. Chem. Phys., 16, 14003–14024, https://doi.org/10.5194/acp-16-14003-2016, https://doi.org/10.5194/acp-16-14003-2016, 2016
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Current approaches to constrain the global methane budget assimilate total column measurements into models, but model biases can impact results. We use tropospheric methane columns to evaluate model transport errors and identify a seasonal time lag in the Northern Hemisphere troposphere masked by stratospheric compensating effects. We find systematic biases in the stratosphere will alias into model-derived emissions estimates, especially those in the high Northern latitudes that vary seasonally.
Andreas Ostler, Ralf Sussmann, Prabir K. Patra, Sander Houweling, Marko De Bruine, Gabriele P. Stiller, Florian J. Haenel, Johannes Plieninger, Philippe Bousquet, Yi Yin, Marielle Saunois, Kaley A. Walker, Nicholas M. Deutscher, David W. T. Griffith, Thomas Blumenstock, Frank Hase, Thorsten Warneke, Zhiting Wang, Rigel Kivi, and John Robinson
Atmos. Meas. Tech., 9, 4843–4859, https://doi.org/10.5194/amt-9-4843-2016, https://doi.org/10.5194/amt-9-4843-2016, 2016
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Our evaluation of column-averaged methane (XCH4) in models and TCCON reveals latitudinal biases between 0.4 % and 2.1 % originating from an inter-model spread in stratospheric CH4. Substituting model stratospheric CH4 fields by satellite data significantly reduces the large XCH4 bias observed for one model. For other models, showing only minor biases, the impact is ambiguous; i.e., the satellite uncertainty range hinders a more accurate model evaluation needed to improve inverse modeling.
Enrico Dammers, Mathias Palm, Martin Van Damme, Corinne Vigouroux, Dan Smale, Stephanie Conway, Geoffrey C. Toon, Nicholas Jones, Eric Nussbaumer, Thorsten Warneke, Christof Petri, Lieven Clarisse, Cathy Clerbaux, Christian Hermans, Erik Lutsch, Kim Strong, James W. Hannigan, Hideaki Nakajima, Isamu Morino, Beatriz Herrera, Wolfgang Stremme, Michel Grutter, Martijn Schaap, Roy J. Wichink Kruit, Justus Notholt, Pierre-F. Coheur, and Jan Willem Erisman
Atmos. Chem. Phys., 16, 10351–10368, https://doi.org/10.5194/acp-16-10351-2016, https://doi.org/10.5194/acp-16-10351-2016, 2016
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Atmospheric ammonia (NH3) measured by the IASI satellite instrument is compared to observations from ground-based FTIR instruments. The seasonal cycles of NH3 in both datasets are consistent for most sites. Correlations are found to be high at sites with considerable NH3 levels, whereas correlations are lower at sites with low NH3 levels close to the detection limit of the IASI instrument. The study's results further indicate that the IASI-NH3 product performs better than earlier estimates.
Makoto Inoue, Isamu Morino, Osamu Uchino, Takahiro Nakatsuru, Yukio Yoshida, Tatsuya Yokota, Debra Wunch, Paul O. Wennberg, Coleen M. Roehl, David W. T. Griffith, Voltaire A. Velazco, Nicholas M. Deutscher, Thorsten Warneke, Justus Notholt, John Robinson, Vanessa Sherlock, Frank Hase, Thomas Blumenstock, Markus Rettinger, Ralf Sussmann, Esko Kyrö, Rigel Kivi, Kei Shiomi, Shuji Kawakami, Martine De Mazière, Sabrina G. Arnold, Dietrich G. Feist, Erica A. Barrow, James Barney, Manvendra Dubey, Matthias Schneider, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Toshinobu Machida, Yousuke Sawa, Kazuhiro Tsuboi, Hidekazu Matsueda, Colm Sweeney, Pieter P. Tans, Arlyn E. Andrews, Sebastien C. Biraud, Yukio Fukuyama, Jasna V. Pittman, Eric A. Kort, and Tomoaki Tanaka
Atmos. Meas. Tech., 9, 3491–3512, https://doi.org/10.5194/amt-9-3491-2016, https://doi.org/10.5194/amt-9-3491-2016, 2016
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In this study, we correct the biases of GOSAT XCO2 and XCH4 using TCCON data. To evaluate the effectiveness of our correction method, uncorrected/corrected GOSAT data are compared to independent XCO2 and XCH4 data derived from aircraft measurements. Consequently, we suggest that this method is effective for reducing the biases of the GOSAT data. We consider that our work provides GOSAT data users with valuable information and contributes to the further development of studies on greenhouse gases.
Denise Müller, Hermann W. Bange, Thorsten Warneke, Tim Rixen, Moritz Müller, Aazani Mujahid, and Justus Notholt
Biogeosciences, 13, 2415–2428, https://doi.org/10.5194/bg-13-2415-2016, https://doi.org/10.5194/bg-13-2415-2016, 2016
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Estuaries act as sources of the greenhouse gases nitrous oxide (N2O) and methane (CH4) to the atmosphere. We provide first measurements of N2O and CH4 in two estuaries in north-western Borneo, a region which is dominated by peatlands. We show that N2O and CH4 concentrations in these estuaries are moderate despite high organic carbon loads, that nutrient enhancement does not lead to enhanced N2O emissions, and that the wet season dominates the variability of the emissions in these systems.
Scot M. Miller, Roisin Commane, Joe R. Melton, Arlyn E. Andrews, Joshua Benmergui, Edward J. Dlugokencky, Greet Janssens-Maenhout, Anna M. Michalak, Colm Sweeney, and Doug E. J. Worthy
Biogeosciences, 13, 1329–1339, https://doi.org/10.5194/bg-13-1329-2016, https://doi.org/10.5194/bg-13-1329-2016, 2016
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We use atmospheric data from the US and Canada to examine seven wetland methane flux estimates. Relative to existing estimates, we find a methane source that is smaller in magnitude with a broader seasonal cycle. Furthermore, we estimate the largest fluxes over the Hudson Bay Lowlands, a spatial distribution that differs from commonly used remote sensing estimates of wetland location.
Susan Kulawik, Debra Wunch, Christopher O'Dell, Christian Frankenberg, Maximilian Reuter, Tomohiro Oda, Frederic Chevallier, Vanessa Sherlock, Michael Buchwitz, Greg Osterman, Charles E. Miller, Paul O. Wennberg, David Griffith, Isamu Morino, Manvendra K. Dubey, Nicholas M. Deutscher, Justus Notholt, Frank Hase, Thorsten Warneke, Ralf Sussmann, John Robinson, Kimberly Strong, Matthias Schneider, Martine De Mazière, Kei Shiomi, Dietrich G. Feist, Laura T. Iraci, and Joyce Wolf
Atmos. Meas. Tech., 9, 683–709, https://doi.org/10.5194/amt-9-683-2016, https://doi.org/10.5194/amt-9-683-2016, 2016
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To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized. This paper examines two satellite data sets (GOSAT, launched 2009, and SCIAMACHY, launched 2002), and two models (CarbonTracker and MACC) vs. the TCCON CO2 validation data set. We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability. Our findings are useful for assimilation of satellite data.
Yuting Wang, Nicholas M. Deutscher, Mathias Palm, Thorsten Warneke, Justus Notholt, Ian Baker, Joe Berry, Parvadha Suntharalingam, Nicholas Jones, Emmanuel Mahieu, Bernard Lejeune, James Hannigan, Stephanie Conway, Joseph Mendonca, Kimberly Strong, J. Elliott Campbell, Adam Wolf, and Stefanie Kremser
Atmos. Chem. Phys., 16, 2123–2138, https://doi.org/10.5194/acp-16-2123-2016, https://doi.org/10.5194/acp-16-2123-2016, 2016
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OCS could provide an additional constraint on the carbon cycle. The FTIR networks have existed for more than 20 years. For the first time, we used FTIR measurements of OCS and CO2 to study their relationship. We put the coupled CO2 and OCS land fluxes from the Simple Biosphere Model (SiB) into a transport model, and compared the simulations to the measurements. Looking at OCS and CO2 together inspires some new thoughts in how the biospheric models reproduce the carbon cycle in the real world.
Matthias Buschmann, Nicholas M. Deutscher, Vanessa Sherlock, Mathias Palm, Thorsten Warneke, and Justus Notholt
Atmos. Meas. Tech., 9, 577–585, https://doi.org/10.5194/amt-9-577-2016, https://doi.org/10.5194/amt-9-577-2016, 2016
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The column-averaged dry-air mole fraction of CO2 has been retrieved from high-resolution solar absorption spectra from two different measurement networks. We investigate the differences between these retrievals and find that their sensitivity differs greatly. As a result the direct comparison of the two retrievals remains challenging.
D. Müller, T. Warneke, T. Rixen, M. Müller, A. Mujahid, H. W. Bange, and J. Notholt
Biogeosciences, 13, 691–705, https://doi.org/10.5194/bg-13-691-2016, https://doi.org/10.5194/bg-13-691-2016, 2016
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We studied organic carbon and the dissolved greenhouse gases carbon dioxide (CO2) and carbon monoxide (CO) in two estuaries in Sarawak, Malaysia, whose coast is covered by carbon-rich peatlands. The estuaries received terrestrial organic carbon from peat-draining tributaries. A large fraction was converted to CO2 and a minor fraction to CO. Both gases were released to the atmosphere. This shows how these estuaries function as efficient filters between land and ocean in this important region.
E. Dammers, C. Vigouroux, M. Palm, E. Mahieu, T. Warneke, D. Smale, B. Langerock, B. Franco, M. Van Damme, M. Schaap, J. Notholt, and J. W. Erisman
Atmos. Chem. Phys., 15, 12789–12803, https://doi.org/10.5194/acp-15-12789-2015, https://doi.org/10.5194/acp-15-12789-2015, 2015
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We present a new retrieval method for ammonia (NH3) concentrations and total columns from ground-based Fourier transform infrared (FTIR) observations. Observations from Bremen, Lauder, Réunion and Jungfraujoch are used to show the capabilities of the new retrieval. The developed retrieval provides a new way of obtaining time-resolved measurements and will be useful for understanding the dynamics of ammonia concentrations in the atmosphere and for satellite and model validation.
R. J. Parker, H. Boesch, K. Byckling, A. J. Webb, P. I. Palmer, L. Feng, P. Bergamaschi, F. Chevallier, J. Notholt, N. Deutscher, T. Warneke, F. Hase, R. Sussmann, S. Kawakami, R. Kivi, D. W. T. Griffith, and V. Velazco
Atmos. Meas. Tech., 8, 4785–4801, https://doi.org/10.5194/amt-8-4785-2015, https://doi.org/10.5194/amt-8-4785-2015, 2015
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Atmospheric CH4 is an important greenhouse gas. Long-term global observations are necessary to understand its behaviour, with satellite observations playing a key role. The "proxy" retrieval method is one of the most successful but relies on the contribution from atmospheric CO2 models. This work assesses the significance of the uncertainty from the model CO2 within the retrieval and determines that despite this uncertainty the data are still valuable for determining sources and sinks of CH4.
D. Müller, T. Warneke, T. Rixen, M. Müller, S. Jamahari, N. Denis, A. Mujahid, and J. Notholt
Biogeosciences, 12, 5967–5979, https://doi.org/10.5194/bg-12-5967-2015, https://doi.org/10.5194/bg-12-5967-2015, 2015
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Tropical peatlands are an important source of organic carbon to rivers. However, due to the remoteness of these ecosystems, data are scarce. We present the first combined assessment of both lateral organic carbon fluxes and CO2 emissions from an undisturbed tropical peat-draining river. Compared to the organic carbon concentrations, CO2 fluxes to the atmosphere were actually relatively moderate, which we attributed to the short water residence time.
A. Ostler, R. Sussmann, P. K. Patra, P. O. Wennberg, N. M. Deutscher, D. W. T. Griffith, T. Blumenstock, F. Hase, R. Kivi, T. Warneke, Z. Wang, M. De Mazière, J. Robinson, and H. Ohyama
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-20395-2015, https://doi.org/10.5194/acpd-15-20395-2015, 2015
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We find that stratospheric model-transport errors are common for chemical transport models that are used for inverse estimates of CH4 emissions. These model-transport errors cause latitudinal as well as seasonal biases in simulated stratospheric and, hence, column-averaged CH4 mixing ratios (XCH4). Such a model bias corresponds to an overestimation of arctic and mid-latitude CH4 emissions if inversion studies do not apply an ad hoc bias correction before inverting fluxes from XCH4 observations.
J. Heymann, M. Reuter, M. Hilker, M. Buchwitz, O. Schneising, H. Bovensmann, J. P. Burrows, A. Kuze, H. Suto, N. M. Deutscher, M. K. Dubey, D. W. T. Griffith, F. Hase, S. Kawakami, R. Kivi, I. Morino, C. Petri, C. Roehl, M. Schneider, V. Sherlock, R. Sussmann, V. A. Velazco, T. Warneke, and D. Wunch
Atmos. Meas. Tech., 8, 2961–2980, https://doi.org/10.5194/amt-8-2961-2015, https://doi.org/10.5194/amt-8-2961-2015, 2015
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Long-term data sets of global atmospheric carbon dioxide concentrations based on observations from different satellite instruments may suffer from inconsistencies originating from the use of different retrieval algorithms. This issue has been addressed by applying the Bremen Optimal Estimation DOAS retrieval algorithm to SCIAMACHY and TANSO-FTS observations. Detailed comparisons with TCCON and CarbonTracker show good consistency between the SCIAMACHY and TANSO-FTS data sets.
C. E. Yver Kwok, D. Müller, C. Caldow, B. Lebègue, J. G. Mønster, C. W. Rella, C. Scheutz, M. Schmidt, M. Ramonet, T. Warneke, G. Broquet, and P. Ciais
Atmos. Meas. Tech., 8, 2853–2867, https://doi.org/10.5194/amt-8-2853-2015, https://doi.org/10.5194/amt-8-2853-2015, 2015
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This study presents two methods for estimating methane emissions from a waste water treatment plant (WWTP) along with results from a measurement campaign at a WWTP in Valence, France. We show that the tracer release method is suitable to quantify facility emissions, while the chamber measurements, provide insights into individual processes. We confirm that the open basins are not a major source of CH4 on the WWTP but that the pretreatment and sludge treatment are the main emitters.
H. van Asperen, T. Warneke, S. Sabbatini, G. Nicolini, D. Papale, and J. Notholt
Biogeosciences, 12, 4161–4174, https://doi.org/10.5194/bg-12-4161-2015, https://doi.org/10.5194/bg-12-4161-2015, 2015
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Recent studies have suggested the potential importance of abiotic decomposition (photodegradation) in arid ecosystems. This study focuses on the measurement and understanding of abiotic fluxes. Photodegradation fluxes have not been observed. Thermal degradation fluxes were observed in the field (for CO) and in the laboratory (for CO2 and CO). Previous studies have potentially overestimated the role of photodegradation or misinterpreted thermal degradation fluxes as photodegradation fluxes.
S. Song, N. E. Selin, A. L. Soerensen, H. Angot, R. Artz, S. Brooks, E.-G. Brunke, G. Conley, A. Dommergue, R. Ebinghaus, T. M. Holsen, D. A. Jaffe, S. Kang, P. Kelley, W. T. Luke, O. Magand, K. Marumoto, K. A. Pfaffhuber, X. Ren, G.-R. Sheu, F. Slemr, T. Warneke, A. Weigelt, P. Weiss-Penzias, D. C. Wip, and Q. Zhang
Atmos. Chem. Phys., 15, 7103–7125, https://doi.org/10.5194/acp-15-7103-2015, https://doi.org/10.5194/acp-15-7103-2015, 2015
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A better knowledge of mercury (Hg) emission fluxes into the global atmosphere is important for assessing its human health impacts and evaluating the effectiveness of corresponding policy actions. We for the first time apply a top-down approach at a global scale to quantitatively estimate present-day mercury emission sources as well as key parameters in a chemical transport model, in order to better constrain the global biogeochemical cycle of mercury.
A. J. Turner, D. J. Jacob, K. J. Wecht, J. D. Maasakkers, E. Lundgren, A. E. Andrews, S. C. Biraud, H. Boesch, K. W. Bowman, N. M. Deutscher, M. K. Dubey, D. W. T. Griffith, F. Hase, A. Kuze, J. Notholt, H. Ohyama, R. Parker, V. H. Payne, R. Sussmann, C. Sweeney, V. A. Velazco, T. Warneke, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 15, 7049–7069, https://doi.org/10.5194/acp-15-7049-2015, https://doi.org/10.5194/acp-15-7049-2015, 2015
S. Barthlott, M. Schneider, F. Hase, A. Wiegele, E. Christner, Y. González, T. Blumenstock, S. Dohe, O. E. García, E. Sepúlveda, K. Strong, J. Mendonca, D. Weaver, M. Palm, N. M. Deutscher, T. Warneke, J. Notholt, B. Lejeune, E. Mahieu, N. Jones, D. W. T. Griffith, V. A. Velazco, D. Smale, J. Robinson, R. Kivi, P. Heikkinen, and U. Raffalski
Atmos. Meas. Tech., 8, 1555–1573, https://doi.org/10.5194/amt-8-1555-2015, https://doi.org/10.5194/amt-8-1555-2015, 2015
S. M. Miller, M. N. Hayek, A. E. Andrews, I. Fung, and J. Liu
Atmos. Chem. Phys., 15, 2903–2914, https://doi.org/10.5194/acp-15-2903-2015, https://doi.org/10.5194/acp-15-2903-2015, 2015
A. Ostler, R. Sussmann, M. Rettinger, N. M. Deutscher, S. Dohe, F. Hase, N. Jones, M. Palm, and B.-M. Sinnhuber
Atmos. Meas. Tech., 7, 4081–4101, https://doi.org/10.5194/amt-7-4081-2014, https://doi.org/10.5194/amt-7-4081-2014, 2014
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Ground-based FTIR soundings of column-average methane from NDACC and TCCON can be combined without the need to apply an overall calibration factor. NDACC and TCCON measurements complement one another and provide valuable information for satellite validation, evaluation of chemical-transport models, and source-sink inversions. The impact of dynamical variability on NDACC and TCCON retrievals of column-average methane is reflected in different smoothing effects.
Z. Wang, N. M. Deutscher, T. Warneke, J. Notholt, B. Dils, D. W. T. Griffith, M. Schmidt, M. Ramonet, and C. Gerbig
Atmos. Meas. Tech., 7, 3295–3305, https://doi.org/10.5194/amt-7-3295-2014, https://doi.org/10.5194/amt-7-3295-2014, 2014
S. Kowalewski, C. von Savigny, M. Palm, I. C. McDade, and J. Notholt
Atmos. Chem. Phys., 14, 10193–10210, https://doi.org/10.5194/acp-14-10193-2014, https://doi.org/10.5194/acp-14-10193-2014, 2014
E. Sepúlveda, M. Schneider, F. Hase, S. Barthlott, D. Dubravica, O. E. García, A. Gomez-Pelaez, Y. González, J. C. Guerra, M. Gisi, R. Kohlhepp, S. Dohe, T. Blumenstock, K. Strong, D. Weaver, M. Palm, A. Sadeghi, N. M. Deutscher, T. Warneke, J. Notholt, N. Jones, D. W. T. Griffith, D. Smale, G. W. Brailsford, J. Robinson, F. Meinhardt, M. Steinbacher, T. Aalto, and D. Worthy
Atmos. Meas. Tech., 7, 2337–2360, https://doi.org/10.5194/amt-7-2337-2014, https://doi.org/10.5194/amt-7-2337-2014, 2014
S. M. Miller, A. M. Michalak, and P. J. Levi
Geosci. Model Dev., 7, 303–315, https://doi.org/10.5194/gmd-7-303-2014, https://doi.org/10.5194/gmd-7-303-2014, 2014
Z. Mariani, K. Strong, M. Palm, R. Lindenmaier, C. Adams, X. Zhao, V. Savastiouk, C. T. McElroy, F. Goutail, and J. R. Drummond
Atmos. Meas. Tech., 6, 1549–1565, https://doi.org/10.5194/amt-6-1549-2013, https://doi.org/10.5194/amt-6-1549-2013, 2013
H. Boesch, N. M. Deutscher, T. Warneke, K. Byckling, A. J. Cogan, D. W. T. Griffith, J. Notholt, R. J. Parker, and Z. Wang
Atmos. Meas. Tech., 6, 599–612, https://doi.org/10.5194/amt-6-599-2013, https://doi.org/10.5194/amt-6-599-2013, 2013
M. Schneider, S. Barthlott, F. Hase, Y. González, K. Yoshimura, O. E. García, E. Sepúlveda, A. Gomez-Pelaez, M. Gisi, R. Kohlhepp, S. Dohe, T. Blumenstock, A. Wiegele, E. Christner, K. Strong, D. Weaver, M. Palm, N. M. Deutscher, T. Warneke, J. Notholt, B. Lejeune, P. Demoulin, N. Jones, D. W. T. Griffith, D. Smale, and J. Robinson
Atmos. Meas. Tech., 5, 3007–3027, https://doi.org/10.5194/amt-5-3007-2012, https://doi.org/10.5194/amt-5-3007-2012, 2012
Related subject area
Atmospheric sciences
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-229, https://doi.org/10.5194/gmd-2024-229, 2025
Revised manuscript accepted for GMD
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This study presents the first comprehensive evaluation of unstructured meshes using the iAMAS model over Antarctica, encompassing both surface and upper-level meteorological fields. Comparison with ERA5 and observational data reveals that the iAMAS model performs well in simulating the Antarctic atmosphere; iAMAS demonstrates comparable, and in some cases superior, performance in simulating temperature and wind speed in East Antarctica when compared to ERA5.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
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Short summary
Inverse modeling uses atmospheric measurements to estimate emissions of greenhouse gases, which are key to understand the climate system. However, the measurement information alone is typically insufficient to provide reasonable emission estimates. Additional information is required. This article applies modern mathematical inversion techniques to formulate such additional knowledge. It is a prime example of how such tools can improve the quality of estimates compared to commonly used methods.
Inverse modeling uses atmospheric measurements to estimate emissions of greenhouse gases, which...
