Articles | Volume 15, issue 8
https://doi.org/10.5194/essd-15-3387-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-3387-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
02 Aug 2023
Data description paper |
| 02 Aug 2023
| 02 Aug 2023
Network for the Detection of Atmospheric Composition Change (NDACC) Fourier transform infrared (FTIR) trace gas measurements at the University of Toronto Atmospheric Observatory from 2002 to 2020
Shoma Yamanouchi
CORRESPONDING AUTHOR
Department of Physics, University of Toronto, Toronto, M5S 1A7, Canada
Stephanie Conway
Department of Physics, University of Toronto, Toronto, M5S 1A7, Canada
Kimberly Strong
Department of Physics, University of Toronto, Toronto, M5S 1A7, Canada
Orfeo Colebatch
Department of Physics, University of Toronto, Toronto, M5S 1A7, Canada
Erik Lutsch
Department of Physics, University of Toronto, Toronto, M5S 1A7, Canada
Sébastien Roche
Department of Physics, University of Toronto, Toronto, M5S 1A7, Canada
Jeffrey Taylor
Nova Scotia Community College, Halifax, B3K 2T3, Canada
Cynthia H. Whaley
Environment and Climate Change Canada, Victoria, V8W 2Y2, Canada
Aldona Wiacek
Saint Mary's University, Halifax, B3H 3C3, Canada
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Andrea Pazmiño, Florence Goutail, Sophie Godin-Beekmann, Alain Hauchecorne, Jean-Pierre Pommereau, Martyn P. Chipperfield, Wuhu Feng, Franck Lefèvre, Audrey Lecouffe, Michel Van Roozendael, Nis Jepsen, Georg Hansen, Rigel Kivi, Kimberly Strong, and Kaley A. Walker
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Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
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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
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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.
Ian Ashpole and Aldona Wiacek
Atmos. Meas. Tech., 16, 1923–1949, https://doi.org/10.5194/amt-16-1923-2023, https://doi.org/10.5194/amt-16-1923-2023, 2023
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The MOPITT instrument has been measuring atmospheric carbon monoxide (CO) from space since 2000. Its data products are valuable for CO trend analysis. This paper compares products with different spatial resolutions to identify discrepancies in mean CO amounts and detectable trends for coastal grid boxes. It is found that CO amounts and trends differ significantly between data products for a large number of these grid boxes, essentially due to how the coarser-resolution products are created.
Nasrin Mostafavi Pak, Jacob K. Hedelius, Sébastien Roche, Liz Cunningham, Bianca Baier, Colm Sweeney, Coleen Roehl, Joshua Laughner, Geoffrey Toon, Paul Wennberg, Harrison Parker, Colin Arrowsmith, Joseph Mendonca, Pierre Fogal, Tyler Wizenberg, Beatriz Herrera, Kimberly Strong, Kaley A. Walker, Felix Vogel, and Debra Wunch
Atmos. Meas. Tech., 16, 1239–1261, https://doi.org/10.5194/amt-16-1239-2023, https://doi.org/10.5194/amt-16-1239-2023, 2023
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Ground-based remote sensing instruments in the Total Carbon Column Observing Network (TCCON) measure greenhouse gases in the atmosphere. Consistency between TCCON measurements is crucial to accurately infer changes in atmospheric composition. We use portable remote sensing instruments (EM27/SUN) to evaluate biases between TCCON stations in North America. We also improve the retrievals of EM27/SUN instruments and evaluate the previous (GGG2014) and newest (GGG2020) retrieval algorithms.
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.
Joshua L. Laughner, Sébastien Roche, Matthäus Kiel, Geoffrey C. Toon, Debra Wunch, Bianca C. Baier, Sébastien Biraud, Huilin Chen, Rigel Kivi, Thomas Laemmel, Kathryn McKain, Pierre-Yves Quéhé, Constantina Rousogenous, Britton B. Stephens, Kaley Walker, and Paul O. Wennberg
Atmos. Meas. Tech., 16, 1121–1146, https://doi.org/10.5194/amt-16-1121-2023, https://doi.org/10.5194/amt-16-1121-2023, 2023
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Observations using sunlight to measure surface-to-space total column of greenhouse gases in the atmosphere need an initial guess of the vertical distribution of those gases to start from. We have developed an approach to provide those initial guess profiles that uses readily available meteorological data as input. This lets us make these guesses without simulating them with a global model. The profiles generated this way match independent observations well.
Cynthia H. Whaley, Kathy S. Law, Jens Liengaard Hjorth, Henrik Skov, Stephen R. Arnold, Joakim Langner, Jakob Boyd Pernov, Garance Bergeron, Ilann Bourgeois, Jesper H. Christensen, Rong-You Chien, Makoto Deushi, Xinyi Dong, Peter Effertz, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Greg Huey, Ulas Im, Rigel Kivi, Louis Marelle, Tatsuo Onishi, Naga Oshima, Irina Petropavlovskikh, Jeff Peischl, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Tom Ryerson, Ragnhild Skeie, Sverre Solberg, Manu A. Thomas, Chelsea Thompson, Kostas Tsigaridis, Svetlana Tsyro, Steven T. Turnock, Knut von Salzen, and David W. Tarasick
Atmos. Chem. Phys., 23, 637–661, https://doi.org/10.5194/acp-23-637-2023, https://doi.org/10.5194/acp-23-637-2023, 2023
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This study summarizes recent research on ozone in the Arctic, a sensitive and rapidly warming region. We find that the seasonal cycles of near-surface atmospheric ozone are variable depending on whether they are near the coast, inland, or at high altitude. Several global model simulations were evaluated, and we found that because models lack some of the ozone chemistry that is important for the coastal Arctic locations, they do not accurately simulate ozone there.
Ali Jalali, Kaley A. Walker, Kimberly Strong, Rebecca R. Buchholz, Merritt N. Deeter, Debra Wunch, Sébastien Roche, Tyler Wizenberg, Erik Lutsch, Erin McGee, Helen M. Worden, Pierre Fogal, and James R. Drummond
Atmos. Meas. Tech., 15, 6837–6863, https://doi.org/10.5194/amt-15-6837-2022, https://doi.org/10.5194/amt-15-6837-2022, 2022
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This study validates MOPITT version 8 carbon monoxide measurements over the Canadian high Arctic for the period 2006 to 2019. The MOPITT products from different detector pixels and channels are compared with ground-based measurements from the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada. These results show good consistency between the satellite and ground-based measurements and provide guidance on the usage of these MOPITT data at high latitudes.
Beatriz Herrera, Alejandro Bezanilla, Thomas Blumenstock, Enrico Dammers, Frank Hase, Lieven Clarisse, Adolfo Magaldi, Claudia Rivera, Wolfgang Stremme, Kimberly Strong, Camille Viatte, Martin Van Damme, and Michel Grutter
Atmos. Chem. Phys., 22, 14119–14132, https://doi.org/10.5194/acp-22-14119-2022, https://doi.org/10.5194/acp-22-14119-2022, 2022
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This work investigates atmospheric ammonia (NH3), a key trace gas with consequences for the environment and human health, in Mexico City. The results from the ground-based and satellite instruments show the variability and spatial distribution of NH3 over this region. NH3 in Mexico City has been increasing for the past 10 years and most of its sources are urban. This work contributes to a better understanding of NH3 sources and variability in urban and remote areas.
Xin Yang, Kimberly Strong, Alison S. Criscitiello, Marta Santos-Garcia, Kristof Bognar, Xiaoyi Zhao, Pierre Fogal, Kaley A. Walker, Sara M. Morris, and Peter Effertz
EGUsphere, https://doi.org/10.5194/egusphere-2022-696, https://doi.org/10.5194/egusphere-2022-696, 2022
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Snow pack in high Arctic plays a key role in polar atmospheric chemistry, especially in spring when photochemistry becomes active. By sampling surface snow from a Canadian high Arctic location at Eureka, Nunavut (80° N, 86° W), we demonstrate that surface snow is a net sink rather than a source of atmospheric reactive bromine and nitrate. This finding is new and opposite to previous conclusions that snowpack is a large and direct source of reactive bromine in polar spring.
Camille Viatte, Rimal Abeed, Shoma Yamanouchi, William C. Porter, Sarah Safieddine, Martin Van Damme, Lieven Clarisse, Beatriz Herrera, Michel Grutter, Pierre-Francois Coheur, Kimberly Strong, and Cathy Clerbaux
Atmos. Chem. Phys., 22, 12907–12922, https://doi.org/10.5194/acp-22-12907-2022, https://doi.org/10.5194/acp-22-12907-2022, 2022
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Large cities can experience high levels of fine particulate matter (PM2.5) pollution linked to ammonia (NH3) mainly emitted from agricultural activities. Using a combination of PM2.5 and NH3 measurements from in situ instruments, satellite infrared spectrometers, and atmospheric model simulations, we have demonstrated the role of NH3 and meteorological conditions on pollution events occurring over Paris, Toronto, and Mexico City.
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.
Gaia Pinardi, Michel Van Roozendael, François Hendrick, Andreas Richter, Pieter Valks, Ramina Alwarda, Kristof Bognar, Udo Frieß, José Granville, Myojeong Gu, Paul Johnston, Cristina Prados-Roman, Richard Querel, Kimberly Strong, Thomas Wagner, Folkard Wittrock, and Margarita Yela Gonzalez
Atmos. Meas. Tech., 15, 3439–3463, https://doi.org/10.5194/amt-15-3439-2022, https://doi.org/10.5194/amt-15-3439-2022, 2022
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We report on the GOME-2A and GOME-2B OClO dataset (2007 to 2016, from the EUMETSAT's AC SAF) validation using data from nine NDACC zenith-scattered-light DOAS (ZSL-DOAS) instruments distributed in both the Arctic and Antarctic. Specific sensitivity tests are performed on the ground-based data to estimate the impact of the different OClO DOAS analysis settings and their typical errors. Good agreement is found for both the inter-annual variability and the overall OClO seasonal behavior.
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.
Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
Atmos. Chem. Phys., 22, 5775–5828, https://doi.org/10.5194/acp-22-5775-2022, https://doi.org/10.5194/acp-22-5775-2022, 2022
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Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
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.
Tyler Wizenberg, Kimberly Strong, Kaley Walker, Erik Lutsch, Tobias Borsdorff, and Jochen Landgraf
Atmos. Meas. Tech., 14, 7707–7728, https://doi.org/10.5194/amt-14-7707-2021, https://doi.org/10.5194/amt-14-7707-2021, 2021
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CO is an important atmospheric gas that influences both air quality and the climate. Here, we compare CO measurements from TROPOMI with those from ACE-FTS and an Arctic ground-based FTS at Eureka, Nunavut, to further characterize the accuracy of TROPOMI measurements. CO columns from the instruments agree well but show larger differences at high latitudes. Despite this, the results fall within the TROPOMI accuracy target, indicating good data quality at high latitudes.
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.
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.
Ulas Im, Kostas Tsigaridis, Gregory Faluvegi, Peter L. Langen, Joshua P. French, Rashed Mahmood, Manu A. Thomas, Knut von Salzen, Daniel C. Thomas, Cynthia H. Whaley, Zbigniew Klimont, Henrik Skov, and Jørgen Brandt
Atmos. Chem. Phys., 21, 10413–10438, https://doi.org/10.5194/acp-21-10413-2021, https://doi.org/10.5194/acp-21-10413-2021, 2021
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Future (2015–2050) simulations of the aerosol burdens and their radiative forcing and climate impacts over the Arctic under various emission projections show that although the Arctic aerosol burdens are projected to decrease significantly by 10 to 60 %, regardless of the magnitude of aerosol reductions, surface air temperatures will continue to increase by 1.9–2.6 ℃, while sea-ice extent will continue to decrease, implying reductions of greenhouse gases are necessary to mitigate climate change.
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.
Sébastien Roche, Kimberly Strong, Debra Wunch, Joseph Mendonca, Colm Sweeney, Bianca Baier, Sébastien C. Biraud, Joshua L. Laughner, Geoffrey C. Toon, and Brian J. Connor
Atmos. Meas. Tech., 14, 3087–3118, https://doi.org/10.5194/amt-14-3087-2021, https://doi.org/10.5194/amt-14-3087-2021, 2021
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We evaluate CO2 profile retrievals from ground-based near-infrared solar absorption spectra after implementing several improvements to the GFIT2 retrieval algorithm. Realistic errors in the a priori temperature profile (~ 2 °C in the lower troposphere) are found to be the leading source of differences between the retrieved and true CO2 profiles, differences that are larger than typical CO2 variability. A temperature retrieval or correction is critical to improve CO2 profile retrieval results.
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.
Shoma Yamanouchi, Camille Viatte, Kimberly Strong, Erik Lutsch, Dylan B. A. Jones, Cathy Clerbaux, Martin Van Damme, Lieven Clarisse, and Pierre-Francois Coheur
Atmos. Meas. Tech., 14, 905–921, https://doi.org/10.5194/amt-14-905-2021, https://doi.org/10.5194/amt-14-905-2021, 2021
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Ammonia (NH3) is a major source of pollution in the air. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 over Toronto, Canada, derived from multiscale datasets are examined. These NH3 datasets were compared to each other and to a model to better understand NH3 variability and to assess model performance.
Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Henk J. Eskes, Kai-Uwe Eichmann, Ann Mari Fjæraa, José Granville, Sander Niemeijer, Alexander Cede, Martin Tiefengraber, François Hendrick, Andrea Pazmiño, Alkiviadis Bais, Ariane Bazureau, K. Folkert Boersma, Kristof Bognar, Angelika Dehn, Sebastian Donner, Aleksandr Elokhov, Manuel Gebetsberger, Florence Goutail, Michel Grutter de la Mora, Aleksandr Gruzdev, Myrto Gratsea, Georg H. Hansen, Hitoshi Irie, Nis Jepsen, Yugo Kanaya, Dimitris Karagkiozidis, Rigel Kivi, Karin Kreher, Pieternel F. Levelt, Cheng Liu, Moritz Müller, Monica Navarro Comas, Ankie J. M. Piters, Jean-Pierre Pommereau, Thierry Portafaix, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Julia Remmers, Andreas Richter, John Rimmer, Claudia Rivera Cárdenas, Lidia Saavedra de Miguel, Valery P. Sinyakov, Wolfgang Stremme, Kimberly Strong, Michel Van Roozendael, J. Pepijn Veefkind, Thomas Wagner, Folkard Wittrock, Margarita Yela González, and Claus Zehner
Atmos. Meas. Tech., 14, 481–510, https://doi.org/10.5194/amt-14-481-2021, https://doi.org/10.5194/amt-14-481-2021, 2021
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This paper reports on the ground-based validation of the NO2 data produced operationally by the TROPOMI instrument on board the Sentinel-5 Precursor satellite. Tropospheric, stratospheric, and total NO2 columns are compared to measurements collected from MAX-DOAS, ZSL-DOAS, and PGN/Pandora instruments respectively. The products are found to satisfy mission requirements in general, though negative mean differences are found at sites with high pollution levels. Potential causes are discussed.
Jan-Lukas Tirpitz, Udo Frieß, François Hendrick, Carlos Alberti, Marc Allaart, Arnoud Apituley, Alkis Bais, Steffen Beirle, Stijn Berkhout, Kristof Bognar, Tim Bösch, Ilya Bruchkouski, Alexander Cede, Ka Lok Chan, Mirjam den Hoed, Sebastian Donner, Theano Drosoglou, Caroline Fayt, Martina M. Friedrich, Arnoud Frumau, Lou Gast, Clio Gielen, Laura Gomez-Martín, Nan Hao, Arjan Hensen, Bas Henzing, Christian Hermans, Junli Jin, Karin Kreher, Jonas Kuhn, Johannes Lampel, Ang Li, Cheng Liu, Haoran Liu, Jianzhong Ma, Alexis Merlaud, Enno Peters, Gaia Pinardi, Ankie Piters, Ulrich Platt, Olga Puentedura, Andreas Richter, Stefan Schmitt, Elena Spinei, Deborah Stein Zweers, Kimberly Strong, Daan Swart, Frederik Tack, Martin Tiefengraber, René van der Hoff, Michel van Roozendael, Tim Vlemmix, Jan Vonk, Thomas Wagner, Yang Wang, Zhuoru Wang, Mark Wenig, Matthias Wiegner, Folkard Wittrock, Pinhua Xie, Chengzhi Xing, Jin Xu, Margarita Yela, Chengxin Zhang, and Xiaoyi Zhao
Atmos. Meas. Tech., 14, 1–35, https://doi.org/10.5194/amt-14-1-2021, https://doi.org/10.5194/amt-14-1-2021, 2021
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Multi-axis differential optical absorption spectroscopy (MAX-DOAS) is a ground-based remote sensing measurement technique that derives atmospheric aerosol and trace gas vertical profiles from skylight spectra. In this study, consistency and reliability of MAX-DOAS profiles are assessed by applying nine different evaluation algorithms to spectral data recorded during an intercomparison campaign in the Netherlands and by comparing the results to colocated supporting observations.
Xin Yang, Anne-M. Blechschmidt, Kristof Bognar, Audra McClure-Begley, Sara Morris, Irina Petropavlovskikh, Andreas Richter, Henrik Skov, Kimberly Strong, David W. Tarasick, Taneil Uttal, Mika Vestenius, and Xiaoyi Zhao
Atmos. Chem. Phys., 20, 15937–15967, https://doi.org/10.5194/acp-20-15937-2020, https://doi.org/10.5194/acp-20-15937-2020, 2020
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This is a modelling-based study on Arctic surface ozone, with a particular focus on spring ozone depletion events (i.e. with concentrations < 10 ppbv). Model experiments show that model runs with blowing-snow-sourced sea salt aerosols implemented as a source of reactive bromine can reproduce well large-scale ozone depletion events observed in the Arctic. This study supplies modelling evidence of the proposed mechanism of reactive-bromine release from blowing snow on sea ice (Yang et al., 2008).
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.
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Short summary
Nineteen years of atmospheric composition measurements made at the University of Toronto Atmospheric Observatory (TAO; 43.66° N, 79.40° W; 174 m.a.s.l.) are presented. These are retrieved from Fourier transform infrared (FTIR) solar absorption spectra recorded with a spectrometer from May 2002 to December 2020. The retrievals have been optimized for fourteen species: O3, HCl, HF, HNO3, CH4, C2H6, CO, HCN, N2O, C2H2, H2CO, CH3OH, HCOOH, and NH3.
Nineteen years of atmospheric composition measurements made at the University of Toronto...
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