Articles | Volume 18, issue 3
https://doi.org/10.5194/amt-18-569-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-569-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Feb 2025
Research article |
| 03 Feb 2025
| 03 Feb 2025
Validation of the version 4.5 MAESTRO ozone and NO2 measurements
Paul S. Jeffery
Department of Physics, University of Toronto, Toronto, ON, M5S1A7, Canada
James R. Drummond
Department of Physics and Atmospheric Physics, Dalhousie University, Halifax, NS, B3H4R2, Canada
C. Thomas McElroy
Department of Earth and Space Science and Engineering, York University, Toronto, ON, M3J1P3, Canada
Department of Physics, University of Toronto, Toronto, ON, M5S1A7, Canada
Jiansheng Zou
Department of Physics, University of Toronto, Toronto, ON, M5S1A7, Canada
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Atmos. Chem. Phys., 24, 7927–7959, https://doi.org/10.5194/acp-24-7927-2024, https://doi.org/10.5194/acp-24-7927-2024, 2024
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The MOPITT instrument has been monitoring carbon monoxide (CO) since March 2000. This dataset has been used for many applications; however, episodic emission events, which release large amounts of CO into the atmosphere, are a major source of uncertainty. This study presents a method for identifying these events by determining measurements that are unlikely to have typically arisen. The distribution and frequency of these flagged measurements in the MOPITT dataset are presented and discussed.
Paul S. Jeffery, Kaley A. Walker, Chris E. Sioris, Chris D. Boone, Doug Degenstein, Gloria L. Manney, C. Thomas McElroy, Luis Millán, David A. Plummer, Niall J. Ryan, Patrick E. Sheese, and Jiansheng Zou
Atmos. Chem. Phys., 22, 14709–14734, https://doi.org/10.5194/acp-22-14709-2022, https://doi.org/10.5194/acp-22-14709-2022, 2022
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The upper troposphere–lower stratosphere is one of the most variable regions in the atmosphere. To improve our understanding of water vapour and ozone concentrations in this region, climatologies have been developed from 14 years of measurements from three Canadian satellite instruments. Horizontal and vertical coordinates have been chosen to minimize the effects of variability. To aid in analysis, model simulations have been used to characterize differences between instrument climatologies.
Viktoria F. Sofieva, Alexandra Laeng, Thomas von Clarmann, Gabriele Stiller, Michael Kiefer, Johanna Tamminen, Alexey Rozanov, Carlo Arosio, Nathaniel Livesey, Robert Damadeo, Patrick Sheese, Kaley A. Walker, Doug Degenstein, Daniel Zawada, Natalya A. Kramarova, and Arno Keppens
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This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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For satellite measurements of atmospheric composition, the random uncertainty estimates provided by retrieval algorithms might be imperfect due to various approximations used in the retrievals or presence of unknown error sources. This paper presents an overview of the methods used for validation of random uncertainty estimates. All methods discussed in this study are categorized, and assumptions and limitations of each method are discussed.
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Atmos. Chem. Phys., 25, 5199–5213, https://doi.org/10.5194/acp-25-5199-2025, https://doi.org/10.5194/acp-25-5199-2025, 2025
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Laura N. Saunders, Kaley A. Walker, Gabriele P. Stiller, Thomas von Clarmann, Florian Haenel, Hella Garny, Harald Bönisch, Chris D. Boone, Ariana E. Castillo, Andreas Engel, Johannes C. Laube, Marianna Linz, Felix Ploeger, David A. Plummer, Eric A. Ray, and Patrick E. Sheese
Atmos. Chem. Phys., 25, 4185–4209, https://doi.org/10.5194/acp-25-4185-2025, https://doi.org/10.5194/acp-25-4185-2025, 2025
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We present a 17-year stratospheric age-of-air dataset derived from ACE-FTS satellite measurements of sulfur hexafluoride. This is the longest continuous, global, and vertically resolved age of air time series available to date. In this paper, we show that this dataset agrees well with age-of-air datasets based on measurements from other instruments. We also present trends in the midlatitude lower stratosphere that indicate changes in the global circulation that are predicted by climate models.
Paul Konopka, Felix Ploeger, Francesco D'Amato, Teresa Campos, Marc von Hobe, Shawn B. Honomichl, Peter Hoor, Laura L. Pan, Michelle L. Santee, Silvia Viciani, Kaley A. Walker, and Michaela I. Hegglin
EGUsphere, https://doi.org/10.5194/egusphere-2025-1155, https://doi.org/10.5194/egusphere-2025-1155, 2025
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We present an improved version of the Chemical Lagrangian Model of the Stratosphere (CLaMS-3.0), which better represents transport from the lower atmosphere to the upper troposphere and lower stratosphere. By refining grid resolution and improving convection representation, the model more accurately simulates carbon monoxide transport. Comparisons with satellite and in situ observations highlight its ability to capture seasonal variations and improve our understanding of atmospheric transport.
Kimberlee Dubé, Susann Tegtmeier, Felix Ploeger, and Kaley A. Walker
Atmos. Chem. Phys., 25, 1433–1447, https://doi.org/10.5194/acp-25-1433-2025, https://doi.org/10.5194/acp-25-1433-2025, 2025
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Atmos. Meas. Tech., 17, 6983–7005, https://doi.org/10.5194/amt-17-6983-2024, https://doi.org/10.5194/amt-17-6983-2024, 2024
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Ozone measurements from the ACE-FTS satellite instrument have been compared to worldwide balloon-borne ozonesonde profiles using pairs of closely spaced profiles and monthly averaged profiles. ACE-FTS typically measures more ozone in the stratosphere by up to 10 %. The long-term stability of the ACE-FTS ozone data is good, exhibiting small (but non-significant) drifts of less than 3 % per decade in the stratosphere. Lower in the profiles, the calculated drifts are larger (up to 10 % per decade).
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Measurements of stratospheric aerosol from the MAESTRO instrument are compared to other measurements to assess their scientific value. We find that medians of MAESTRO measurements binned by month and latitude show reasonable correlation with other data sets, with notable increases after volcanic eruptions, and that biases in the data can be alleviated through a simple correction technique. Used with care, MAESTRO aerosol measurements provide information that can complement other data sets.
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Atmos. Chem. Phys., 24, 7927–7959, https://doi.org/10.5194/acp-24-7927-2024, https://doi.org/10.5194/acp-24-7927-2024, 2024
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Atmos. Meas. Tech., 17, 2429–2449, https://doi.org/10.5194/amt-17-2429-2024, https://doi.org/10.5194/amt-17-2429-2024, 2024
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Paul S. Jeffery, James R. Drummond, Jiansheng Zou, and Kaley A. Walker
Atmos. Chem. Phys., 24, 4253–4263, https://doi.org/10.5194/acp-24-4253-2024, https://doi.org/10.5194/acp-24-4253-2024, 2024
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The MOPITT instrument has been monitoring carbon monoxide (CO) since March 2000. This dataset has been used for many applications; however, episodic emission events, which release large amounts of CO into the atmosphere, are a major source of uncertainty. This study presents a method for identifying these events by determining measurements that are unlikely to have typically arisen. The distribution and frequency of these flagged measurements in the MOPITT dataset are presented and discussed.
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
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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.
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
Atmos. Chem. Phys., 23, 15655–15670, https://doi.org/10.5194/acp-23-15655-2023, https://doi.org/10.5194/acp-23-15655-2023, 2023
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The vortex-averaged ozone loss over the last 3 decades is evaluated for both polar regions using the passive ozone tracer of the chemical transport model TOMCAT/SLIMCAT and total ozone observations from the SAOZ network and MSR2 reanalysis. Three metrics were developed to compute ozone trends since 2000. The study confirms the ozone recovery in the Antarctic and shows a potential sign of quantitative detection of ozone recovery in the Arctic that needs to be robustly confirmed in the future.
Kimberlee Dubé, Susann Tegtmeier, Adam Bourassa, Daniel Zawada, Douglas Degenstein, Patrick E. Sheese, Kaley A. Walker, and William Randel
Atmos. Chem. Phys., 23, 13283–13300, https://doi.org/10.5194/acp-23-13283-2023, https://doi.org/10.5194/acp-23-13283-2023, 2023
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This paper presents a technique for understanding the causes of long-term changes in stratospheric composition. By using N2O as a proxy for stratospheric circulation in the model used to calculated trends, it is possible to separate the effects of dynamics and chemistry on observed trace gas trends. We find that observed HCl increases are due to changes in the stratospheric circulation, as are O3 decreases above 30 hPa in the Northern Hemisphere.
Vladimir Savastiouk, Henri Diémoz, and C. Thomas McElroy
Atmos. Meas. Tech., 16, 4785–4806, https://doi.org/10.5194/amt-16-4785-2023, https://doi.org/10.5194/amt-16-4785-2023, 2023
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This paper describes a way to significantly improve ozone measurements at low sun elevations and large ozone amounts when using the Brewer ozone spectrophotometer. The proposed algorithm will allow more uniform ozone measurements across the monitoring network. This will contribute to more reliable trend analysis and support the satellite validation. This research contributes to better understanding the physics of the instrument, and the new algorithm is based on this new knowledge.
Michael Kiefer, Dale F. Hurst, Gabriele P. Stiller, Stefan Lossow, Holger Vömel, John Anderson, Faiza Azam, Jean-Loup Bertaux, Laurent Blanot, Klaus Bramstedt, John P. Burrows, Robert Damadeo, Bianca Maria Dinelli, Patrick Eriksson, Maya García-Comas, John C. Gille, Mark Hervig, Yasuko Kasai, Farahnaz Khosrawi, Donal Murtagh, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Takafumi Sugita, Thomas von Clarmann, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 16, 4589–4642, https://doi.org/10.5194/amt-16-4589-2023, https://doi.org/10.5194/amt-16-4589-2023, 2023
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We quantify biases and drifts (and their uncertainties) between the stratospheric water vapor measurement records of 15 satellite-based instruments (SATs, with 31 different retrievals) and balloon-borne frost point hygrometers (FPs) launched at 27 globally distributed stations. These comparisons of measurements during the period 2000–2016 are made using robust, consistent statistical methods. With some exceptions, the biases and drifts determined for most SAT–FP pairs are < 10 % and < 1 % yr−1.
Vitali Fioletov, Xiaoyi Zhao, Ihab Abboud, Michael Brohart, Akira Ogyu, Reno Sit, Sum Chi Lee, Irina Petropavlovskikh, Koji Miyagawa, Bryan J. Johnson, Patrick Cullis, John Booth, Glen McConville, and C. Thomas McElroy
Atmos. Chem. Phys., 23, 12731–12751, https://doi.org/10.5194/acp-23-12731-2023, https://doi.org/10.5194/acp-23-12731-2023, 2023
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Stratospheric ozone within the Southern Hemisphere springtime polar vortex has been a subject of intense research since the discovery of the Antarctic ozone hole. The wintertime ozone in the vortex is less studied. We show that the recent wintertime ozone values over the South Pole were about 12 % below the pre-1980s level; i.e., the decline there was nearly twice as large as that over southern midlatitudes. Thus, wintertime ozone there can be used as an indicator of the ozone layer state.
Luis F. Millán, Gloria L. Manney, Harald Boenisch, Michaela I. Hegglin, Peter Hoor, Daniel Kunkel, Thierry Leblanc, Irina Petropavlovskikh, Kaley Walker, Krzysztof Wargan, and Andreas Zahn
Atmos. Meas. Tech., 16, 2957–2988, https://doi.org/10.5194/amt-16-2957-2023, https://doi.org/10.5194/amt-16-2957-2023, 2023
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The determination of atmospheric composition trends in the upper troposphere and lower stratosphere (UTLS) is still highly uncertain. We present the creation of dynamical diagnostics to map several ozone datasets (ozonesondes, lidars, aircraft, and satellite measurements) in geophysically based coordinate systems. The diagnostics can also be used to analyze other greenhouse gases relevant to surface climate and UTLS chemistry.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Carlo Arosio, Alexei Rozanov, Mark Weber, Doug Degenstein, Adam Bourassa, Daniel Zawada, Michael Kiefer, Alexandra Laeng, Kaley A. Walker, Patrick Sheese, Daan Hubert, Michel van Roozendael, Christian Retscher, Robert Damadeo, and Jerry D. Lumpe
Atmos. Meas. Tech., 16, 1881–1899, https://doi.org/10.5194/amt-16-1881-2023, https://doi.org/10.5194/amt-16-1881-2023, 2023
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The paper presents the updated SAGE-CCI-OMPS+ climate data record of monthly zonal mean ozone profiles. This dataset covers the stratosphere and combines measurements by nine limb and occultation satellite instruments (SAGE II, OSIRIS, MIPAS, SCIAMACHY, GOMOS, ACE-FTS, OMPS-LP, POAM III, and SAGE III/ISS). The update includes new versions of MIPAS, ACE-FTS, and OSIRIS datasets and introduces data from additional sensors (POAM III and SAGE III/ISS) and retrieval processors (OMPS-LP).
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.
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.
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.
Paul S. Jeffery, Kaley A. Walker, Chris E. Sioris, Chris D. Boone, Doug Degenstein, Gloria L. Manney, C. Thomas McElroy, Luis Millán, David A. Plummer, Niall J. Ryan, Patrick E. Sheese, and Jiansheng Zou
Atmos. Chem. Phys., 22, 14709–14734, https://doi.org/10.5194/acp-22-14709-2022, https://doi.org/10.5194/acp-22-14709-2022, 2022
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The upper troposphere–lower stratosphere is one of the most variable regions in the atmosphere. To improve our understanding of water vapour and ozone concentrations in this region, climatologies have been developed from 14 years of measurements from three Canadian satellite instruments. Horizontal and vertical coordinates have been chosen to minimize the effects of variability. To aid in analysis, model simulations have been used to characterize differences between instrument climatologies.
Kimberlee Dubé, Daniel Zawada, Adam Bourassa, Doug Degenstein, William Randel, David Flittner, Patrick Sheese, and Kaley Walker
Atmos. Meas. Tech., 15, 6163–6180, https://doi.org/10.5194/amt-15-6163-2022, https://doi.org/10.5194/amt-15-6163-2022, 2022
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Satellite observations are important for monitoring changes in atmospheric composition. Here we describe an improved version of the NO2 retrieval for the Optical Spectrograph and InfraRed Imager System. The resulting NO2 profiles are compared to those from the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer and the Stratospheric Aerosol and Gas Experiment III on the International Space Station. All datasets agree within 20 % throughout the stratosphere.
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
Preprint archived
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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.
William G. Read, Gabriele Stiller, Stefan Lossow, Michael Kiefer, Farahnaz Khosrawi, Dale Hurst, Holger Vömel, Karen Rosenlof, Bianca M. Dinelli, Piera Raspollini, Gerald E. Nedoluha, John C. Gille, Yasuko Kasai, Patrick Eriksson, Christopher E. Sioris, Kaley A. Walker, Katja Weigel, John P. Burrows, and Alexei Rozanov
Atmos. Meas. Tech., 15, 3377–3400, https://doi.org/10.5194/amt-15-3377-2022, https://doi.org/10.5194/amt-15-3377-2022, 2022
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This paper attempts to provide an assessment of the accuracy of 21 satellite-based instruments that remotely measure atmospheric humidity in the upper troposphere of the Earth's atmosphere. The instruments made their measurements from 1984 to the present time; however, most of these instruments began operations after 2000, and only a few are still operational. The objective of this study is to quantify the accuracy of each satellite humidity data set.
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.
Merritt Deeter, Gene Francis, John Gille, Debbie Mao, Sara Martínez-Alonso, Helen Worden, Dan Ziskin, James Drummond, Róisín Commane, Glenn Diskin, and Kathryn McKain
Atmos. Meas. Tech., 15, 2325–2344, https://doi.org/10.5194/amt-15-2325-2022, https://doi.org/10.5194/amt-15-2325-2022, 2022
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The MOPITT (Measurements of Pollution in the Troposphere) satellite instrument uses remote sensing to obtain retrievals (measurements) of carbon monoxide (CO) in the atmosphere. This paper describes the latest MOPITT data product, Version 9. Globally, the number of daytime MOPITT retrievals over land has increased by 30 %–40 % compared to the previous product. The reported improvements in the MOPITT product should benefit a wide variety of applications including studies of pollution sources.
Patrick E. Sheese, Kaley A. Walker, Chris D. Boone, Adam E. Bourassa, Doug A. Degenstein, Lucien Froidevaux, C. Thomas McElroy, Donal Murtagh, James M. Russell III, and Jiansheng Zou
Atmos. Meas. Tech., 15, 1233–1249, https://doi.org/10.5194/amt-15-1233-2022, https://doi.org/10.5194/amt-15-1233-2022, 2022
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This study analyzes the quality of two versions (v3.6 and v4.1) of ozone concentration measurements from the ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer), by comparing with data from five satellite instruments between 2004 and 2020. It was found that although the v3.6 data exhibit a better agreement than v4.1 with respect to the other instruments, v4.1 exhibits much better stability over time than v3.6. The stability of v4.1 makes it suitable for ozone trend studies.
Heba S. Marey, James R. Drummond, Dylan B. A. Jones, Helen Worden, Merritt N. Deeter, John Gille, and Debbie Mao
Atmos. Meas. Tech., 15, 701–719, https://doi.org/10.5194/amt-15-701-2022, https://doi.org/10.5194/amt-15-701-2022, 2022
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In this study, an analysis has been performed to understand the improvements in observational coverage over Canada in the new MOPITT V9 product. Temporal and spatial analysis of V9 indicates a general coverage gain of 15–20 % relative to V8, which varies regionally and seasonally; e.g., the number of successful MOPITT retrievals in V9 was doubled over Canada in winter. Also, comparison with the corresponding IASI instrument indicated generally good agreement, with about a 5–10 % positive bias.
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.
Alexey B. Tikhomirov, Glen Lesins, and James R. Drummond
Atmos. Meas. Tech., 14, 7123–7145, https://doi.org/10.5194/amt-14-7123-2021, https://doi.org/10.5194/amt-14-7123-2021, 2021
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Two commercial quadcopters (DJI Matrice 100 and M210 RTK) were equipped with an air temperature measurement system. They were flown at the Polar Environment Atmospheric Research Laboratory, Eureka, Nunavut, Canada, at 80° N latitude to study surface-based temperature inversion during February–March field campaigns in 2017 and 2020. It was demonstrated that the drones can be effectively used in the High Arctic to measure vertical temperature profiles up to 75 m off the ground.
Nathaniel J. Livesey, William G. Read, Lucien Froidevaux, Alyn Lambert, Michelle L. Santee, Michael J. Schwartz, Luis F. Millán, Robert F. Jarnot, Paul A. Wagner, Dale F. Hurst, Kaley A. Walker, Patrick E. Sheese, and Gerald E. Nedoluha
Atmos. Chem. Phys., 21, 15409–15430, https://doi.org/10.5194/acp-21-15409-2021, https://doi.org/10.5194/acp-21-15409-2021, 2021
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The Microwave Limb Sounder (MLS), an instrument on NASA's Aura mission launched in 2004, measures vertical profiles of the temperature and composition of Earth's "middle atmosphere" (the region from ~12 to ~100 km altitude). We describe how, among the 16 trace gases measured by MLS, the measurements of water vapor (H2O) and nitrous oxide (N2O) have started to drift since ~2010. The paper also discusses the origins of this drift and work to ameliorate it in a new version of the MLS dataset.
Francesco Grieco, Kristell Pérot, Donal Murtagh, Patrick Eriksson, Bengt Rydberg, Michael Kiefer, Maya Garcia-Comas, Alyn Lambert, and Kaley A. Walker
Atmos. Meas. Tech., 14, 5823–5857, https://doi.org/10.5194/amt-14-5823-2021, https://doi.org/10.5194/amt-14-5823-2021, 2021
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We present improved Odin/SMR mesospheric H2O concentration and temperature data sets, reprocessed assuming a bigger sideband leakage of the instrument. The validation study shows how the improved SMR data sets agree better with other instruments' observations than the old SMR version did. Given their unique time extension and geographical coverage, and H2O being a good tracer of mesospheric circulation, the new data sets are valuable for the study of dynamical processes and multi-year trends.
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.
Michaela I. Hegglin, Susann Tegtmeier, John Anderson, Adam E. Bourassa, Samuel Brohede, Doug Degenstein, Lucien Froidevaux, Bernd Funke, John Gille, Yasuko Kasai, Erkki T. Kyrölä, Jerry Lumpe, Donal Murtagh, Jessica L. Neu, Kristell Pérot, Ellis E. Remsberg, Alexei Rozanov, Matthew Toohey, Joachim Urban, Thomas von Clarmann, Kaley A. Walker, Hsiang-Jui Wang, Carlo Arosio, Robert Damadeo, Ryan A. Fuller, Gretchen Lingenfelser, Christopher McLinden, Diane Pendlebury, Chris Roth, Niall J. Ryan, Christopher Sioris, Lesley Smith, and Katja Weigel
Earth Syst. Sci. Data, 13, 1855–1903, https://doi.org/10.5194/essd-13-1855-2021, https://doi.org/10.5194/essd-13-1855-2021, 2021
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An overview of the SPARC Data Initiative is presented, to date the most comprehensive assessment of stratospheric composition measurements spanning 1979–2018. Measurements of 26 chemical constituents obtained from an international suite of space-based limb sounders were compiled into vertically resolved, zonal monthly mean time series. The quality and consistency of these gridded datasets are then evaluated using a climatological validation approach and a range of diagnostics.
Patrick E. Sheese, Kaley A. Walker, Chris D. Boone, Doug A. Degenstein, Felicia Kolonjari, David Plummer, Douglas E. Kinnison, Patrick Jöckel, and Thomas von Clarmann
Atmos. Meas. Tech., 14, 1425–1438, https://doi.org/10.5194/amt-14-1425-2021, https://doi.org/10.5194/amt-14-1425-2021, 2021
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Output from climate chemistry models (CMAM, EMAC, and WACCM) is used to estimate the expected geophysical variability of ozone concentrations between coincident satellite instrument measurement times and geolocations. We use the Canadian ACE-FTS and OSIRIS instruments as a case study. Ensemble mean estimates are used to optimize coincidence criteria between the two instruments, allowing for the use of more coincident profiles while providing an estimate of the geophysical variation.
Emily M. Gordon, Annika Seppälä, Bernd Funke, Johanna Tamminen, and Kaley A. Walker
Atmos. Chem. Phys., 21, 2819–2836, https://doi.org/10.5194/acp-21-2819-2021, https://doi.org/10.5194/acp-21-2819-2021, 2021
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Energetic particle precipitation (EPP) is the rain of solar energetic particles into the Earth's atmosphere. EPP is known to deplete O3 in the polar mesosphere–upper stratosphere via the formation of NOx. NOx also causes chlorine deactivation in the lower stratosphere and has, thus, been proposed to potentially result in reduced ozone depletion in the spring. We provide the first evidence to show that NOx formed by EPP is able to remove active chlorine, resulting in enhanced total ozone column.
Seidai Nara, Tomohiro O. Sato, Takayoshi Yamada, Tamaki Fujinawa, Kota Kuribayashi, Takeshi Manabe, Lucien Froidevaux, Nathaniel J. Livesey, Kaley A. Walker, Jian Xu, Franz Schreier, Yvan J. Orsolini, Varavut Limpasuvan, Nario Kuno, and Yasuko Kasai
Atmos. Meas. Tech., 13, 6837–6852, https://doi.org/10.5194/amt-13-6837-2020, https://doi.org/10.5194/amt-13-6837-2020, 2020
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In the atmosphere, more than 80 % of chlorine compounds are anthropogenic. Hydrogen chloride (HCl), the main stratospheric chlorine reservoir, is useful to estimate the total budget of the atmospheric chlorine compounds. We report, for the first time, the HCl vertical distribution from the middle troposphere to the lower thermosphere using a high-sensitivity SMILES measurement; the data quality is quantified by comparisons with other measurements and via theoretical error analysis.
Francesco Grieco, Kristell Pérot, Donal Murtagh, Patrick Eriksson, Peter Forkman, Bengt Rydberg, Bernd Funke, Kaley A. Walker, and Hugh C. Pumphrey
Atmos. Meas. Tech., 13, 5013–5031, https://doi.org/10.5194/amt-13-5013-2020, https://doi.org/10.5194/amt-13-5013-2020, 2020
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We present a unique – by time extension and geographical coverage – dataset of satellite observations of carbon monoxide (CO) in the mesosphere which will allow us to study dynamical processes, since CO is a very good tracer of circulation in the mesosphere. Previously, the dataset was unusable due to instrumental artefacts that affected the measurements. We identify the cause of the artefacts, eliminate them and prove the quality of the results by comparing with other instrument measurements.
Cited articles
ACE-FTS: Version 4.1/4.2 Level 2 Data, ACE-FTS [data set], https://databace.scisat.ca/level2/ (last access: 10 June 2024), 2024a. a
ACE-FTS: Version 5.2 Level 2 Data, ACE-FTS [data set], available at: https://databace.scisat.ca/level2/ (last access: 10 June 2024), 2024b. a
Adams, C., Strong, K., Batchelor, R. L., Bernath, P. F., Brohede, S., Boone, C., Degenstein, D., Daffer, W. H., Drummond, J. R., Fogal, P. F., Farahani, E., Fayt, C., Fraser, A., Goutail, F., Hendrick, F., Kolonjari, F., Lindenmaier, R., Manney, G., McElroy, C. T., McLinden, C. A., Mendonca, J., Park, J.-H., Pavlovic, B., Pazmino, A., Roth, C., Savastiouk, V., Walker, K. A., Weaver, D., and Zhao, X.: Validation of ACE and OSIRIS ozone and NO2 measurements using ground-based instruments at 80° N, Atmos. Meas. Tech., 5, 927–953, https://doi.org/10.5194/amt-5-927-2012, 2012. a, b, c, d
Adams, C., Bourassa, A. E., Bathgate, A. F., McLinden, C. A., Lloyd, N. D., Roth, C. Z., Llewellyn, E. J., Zawodny, J. M., Flittner, D. E., Manney, G. L., Daffer, W. H., and Degenstein, D. A.: Characterization of Odin-OSIRIS ozone profiles with the SAGE II dataset, Atmos. Meas. Tech., 6, 1447–1459, https://doi.org/10.5194/amt-6-1447-2013, 2013. a
Adams, C., Bourassa, A. E., Sofieva, V., Froidevaux, L., McLinden, C. A., Hubert, D., Lambert, J.-C., Sioris, C. E., and Degenstein, D. A.: Assessment of Odin-OSIRIS ozone measurements from 2001 to the present using MLS, GOMOS, and ozonesondes, Atmos. Meas. Tech., 7, 49–64, https://doi.org/10.5194/amt-7-49-2014, 2014. a
Bauer, R., Rozanov, A., McLinden, C. A., Gordley, L. L., Lotz, W., Russell III, J. M., Walker, K. A., Zawodny, J. M., Ladstätter-Weißenmayer, A., Bovensmann, H., and Burrows, J. P.: Validation of SCIAMACHY limb NO2 profiles using solar occultation measurements, Atmos. Meas. Tech., 5, 1059–1084, https://doi.org/10.5194/amt-5-1059-2012, 2012. a
Bernath, P. F.: The Atmospheric Chemistry Experiment (ACE), J. Quant. Spectrosc. Ra., 186, 3–16, https://doi.org/10.1016/j.jqsrt.2016.04.006, 2017. a, b, c
Bernath, P. F., McElroy, C. T., Abrams, M. C., Boone, C. D., Butler, M., Camy-Peyret, C., Carleer, M., Clerbaux, C., Coheur, P.-F., Colin, R., DeCola, P., DeMazière, M., Drummond, J. R., Dufour, D., Evans, W. F. J., Fast, H., Fussen, D., Gilbert, K., Jennings, D. E., Llewellyn, E. J., Lowe, R. P., Mahieu, E., McConnell, J. C., McHugh, M., McLeod, S. D., Michaud, R., Midwinter, C., Nassar, R., Nichitiu, F., Nowlan, C., Rinsland, C. P., Rochon, Y. J., Rowlands, N., Semeniuk, K., Simon, P., Skelton, R., Sloan, J. J., Soucy, M.-A., Strong, K., Tremblay, P., Turnbull, D., Walker, K. A., Walkty, I., Wardle, D. A., Wehrle, V., Zander, R., and Zou, J.: Atmospheric Chemistry Experiment (ACE): Mission overview, Geophys. Res. Lett., 32, L15S01, https://doi.org/10.1029/2005GL022386, 2005. a, b, c
Bertaux, J. L., Kyrölä, E., Fussen, D., Hauchecorne, A., Dalaudier, F., Sofieva, V., Tamminen, J., Vanhellemont, F., Fanton d'Andon, O., Barrot, G., Mangin, A., Blanot, L., Lebrun, J. C., Pérot, K., Fehr, T., Saavedra, L., Leppelmeier, G. W., and Fraisse, R.: Global ozone monitoring by occultation of stars: an overview of GOMOS measurements on ENVISAT, Atmos. Chem. Phys., 10, 12091–12148, https://doi.org/10.5194/acp-10-12091-2010, 2010. a, b
Bognar, K., Zhao, X., Strong, K., Boone, C. D., Bourassa, A. E., Degenstein, D. A., Drummond, J. R., Duff, A., Goutail, F., Griffin, D., Jeffery, P. S., Lutsch, E., Manney, G. L., McElroy, C. T., McLinden, C. A., Millán, L. F., Pazmino, A., Sioris, C. E., Walker, K. A., and Zou, J.: Updated validation of ACE and OSIRIS ozone and NO2 measurements in the Arctic using ground-based instruments at Eureka, Canada, J. Quant. Spectrosc. Ra., 238, 106571, https://doi.org/10.1016/j.jqsrt.2019.07.014, 2019. a, b, c, d
Bognar, K., Tegtmeier, S., Bourassa, A., Roth, C., Warnock, T., Zawada, D., and Degenstein, D.: Stratospheric ozone trends for 1984–2021 in the SAGE II–OSIRIS–SAGE III/ISS composite dataset, Atmos. Chem. Phys., 22, 9553–9569, https://doi.org/10.5194/acp-22-9553-2022, 2022. a, b
Boone, C. D., Nassar, R., Walker, K. A., Rochon, Y., McLeod, S. D., Rinsland, C. P., and Bernath, P. F.: Retrievals for the atmospheric chemistry experiment Fourier-transform spectrometer, Appl. Opt., 44, 7218–7231, https://doi.org/10.1364/AO.44.007218, 2005. a
Boone, C. D., Walker, K. A., and Bernath, P. F.: Version 3 retrievals for the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), in: The Atmospheric Chemistry Experiment ACE at 10: A Solar Occultation Anthology, 103–127 pp., A. Deepak Publishing, Hampton, Virginia, USA, 103–127 pp., ISBN 978-0-937194-54-9, 2013. a
Boone, C. D., Bernath, P. F., Cok, D., Jones, S. C., and Steffen, J.: Version 4 retrievals for the atmospheric chemistry experiment Fourier transform spectrometer (ACE-FTS) and imagers, J. Quant. Spectrosc. Ra., 247, 106939, https://doi.org/10.1016/j.jqsrt.2020.106939, 2020. a
Boone, C. D., Bernath, P. F., and Lecours, M.: Version 5 retrievals for ACE-FTS and ACE-imagers, J. Quant. Spectrosc. Ra., 310, 108749, https://doi.org/10.1016/j.jqsrt.2023.108749, 2023. a, b
Bourassa, A. E., Degenstein, D. A., Randel, W. J., Zawodny, J. M., Kyrölä, E., McLinden, C. A., Sioris, C. E., and Roth, C. Z.: Trends in stratospheric ozone derived from merged SAGE II and Odin-OSIRIS satellite observations, Atmos. Chem. Phys., 14, 6983–6994, https://doi.org/10.5194/acp-14-6983-2014, 2014. a
Bovensmann, H., Burrows, J. P., Buchwitz, M., Frerick, J., Noël, S., Rozanov, V. V., Chance, K. V., and Goede, A. P. H.: SCIAMACHY: Mission Objectives and Measurement Modes, J. Atmos. Sci., 56, 127–150, https://doi.org/10.1175/1520-0469(1999)056<0127:SMOAMM>2.0.CO;2, 1999. a
Brasseur, G. P. and Solomon, S.: Aeronomy of the middle atmosphere: Chemistry and physics of the stratosphere and mesosphere, 3rd Edn., Springer Netherlands, Dordrecht, Great Britain, https://doi.org/10.1007/1-4020-3824-0, 2005. a, b
Buehner, M., McTaggart-Cowan, R., Beaulne, A., Charette, C., Garand, L., Heilliette, S., Lapalme, E., Laroche, S., Macpherson, S. R., Morneau, J., and Zadra, A.: Implementation of deterministic weather forecasting systems based on ensemble–variational data assimilation at Environment Canada. Part I: The global system, Mon. Weather Rev., 143, 2532–2559, https://doi.org/10.1175/MWR-D-14-00354.1, 2015. a
Burrows, J. P., Hölzle, E., Goede, A. P. H., Visser, H., and Fricke, W.: SCIAMACHY – scanning imaging absorption spectrometer for atmospheric chartography, Acta Astronaut., 35, 445–451, https://doi.org/10.1016/0094-5765(94)00278-T, 1995. a
Chin, M., Ginoux, P., Kinne, S., Torres, O., Holben, B. N., Duncan, B. N., Martin, R. V., Logan, J. A., Higurashi, A., and Nakajima, T.: Tropospheric Aerosol Optical Thickness from the GOCART Model and Comparisons with Satellite and Sun Photometer Measurements, J. Atmos. Sci., 59, 461–483, https://doi.org/10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2, 2002. a
Chu, W. P., McCormick, M. P., Lenoble, J., Brogniez, C., and Pruvost, P.: SAGE II inversion algorithm, J. Geophys. Res.-Atmos., 94, 8339–8351, https://doi.org/10.1029/JD094iD06p08339, 1989. a
Colarco, P., da Silva, A., Chin, M., and Diehl, T.: Online simulations of global aerosol distributions in the NASA GEOS-4 model and comparisons to satellite and ground-based aerosol optical depth, J. Geophys. Res.-Atmos., 115, D14207, https://doi.org/10.1029/2009JD012820, 2010. a
Davis, S. M., Rosenlof, K. H., Hassler, B., Hurst, D. F., Read, W. G., Vömel, H., Selkirk, H., Fujiwara, M., and Damadeo, R.: The Stratospheric Water and Ozone Satellite Homogenized (SWOOSH) database: a long-term database for climate studies, Earth Syst. Sci. Data, 8, 461–490, https://doi.org/10.5194/essd-8-461-2016, 2016. a
Degenstein, D. A., Bourassa, A. E., Roth, C. Z., and Llewellyn, E. J.: Limb scatter ozone retrieval from 10 to 60 km using a multiplicative algebraic reconstruction technique, Atmos. Chem. Phys., 9, 6521–6529, https://doi.org/10.5194/acp-9-6521-2009, 2009. a
Dubé, K., Bourassa, A., Zawada, D., Degenstein, D., Damadeo, R., Flittner, D., and Randel, W.: Accounting for the photochemical variation in stratospheric NO2 in the SAGE III/ISS solar occultation retrieval, Atmos. Meas. Tech., 14, 557–566, https://doi.org/10.5194/amt-14-557-2021, 2021. a, b, c
Dubé, K., Zawada, D., Bourassa, A., Degenstein, D., Randel, W., Flittner, D., Sheese, P., and Walker, K.: An improved OSIRIS NO2 profile retrieval in the upper troposphere–lower stratosphere and intercomparison with ACE-FTS and SAGE III/ISS, Atmos. Meas. Tech., 15, 6163–6180, https://doi.org/10.5194/amt-15-6163-2022, 2022. a, b, c, d, e
Dufour, D. G., Drummond, J. R., McElroy, C. T., Midwinter, C., Bernath, P. F., Walker, K. A., and Nowlan, C.: Simultaneous Measurements of Visible (400−-700 nm) and Infrared (3.4 µm) NO2 Absorption, J. Phys. Chem. A, 110, 12414–12418, https://doi.org/10.1021/jp0634306, 2006. a, b
Duncan, B. N., Strahan, S. E., Yoshida, Y., Steenrod, S. D., and Livesey, N.: Model study of the cross-tropopause transport of biomass burning pollution, Atmos. Chem. Phys., 7, 3713–3736, https://doi.org/10.5194/acp-7-3713-2007, 2007. a
Dupuy, E., Walker, K. A., Kar, J., Boone, C. D., McElroy, C. T., Bernath, P. F., Drummond, J. R., Skelton, R., McLeod, S. D., Hughes, R. C., Nowlan, C. R., Dufour, D. G., Zou, J., Nichitiu, F., Strong, K., Baron, P., Bevilacqua, R. M., Blumenstock, T., Bodeker, G. E., Borsdorff, T., Bourassa, A. E., Bovensmann, H., Boyd, I. S., Bracher, A., Brogniez, C., Burrows, J. P., Catoire, V., Ceccherini, S., Chabrillat, S., Christensen, T., Coffey, M. T., Cortesi, U., Davies, J., De Clercq, C., Degenstein, D. A., De Mazière, M., Demoulin, P., Dodion, J., Firanski, B., Fischer, H., Forbes, G., Froidevaux, L., Fussen, D., Gerard, P., Godin-Beekmann, S., Goutail, F., Granville, J., Griffith, D., Haley, C. S., Hannigan, J. W., Höpfner, M., Jin, J. J., Jones, A., Jones, N. B., Jucks, K., Kagawa, A., Kasai, Y., Kerzenmacher, T. E., Kleinböhl, A., Klekociuk, A. R., Kramer, I., Küllmann, H., Kuttippurath, J., Kyrölä, E., Lambert, J.-C., Livesey, N. J., Llewellyn, E. J., Lloyd, N. D., Mahieu, E., Manney, G. L., Marshall, B. T., McConnell, J. C., McCormick, M. P., McDermid, I. S., McHugh, M., McLinden, C. A., Mellqvist, J., Mizutani, K., Murayama, Y., Murtagh, D. P., Oelhaf, H., Parrish, A., Petelina, S. V., Piccolo, C., Pommereau, J.-P., Randall, C. E., Robert, C., Roth, C., Schneider, M., Senten, C., Steck, T., Strandberg, A., Strawbridge, K. B., Sussmann, R., Swart, D. P. J., Tarasick, D. W., Taylor, J. R., Tétard, C., Thomason, L. W., Thompson, A. M., Tully, M. B., Urban, J., Vanhellemont, F., Vigouroux, C., von Clarmann, T., von der Gathen, P., von Savigny, C., Waters, J. W., Witte, J. C., Wolff, M., and Zawodny, J. M.: Validation of ozone measurements from the Atmospheric Chemistry Experiment (ACE), Atmos. Chem. Phys., 9, 287–343, https://doi.org/10.5194/acp-9-287-2009, 2009. a, b, c
EOS MLS Science Team: MLS/Aura Near-Real-Time L2 Ozone (O3) Mixing Ratio V005, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://disc.gsfc.nasa.gov/datacollection/ML2O3_NRT_005.html (last access: 11 June 2024), 2022. a
Eriksson, P.: Odin/SMR Algorithm Theoretical Basis Document – Level 2 processing, Tech. rep., Department of Space, Earth and Environment, Chalmers University of Technology, http://odin.rss.chalmers.se/static/documents/PVER.pdf (last access: 10 June 2024), 2020. a
European Space Agency: Envisat GOMOS Level 2 – Atmospheric constituents profiles – Gridded User Friendly Product [GOMOS_UFP_gridded], Version R/IPF 6.01, European Space Agency [data set], https://doi.org/10.57780/EN1-a0f1eee, 2017. a
European Space Agency: Odin SMR Level 2 data products, Version 3 [data set], available at: https://odin.rss.chalmers.se/level2 (last access: 10 June 2024), 2024. a
Fischer, H., Birk, M., Blom, C., Carli, B., Carlotti, M., von Clarmann, T., Delbouille, L., Dudhia, A., Ehhalt, D., Endemann, M., Flaud, J. M., Gessner, R., Kleinert, A., Koopman, R., Langen, J., López-Puertas, M., Mosner, P., Nett, H., Oelhaf, H., Perron, G., Remedios, J., Ridolfi, M., Stiller, G., and Zander, R.: MIPAS: an instrument for atmospheric and climate research, Atmos. Chem. Phys., 8, 2151–2188, https://doi.org/10.5194/acp-8-2151-2008, 2008. a, b
Flynn, L. E., Homstein, J., and Hilsenrath, E.: The ozone mapping and profiler suite (OMPS). The next generation of US ozone monitoring instruments, in: IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium, Vol. 1, p. 155, https://doi.org/10.1109/IGARSS.2004.1368968, 2004. a
Funke, B., López-Puertas, M., Stiller, G., v. Clarmann, T., and Höpfner, M.: A new non-LTE retrieval method for atmospheric parameters from mipas-envisat emission spectra, Adv. Space Res., 27, 1099–1104, https://doi.org/10.1016/S0273-1177(01)00169-7, 2001. a
Funke, B., García-Comas, M., Glatthor, N., Grabowski, U., Kellmann, S., Kiefer, M., Linden, A., López-Puertas, M., Stiller, G. P., and von Clarmann, T.: Michelson Interferometer for Passive Atmospheric Sounding Institute of Meteorology and Climate Research/Instituto de Astrofísica de Andalucía version 8 retrieval of nitric oxide and lower-thermospheric temperature, Atmos. Meas. Tech., 16, 2167–2196, https://doi.org/10.5194/amt-16-2167-2023, 2023. a
Gebhardt, C., Rozanov, A., Hommel, R., Weber, M., Bovensmann, H., Burrows, J. P., Degenstein, D., Froidevaux, L., and Thompson, A. M.: Stratospheric ozone trends and variability as seen by SCIAMACHY from 2002 to 2012, Atmos. Chem. Phys., 14, 831–846, https://doi.org/10.5194/acp-14-831-2014, 2014. a
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017. a
Haley, C. S., Brohede, S. M., Sioris, C. E., Griffioen, E., Murtagh, D. P., McDade, I. C., Eriksson, P., Llewellyn, E. J., Bazureau, A., and Goutail, F.: Retrieval of stratospheric O3 and NO2 profiles from Odin Optical Spectrograph and Infrared Imager System (OSIRIS) limb-scattered sunlight measurements, J. Geophys. Res.-Atmos., 109, D16303, https://doi.org/10.1029/2004JD004588, 2004. a
Hedin, A. E.: Extension of the MSIS Thermosphere Model into the middle and lower atmosphere, J. Geophys. Res.-Space, 96, 1159–1172, https://doi.org/10.1029/90JA02125, 1991. a
Hegglin, M. I., Tegtmeier, S., Anderson, J., Bourassa, A. E., Brohede, S., Degenstein, D., Froidevaux, L., Funke, B., Gille, J., Kasai, Y., Kyrölä, E. T., Lumpe, J., Murtagh, D., Neu, J. L., Pérot, K., Remsberg, E. E., Rozanov, A., Toohey, M., Urban, J., von Clarmann, T., Walker, K. A., Wang, H.-J., Arosio, C., Damadeo, R., Fuller, R. A., Lingenfelser, G., McLinden, C., Pendlebury, D., Roth, C., Ryan, N. J., Sioris, C., Smith, L., and Weigel, K.: Overview and update of the SPARC Data Initiative: comparison of stratospheric composition measurements from satellite limb sounders, Earth Syst. Sci. Data, 13, 1855–1903, https://doi.org/10.5194/essd-13-1855-2021, 2021. a, b, c, d, e
Hubert, D., Lambert, J.-C., Verhoelst, T., Granville, J., Keppens, A., Baray, J.-L., Bourassa, A. E., Cortesi, U., Degenstein, D. A., Froidevaux, L., Godin-Beekmann, S., Hoppel, K. W., Johnson, B. J., Kyrölä, E., Leblanc, T., Lichtenberg, G., Marchand, M., McElroy, C. T., Murtagh, D., Nakane, H., Portafaix, T., Querel, R., Russell III, J. M., Salvador, J., Smit, H. G. J., Stebel, K., Steinbrecht, W., Strawbridge, K. B., Stübi, R., Swart, D. P. J., Taha, G., Tarasick, D. W., Thompson, A. M., Urban, J., van Gijsel, J. A. E., Van Malderen, R., von der Gathen, P., Walker, K. A., Wolfram, E., and Zawodny, J. M.: Ground-based assessment of the bias and long-term stability of 14 limb and occultation ozone profile data records, Atmos. Meas. Tech., 9, 2497–2534, https://doi.org/10.5194/amt-9-2497-2016, 2016. a
Jacob, D. J.: Introduction to Atmospheric Chemistry, Princeton University Press, Princeton, NJ, USA, 1st Edn., 266 pp., https://doi.org/10.1515/9781400841547, 1999. a
Jaross, G., Bhartia, P. K., Chen, G., Kowitt, M., Haken, M., Chen, Z., Xu, P., Warner, J., and Kelly, T.: OMPS Limb Profiler instrument performance assessment, J. Geophys. Res.-Atmos., 119, 4399–4412, https://doi.org/10.1002/2013JD020482, 2014. a
Jia, J., Rozanov, A., Ladstätter-Weißenmayer, A., and Burrows, J. P.: Global validation of SCIAMACHY limb ozone data (versions 2.9 and 3.0, IUP Bremen) using ozonesonde measurements, Atmos. Meas. Tech., 8, 3369–3383, https://doi.org/10.5194/amt-8-3369-2015, 2015. a, b
Justus, C. G. and Johnson, D. L.: The GRAM model: Status of development and future aspects, Adv. Space Res., 19, 549–558, https://doi.org/10.1016/S0273-1177(97)00170-1, 1997. a, b
Kar, J., McElroy, C. T., Drummond, J. R., Zou, J., Nichitiu, F., Walker, K. A., Randall, C. E., Nowlan, C. R., Dufour, D. G., Boone, C. D., Bernath, P. F., Trepte, C. R., Thomason, L. W., and McLinden, C.: Initial comparison of ozone and NO2 profiles from ACE-MAESTRO with balloon and satellite data, J. Geophys. Res.-Atmos., 112, https://doi.org/10.1029/2006JD008242, 2007. a, b
Kerzenmacher, T. E., Walker, K. A., Strong, K., Berman, R., Bernath, P. F., Boone, C. D., Drummond, J. R., Fast, H., Fraser, A., MacQuarrie, K., Midwinter, C., Sung, K., McElroy, C. T., Mittermeier, R. L., Walker, J., and Wu, H.: Measurements of O3, NO2 and temperature during the 2004 Canadian Arctic ACE Validation Campaign, Geophys. Res. Lett., 32, L16S07, https://doi.org/10.1029/2005GL023032, 2005. a
Kiefer, M., von Clarmann, T., Funke, B., García-Comas, M., Glatthor, N., Grabowski, U., Kellmann, S., Kleinert, A., Laeng, A., Linden, A., López-Puertas, M., Marsh, D. R., and Stiller, G. P.: IMK/IAA MIPAS temperature retrieval version 8: nominal measurements, Atmos. Meas. Tech., 14, 4111–4138, https://doi.org/10.5194/amt-14-4111-2021, 2021. a
Kiefer, M., von Clarmann, T., Funke, B., García-Comas, M., Glatthor, N., Grabowski, U., Höpfner, M., Kellmann, S., Laeng, A., Linden, A., López-Puertas, M., and Stiller, G. P.: Version 8 IMK–IAA MIPAS ozone profiles: nominal observation mode, Atmos. Meas. Tech., 16, 1443–1460, https://doi.org/10.5194/amt-16-1443-2023, 2023. a
Kramarova, N. A.: OMPS-NPP L2 LP Ozone (O3) Vertical Profile swath daily Center slit V2.6, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/8MO7DEDYTBH7, 2023. a
Kramarova, N. A., Bhartia, P. K., Jaross, G., Moy, L., Xu, P., Chen, Z., DeLand, M., Froidevaux, L., Livesey, N., Degenstein, D., Bourassa, A., Walker, K. A., and Sheese, P.: Validation of ozone profile retrievals derived from the OMPS LP version 2.5 algorithm against correlative satellite measurements, Atmos. Meas. Tech., 11, 2837–2861, https://doi.org/10.5194/amt-11-2837-2018, 2018. a, b
Kremser, S., Thomason, L. W., and Bird, L. J.: Simplified SAGE II ozone data usage rules, Earth Syst. Sci. Data, 12, 1419–1435, https://doi.org/10.5194/essd-12-1419-2020, 2020. a
Kyrölä, E., Tamminen, J., Leppelmeier, G. W., Sofieva, V., Hassinen, S., Bertaux, J. L., Hauchecorne, A., Dalaudier, F., Cot, C., Korablev, O., Fanton d’Andon, O., Barrot, G., Mangin, A., Théodore, B., Guirlet, M., Etanchaud, F., Snoeij, P., Koopman, R., Saavedra, L., Fraisse, R., Fussen, D., and Vanhellemont, F.: GOMOS on Envisat: an overview, Adv. Space Res., 33, 1020–1028, https://doi.org/10.1016/S0273-1177(03)00590-8, 2004. a
Kyrölä, E., Tamminen, J., Sofieva, V., Bertaux, J. L., Hauchecorne, A., Dalaudier, F., Fussen, D., Vanhellemont, F., Fanton d'Andon, O., Barrot, G., Guirlet, M., Mangin, A., Blanot, L., Fehr, T., Saavedra de Miguel, L., and Fraisse, R.: Retrieval of atmospheric parameters from GOMOS data, Atmos. Chem. Phys., 10, 11881–11903, https://doi.org/10.5194/acp-10-11881-2010, 2010. a, b
Lacis, A. A., Wuebbles, D. J., and Logan, J. A.: Radiative forcing of climate by changes in the vertical distribution of ozone, J. Geophys. Res.-Atmos., 95, 9971–9981, https://doi.org/10.1029/JD095iD07p09971, 1990. a
Laeng, A., von Clarmann, T., Stiller, G., Dinelli, B. M., Dudhia, A., Raspollini, P., Glatthor, N., Grabowski, U., Sofieva, V., Froidevaux, L., Walker, K. A., and Zehner, C.: Merged ozone profiles from four MIPAS processors, Atmos. Meas. Tech., 10, 1511–1518, https://doi.org/10.5194/amt-10-1511-2017, 2017. a
Livesey, N. J., Read, W. G., Wagner, P. A., Froidevaux, L., Santee, M. L., Schwartz, M. J., Lambert, A. ad Millán Valle, L. F., Pumphrey, H. C., Manney, G. L., Fuller, R. A., Jarnot, R. F., Knosp, B. W., and Lay, R. R.: Earth Observing System (EOS) Aura Microwave Limb Sounder (MLS) Version 5.0x Level 2 and 3 data quality and description document., Tech. rep., Jet Propulsion Laboratory, https://mls.jpl.nasa.gov/data/v5-0_data_quality_document.pdf (last access: 5 February 2024) 2022. a, b, c
Llewellyn, E. J., Lloyd, N. D., Degenstein, D. A., Gattinger, R. L., Petelina, S. V., Bourassa, A. E., Wiensz, J. T., Ivanov, E. V., McDade, I. C., Solheim, B. H., McConnell, J. C., Haley, C. S., von Savigny, C., Sioris, C. E., McLinden, C. A., Griffioen, E., Kaminski, J., Evans, W. F. J., Puckrin, E., Strong, K., Wehrle, V., Hum, R. H., Kendall, D. J. W., Matsushita, J., Murtagh, D. P., Brohede, S., Stegman, J., Witt, G., Barnes, G., Payne, W. F., Piché, L., Smith, K., Warshaw, G., Deslauniers, D.-L., Marchand, P., Richardson, E. H., King, R. A., Wevers, I., McCreath, W., Kyrölä, E., Oikarinen, L., Leppelmeier, G. W., Auvinen, H., Mégie, G., Hauchecorne, A., Lefèvre, F., de La Nöe, J., Ricaud, P., Frisk, U., Sjoberg, F., von Schéele, F., and Nordh, L.: The OSIRIS instrument on the Odin spacecraft, Can. J. Phys., 82, 411–422, https://doi.org/10.1139/p04-005, 2004. a, b
Loew, A., Bell, W., Brocca, L., Bulgin, C. E., Burdanowitz, J., Calbet, X., Donner, R. V., Ghent, D., Gruber, A., Kaminski, T., Kinzel, J., Klepp, C., Lambert, J.-C., Schaepman-Strub, G., Schröder, M., and Verhoelst, T.: Validation practices for satellite-based Earth observation data across communities, Rev. Geophys., 55, 779–817, https://doi.org/10.1002/2017RG000562, 2017. a
MAESTRO: Version 4 Level 2 Data, MAESTRO [data set], available at: https://databace. scisat.ca/level2/mae_v4.5 (last access: 10 June 2024), 2024. a
Manney, G. L., Santee, M. L., and Zinoviev, N. S.: Unprecedented Arctic ozone loss in 2011, Nature, 478, 469–475, https://doi.org/10.1038/nature10556, 2011. a
Mauldin III, L. E., Zaun, N. H., McCormick Jr., M. P., Guy, J. H., and Vaughn, W. r.: Stratospheric Aerosol And Gas Experiment II Instrument: A Functional Description, Opt. Eng., 24, 242307, https://doi.org/10.1117/12.7973473, 1985. a, b
Mauldin III, L. E., Salikhov, R., Habib, S., Vladimirov, A. G., Carraway, D., Petrenko, G., and Comella, J.: Meteor-3M(1)/Stratospheric Aerosol and Gas Experiment III (SAGE III) jointly sponsored by the National Aeronautics and Space Administration and the Russian Space Agency, in: Optical Remote Sensing of the Atmosphere and Clouds, edited by: Wang, J., Wu, B., Ogawa, T., and Guan, Z., Vol. 3501, 355–365 pp., International Society for Optics and Photonics, SPIE, https://doi.org/10.1117/12.317767, 1998. a, b
McCormick, M. P.: Sage II: An overview, Adv. Space Res., 7, 219–226, https://doi.org/10.1016/0273-1177(87)90151-7, 1987. a, b
McCormick, M. P., Zawodny, J. M., Veiga, R. E., Larsen, J. C., and Wang, P. H.: An overview of sage I and II ozone measurements, Planet. Space Sci., 37, 1567–1586, https://doi.org/10.1016/0032-0633(89)90146-3, 1989. a
McCormick, M. P., Lei, L., Hill, M. T., Anderson, J., Querel, R., and Steinbrecht, W.: Early results and validation of SAGE III-ISS ozone profile measurements from onboard the International Space Station, Atmos. Meas. Tech., 13, 1287–1297, https://doi.org/10.5194/amt-13-1287-2020, 2020. a, b
McElroy, C. T., Nowlan, C. R., Drummond, J. R., Bernath, P. F., Barton, D. V., Dufour, D. G., Midwinter, C., Hall, R. B., Ogyu, A., Ullberg, A., Wardle, D. I., Kar, J., Zou, J., Nichitiu, F., Boone, C. D., Walker, K. A., and Rowlands, N.: The ACE-MAESTRO instrument on SCISAT: Description, performance, and preliminary results, Appl. Opt., 46, 4341–4356, https://doi.org/10.1364/AO.46.004341, 2007. a, b, c
MIPAS IMK-IAA: Level 2 Data, Version 8, IMK-IAA, MIPAS [data set], available at: https://imk-asf-mipas.imk.kit.edu/ (last access: 11 June 2024), 2024. a
Molod, A., Takacs, L., Suarez, M., and Bacmeister, J.: Development of the GEOS-5 atmospheric general circulation model: evolution from MERRA to MERRA2, Geosci. Model Dev., 8, 1339–1356, https://doi.org/10.5194/gmd-8-1339-2015, 2015. a
Murtagh, D., Frisk, U., Merino, F., Ridal, M., Jonsson, A., Stegman, J., Witt, G., Eriksson, P., Jiménez, C., Megie, G., de la Noë, J., Ricaud, P., Baron, P., Pardo, J. R., Hauchcorne, A., Llewellyn, E. J., Degenstein, D. A., Gattinger, R. L., Lloyd, N. D., Evans, W. F. J., McDade, I. C., Haley, C. S., Sioris, C., von Savigny, C., Solheim, B. H., McConnell, J. C., Strong, K., Richardson, E. H., Leppelmeier, G. W., Kyrölä, E., Auvinen, H., and Oikarinen, L.: An overview of the Odin atmospheric mission, Can. J. Phys., 80, 309–319, https://doi.org/10.1139/p01-157, 2002. a, b, c
NASA/LARC/SD/ASDC: SAGE III Meteor-3M L2 Solar Event Species Profiles (HDF-EOS) V004, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/M3M/SAGEIII/SOLAR_HDF-EOS_L2-V4.0, 2009. a
NASA/LARC/SD/ASDC: Stratospheric Aerosol and Gas Experiment (SAGE) II Version 7.0 Aerosol, O3, NO2 and H2O Profiles in binary format, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/ERBS/SAGEII/SOLAR_BINARY_L2-V7.0, 2012. a
NASA/LARC/SD/ASDC: SAGE III/ISS L2 Solar Event Species Profiles (HDF5) V053, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/ISS/SAGEIII/SOLAR_HDF5_L2-V5.3, 2024. a
Nielsen, J. E., Pawson, S., Molod, A., Auer, B., da Silva, A. M., Douglass, A. R., Duncan, B., Liang, Q., Manyin, M., Oman, L. D., Putman, W., Strahan, S. E., and Wargan, K.: Chemical Mechanisms and Their Applications in the Goddard Earth Observing System (GEOS) Earth System Model, J. Adv. Model Earth Sy., 9, 3019–3044, https://doi.org/10.1002/2017MS001011, 2017. a
OSIRIS: OSIRIS Version 7.2 Level 2, University of Saskatchewan [data set], available at: https://research-groups.usask.ca/osiris/data-products.php (last access: 10 June 2024), 2024. a
Prather, M. J.: Ozone in the upper stratosphere and mesosphere, J. Geophys. Res.-Oceans, 86, 5325–5338, https://doi.org/10.1029/JC086iC06p05325, 1981. a, b
Rault, D. F. and Loughman, R. P.: The OMPS Limb Profiler Environmental Data Record Algorithm Theoretical Basis Document and Expected Performance, IEEE T. Geosci. Remote, 51, 2505–2527, https://doi.org/10.1109/TGRS.2012.2213093, 2013. a, b
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J., Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L., Kim, G.-K., Bloom, S., Chen, J., Collins, D., Conaty, A., da Silva, A., Gu, W., Joiner, J., Koster, R. D., Lucchesi, R., Molod, A., Owens, T., Pawson, S., Pegion, P., Redder, C. R., Reichle, R., Robertson, F. R., Ruddick, A. G., Sienkiewicz, M., and Woollen, J.: MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications, J. Climate, 24, 3624–3648, https://doi.org/10.1175/JCLI-D-11-00015.1, 2011. a
Rozanov, A.: SCIAMACHY Limb NO2 and O3 Dataset, IUP/IFP University of Bremen [data set], http://www.iup.uni-bremen.de/scia-arc/ (last access: 11 June 2024), 2024. a
SAGE III/ISS Data Products User’s Guide: Stratospheric Aerosol and Gas Experiment on the International Space Station (SAGE III/ISS) Data Products User’s Guide, https://asdc.larc.nasa.gov/documents/sageiii-iss/guide/DPUG_G3B_v05.30.pdf (last access: 18 May 2023), 2023. a
Sakazaki, T., Fujiwara, M., Mitsuda, C., Imai, K., Manago, N., Naito, Y., Nakamura, T., Akiyoshi, H., Kinnison, D., Sano, T., Suzuki, M., and Shiotani, M.: Diurnal ozone variations in the stratosphere revealed in observations from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) on board the International Space Station (ISS), J. Geophys. Res.-Atmos., 118, 2991–3006, https://doi.org/10.1002/jgrd.50220, 2013. a, b
Sakazaki, T., Shiotani, M., Suzuki, M., Kinnison, D., Zawodny, J. M., McHugh, M., and Walker, K. A.: Sunset–sunrise difference in solar occultation ozone measurements (SAGE II, HALOE, and ACE–FTS) and its relationship to tidal vertical winds, Atmos. Chem. Phys., 15, 829–843, https://doi.org/10.5194/acp-15-829-2015, 2015. a
Serdyuchenko, A., Gorshelev, V., Weberand, M., and Burrows, J. P.: New broadband high-resolution ozone absorption cross-sections, Spectrosc. Eur., 23, 14–17, 2011. a
Sheese, P. and Walker, K.: Data Quality Flags for ACE-FTS Level 2 Version 4.1/4.2 Data Set, Borealis, V30, Borealis [data set], https://doi.org/10.5683/SP2/BC4ATC, 2023a. a
Sheese, P. and Walker, K.: Data Quality Flags for ACE-FTS Level 2 Version 5.2 Data Set, Borealis, V3, Borealis [data set], https://doi.org/10.5683/SP3/NAYNFE, 2023b. a
Sheese, P. E., Boone, C. D., and Walker, K. A.: Detecting physically unrealistic outliers in ACE-FTS atmospheric measurements, Atmos. Meas. Tech., 8, 741–750, https://doi.org/10.5194/amt-8-741-2015, 2015. a
Sheese, P. E., Walker, K. A., Boone, C. D., McLinden, C. A., Bernath, P. F., Bourassa, A. E., Burrows, J. P., Degenstein, D. A., Funke, B., Fussen, D., Manney, G. L., McElroy, C. T., Murtagh, D., Randall, C. E., Raspollini, P., Rozanov, A., Russell III, J. M., Suzuki, M., Shiotani, M., Urban, J., von Clarmann, T., and Zawodny, J. M.: Validation of ACE-FTS version 3.5 NOy species profiles using correlative satellite measurements, Atmos. Meas. Tech., 9, 5781–5810, https://doi.org/10.5194/amt-9-5781-2016, 2016. a, b, c, d, e, f
Sheese, P. E., Walker, K. A., Boone, C. D., Bernath, P. F., Froidevaux, L., Funke, B., Raspollini, P., and von Clarmann, T.: ACE-FTS ozone, water vapour, nitrous oxide, nitric acid, and carbon monoxide profile comparisons with MIPAS and MLS, J. Quant. Spectrosc. Ra., 186, 63–80, https://doi.org/10.1016/j.jqsrt.2016.06.026 (satellite Remote Sensing and Spectroscopy: Joint ACE-Odin Meeting, October 2015), 2017. a
Sheese, P. E., Walker, K. A., Boone, C. D., Degenstein, D. A., Kolonjari, F., Plummer, D., Kinnison, D. E., Jöckel, P., and von Clarmann, T.: Model estimations of geophysical variability between satellite measurements of ozone profiles, Atmos. Meas. Tech., 14, 1425–1438, https://doi.org/10.5194/amt-14-1425-2021, 2021. a
Sheese, P. E., Walker, K. A., Boone, C. D., Bourassa, A. E., Degenstein, D., Froidevaux, L., McElroy, C. T., Murtagh, D., Russell III, J. M., and Zou, J.: Assessment of the quality of ACE-FTS stratospheric ozone data, Atmos. Meas. Tech., 15, 1233–1249, https://doi.org/10.5194/amt-15-1233-2022, 2022. a, b, c, d, e
Sioris, C. E., Zou, J., Plummer, D. A., Boone, C. D., McElroy, C. T., Sheese, P. E., Moeini, O., and Bernath, P. F.: Upper tropospheric water vapour variability at high latitudes – Part 1: Influence of the annular modes, Atmos. Chem. Phys., 16, 3265–3278, https://doi.org/10.5194/acp-16-3265-2016, 2016. a, b
Sofieva, V. F., Szeląg, M., Tamminen, J., Kyrölä, E., Degenstein, D., Roth, C., Zawada, D., Rozanov, A., Arosio, C., Burrows, J. P., Weber, M., Laeng, A., Stiller, G. P., von Clarmann, T., Froidevaux, L., Livesey, N., van Roozendael, M., and Retscher, C.: Measurement report: regional trends of stratospheric ozone evaluated using the MErged GRIdded Dataset of Ozone Profiles (MEGRIDOP), Atmos. Chem. Phys., 21, 6707–6720, https://doi.org/10.5194/acp-21-6707-2021, 2021. a
SPARC-DI: The SPARC (Stratospheric Processes And their Role in Climate) Data Initiative: Assessment of stratospheric trace gas and aerosol climatologies from satellite limb sounders, SPARC Report No. 8, WCRP-05/2017, https://doi.org/10.3929/ethz-a-010863911, 2017. a, b, c, d
Strahan, S. E., Duncan, B. N., and Hoor, P.: Observationally derived transport diagnostics for the lowermost stratosphere and their application to the GMI chemistry and transport model, Atmos. Chem. Phys., 7, 2435–2445, https://doi.org/10.5194/acp-7-2435-2007, 2007. a
Strode, S.: Diurnal Scaling Factors, NASA [data set], https://avdc.gsfc.nasa.gov/pub/data/project/GMI_SF/ (last access: 10 September 2023), 2021. a
Tamminen, J., Kyrölä, E., Sofieva, V. F., Laine, M., Bertaux, J.-L., Hauchecorne, A., Dalaudier, F., Fussen, D., Vanhellemont, F., Fanton-d'Andon, O., Barrot, G., Mangin, A., Guirlet, M., Blanot, L., Fehr, T., Saavedra de Miguel, L., and Fraisse, R.: GOMOS data characterisation and error estimation, Atmos. Chem. Phys., 10, 9505–9519, https://doi.org/10.5194/acp-10-9505-2010, 2010. a, b
Thomason, L. W., Moore, J. R., Pitts, M. C., Zawodny, J. M., and Chiou, E. W.: An evaluation of the SAGE III version 4 aerosol extinction coefficient and water vapor data products, Atmos. Chem. Phys., 10, 2159–2173, https://doi.org/10.5194/acp-10-2159-2010, 2010. a, b, c, d
Urban, J., Lautié, N., Le Flochmoën, E., Jiménez, C., Eriksson, P., de La Noë, J., Dupuy, E., Ekström, M., El Amraoui, L., Frisk, U., Murtagh, D., Olberg, M., and Ricaud, P.: Odin/SMR limb observations of stratospheric trace gases: Level 2 processing of ClO, N2O, HNO3, and O3, J. Geophys. Res.-Atmos., 110, https://doi.org/10.1029/2004JD005741, 2005. a
Vandaele, A. C., Hermans, C., Fally, S., Carleer, M., Colin, R., Mérienne, M.-F., Jenouvrier, A., and Coquart, B.: High-resolution Fourier transform measurement of the NO2 visible and near-infrared absorption cross sections: Temperature and pressure effects, J. Geophys. Res.-Atmos., 107, ACH3-1–ACH3-12, https://doi.org/10.1029/2001JD000971, 2002. a
von Clarmann, T., Glatthor, N., Grabowski, U., Höpfner, M., Kellmann, S., Kiefer, M., Linden, A., Tsidu, G. M., Milz, M., Steck, T., Stiller, G. P., Wang, D. Y., Fischer, H., Funke, B., Gil-López, S., and López-Puertas, M.: Retrieval of temperature and tangent altitude pointing from limb emission spectra recorded from space by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), J. Geophys. Res.-Atmos., 108, 4736, https://doi.org/10.1029/2003JD003602, 2003. a
von Clarmann, T., Höpfner, M., Kellmann, S., Linden, A., Chauhan, S., Funke, B., Grabowski, U., Glatthor, N., Kiefer, M., Schieferdecker, T., Stiller, G. P., and Versick, S.: Retrieval of temperature, H2O, O3, HNO3, CH4, N2O, ClONO2 and ClO from MIPAS reduced resolution nominal mode limb emission measurements, Atmos. Meas. Tech., 2, 159–175, https://doi.org/10.5194/amt-2-159-2009, 2009. a, b
Wang, H. J., Cunnold, D. M., Thomason, L. W., Zawodny, J. M., and Bodeker, G. E.: Assessment of SAGE version 6.1 ozone data quality, J. Geophys. Res.: Atmos., 107, ACH8-1-18, https://doi.org/10.1029/2002JD002418, 2002. a, b
Wang, H.-J., Cunnold, D. M., Trepte, C., Thomason, L. W., and Zawodny, J. M.: SAGE III solar ozone measurements: Initial results, Geophys. Res. Lett., 33, L03805, https://doi.org/10.1029/2005GL025099, 2006. a
Wang, H. J. R., Damadeo, R., Flittner, D., Kramarova, N., Taha, G., Davis, S., Thompson, A. M., Strahan, S., Wang, Y., Froidevaux, L., Degenstein, D., Bourassa, A., Steinbrecht, W., Walker, K. A., Querel, R., Leblanc, T., Godin-Beekmann, S., Hurst, D., and Hall, E.: Validation of SAGE III/ISS Solar Occultation Ozone Products With Correlative Satellite and Ground-Based Measurements, J. Geophys. Res.-Atmos., 125, e2020JD032430, https://doi.org/10.1029/2020JD032430, 2020. a, b, c, d, e, f, g
Waters, J. W., Froidevaux, L., Harwood, R. S., Jarnot, R. F., Pickett, H. M., Read, W. G., Siegel, P. H., Cofield, R. E., Filipiak, M. J., Flower, D. A., Holden, J. R., Lau, G. K., Livesey, N. J., Manney, G. L., Pumphrey, H. C., Santee, M. L., Wu, D. L., Cuddy, D. T., Lay, R. R., Loo, M. S., Perun, V. S., Schwartz, M. J., Stek, P. C., Thurstans, R. P., Boyles, M. A., Chandra, K. M., Chavez, M. C., Chen, G.-S., Chudasama, B. V., Dodge, R., Fuller, R. A., Girard, M. A., Jiang, J. H., Jiang, Y., Knosp, B. W., LaBelle, R. C., Lam, J. C., Lee, K. A., Miller, D., Oswald, J. E., Patel, N. C., Pukala, D. M., Quintero, O., Scaff, D. M., Van Snyder, W., Tope, M. C., Wagner, P. A., and Walch, M. J.: The Earth observing system microwave limb sounder (EOS MLS) on the aura Satellite, IEEE T. Geosci. Remote, 44, 1075–1092, https://doi.org/10.1109/TGRS.2006.873771, 2006. a, b, c
Short summary
The MAESTRO instrument has been monitoring ozone and NO2 since February 2004. A new version of these data products has recently been released; however, these new products must be validated against other datasets to ensure their validity. This study presents such an assessment, using measurements from 11 satellite instruments to characterize the new MAESTRO products. In the stratosphere, good agreement is found for ozone and acceptable agreement is found for NO2 with these other datasets.
The MAESTRO instrument has been monitoring ozone and NO2 since February 2004. A new version of...
